******Results of the Case-control Association tests ****** There are 320 individuals from 20 independent families. 80 of the individuals are affected, 240 of the individuals are unaffected, and 0 of the individuals are of unknown phenotype. There are 160 males and 160 females. The prevalence values used in the RM test statistic for males and females are 0.085625 and 0.085625, respectively. **************************************** Analysis of Marker 1: rs1 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.101957 pvalue = 0.0781983 df = 1 ***************************************** RCHI test RCHI statistic value = 3.018470 pvalue = 0.0823211 df = 1 ***************************************** RW test RW statistic value = 2.723952 pvalue = 0.098853 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6050 sd = 0.0528 freq = 0.6596 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 allele 2 : freq = 0.3950 sd = 0.0528 freq = 0.3404 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5813 freq = 0.6646 freq = 0.0000 freq = 0.6438 allele 2 : freq = 0.4188 freq = 0.3354 freq = 0.0000 freq = 0.3563 ***************************************** **************************************** Analysis of Marker 2: rs2 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000189 pvalue = 0.989035 df = 1 ***************************************** RCHI test RCHI statistic value = 0.118748 pvalue = 0.730397 df = 1 ***************************************** RW test RW statistic value = 0.584470 pvalue = 0.444565 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2117 sd = 0.0441 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 allele 2 : freq = 0.7883 sd = 0.0441 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 freq = 0.2104 freq = 0.0000 freq = 0.2141 allele 2 : freq = 0.7750 freq = 0.7896 freq = 0.0000 freq = 0.7859 ***************************************** **************************************** Analysis of Marker 3: rs3 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.628546 pvalue = 0.201904 df = 1 ***************************************** RCHI test RCHI statistic value = 1.670009 pvalue = 0.196257 df = 1 ***************************************** RW test RW statistic value = 1.011062 pvalue = 0.314648 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6183 sd = 0.0525 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 allele 2 : freq = 0.3817 sd = 0.0525 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6062 freq = 0.5417 freq = 0.0000 freq = 0.5578 allele 2 : freq = 0.3937 freq = 0.4583 freq = 0.0000 freq = 0.4422 ***************************************** **************************************** Analysis of Marker 4: rs4 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.034870 pvalue = 0.851869 df = 1 ***************************************** RCHI test RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1 ***************************************** RW test RW statistic value = 1.612144 pvalue = 0.204191 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6650 sd = 0.0510 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 allele 2 : freq = 0.3350 sd = 0.0510 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.7042 freq = 0.0000 freq = 0.7016 allele 2 : freq = 0.3063 freq = 0.2958 freq = 0.0000 freq = 0.2984 ***************************************** **************************************** Analysis of Marker 5: rs5 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.279137 pvalue = 0.597268 df = 1 ***************************************** RCHI test RCHI statistic value = 0.940889 pvalue = 0.332049 df = 1 ***************************************** RW test RW statistic value = 0.014446 pvalue = 0.904333 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8717 sd = 0.0361 freq = 0.8712 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 allele 2 : freq = 0.1283 sd = 0.0361 freq = 0.1288 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8562 freq = 0.8896 freq = 0.0000 freq = 0.8812 allele 2 : freq = 0.1437 freq = 0.1104 freq = 0.0000 freq = 0.1187 ***************************************** **************************************** Analysis of Marker 6: rs6 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.134728 pvalue = 0.71358 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001941 pvalue = 0.964858 df = 1 ***************************************** RW test RW statistic value = 0.035816 pvalue = 0.849895 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6383 sd = 0.0519 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 allele 2 : freq = 0.3617 sd = 0.0519 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 freq = 0.6521 freq = 0.0000 freq = 0.6516 allele 2 : freq = 0.3500 freq = 0.3479 freq = 0.0000 freq = 0.3484 ***************************************** **************************************** Analysis of Marker 7: rs7 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.975807 pvalue = 0.323236 df = 1 ***************************************** RCHI test RCHI statistic value = 1.552688 pvalue = 0.212739 df = 1 ***************************************** RW test RW statistic value = 2.667303 pvalue = 0.102429 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5167 sd = 0.0540 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 allele 2 : freq = 0.4833 sd = 0.0540 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.5625 freq = 0.0000 freq = 0.5469 allele 2 : freq = 0.5000 freq = 0.4375 freq = 0.0000 freq = 0.4531 ***************************************** **************************************** Analysis of Marker 8: rs8 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.039657 pvalue = 0.842154 df = 1 ***************************************** RCHI test RCHI statistic value = 0.084971 pvalue = 0.770671 df = 1 ***************************************** RW test RW statistic value = 0.473315 pvalue = 0.491466 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4350 sd = 0.0535 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.5650 sd = 0.0535 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.4417 freq = 0.0000 freq = 0.4453 allele 2 : freq = 0.5437 freq = 0.5583 freq = 0.0000 freq = 0.5547 ***************************************** **************************************** Analysis of Marker 9: rs9 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.601498 pvalue = 0.205691 df = 1 ***************************************** RCHI test RCHI statistic value = 3.149077 pvalue = 0.0759699 df = 1 ***************************************** RW test RW statistic value = 1.375245 pvalue = 0.240913 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8583 sd = 0.0377 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 allele 2 : freq = 0.1417 sd = 0.0377 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8750 freq = 0.8104 freq = 0.0000 freq = 0.8266 allele 2 : freq = 0.1250 freq = 0.1896 freq = 0.0000 freq = 0.1734 ***************************************** **************************************** Analysis of Marker 10: rs10 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.051915 pvalue = 0.819765 df = 1 ***************************************** RCHI test RCHI statistic value = 0.023283 pvalue = 0.878723 df = 1 ***************************************** RW test RW statistic value = 0.000282 pvalue = 0.986591 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8067 sd = 0.0427 freq = 0.7904 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.1933 sd = 0.0427 freq = 0.2096 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7875 freq = 0.0000 freq = 0.7859 allele 2 : freq = 0.2188 freq = 0.2125 freq = 0.0000 freq = 0.2141 ***************************************** **************************************** Analysis of Marker 11: rs11 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.718602 pvalue = 0.396603 df = 1 ***************************************** RCHI test RCHI statistic value = 0.985522 pvalue = 0.320839 df = 1 ***************************************** RW test RW statistic value = 0.160732 pvalue = 0.688483 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8233 sd = 0.0412 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.1767 sd = 0.0412 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.8438 freq = 0.0000 freq = 0.8344 allele 2 : freq = 0.1938 freq = 0.1562 freq = 0.0000 freq = 0.1656 ***************************************** **************************************** Analysis of Marker 12: rs12 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.665125 pvalue = 0.414757 df = 1 ***************************************** RCHI test RCHI statistic value = 0.419130 pvalue = 0.517372 df = 1 ***************************************** RW test RW statistic value = 0.171040 pvalue = 0.679189 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3217 sd = 0.0505 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339 allele 2 : freq = 0.6783 sd = 0.0505 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.3563 freq = 0.0000 freq = 0.3484 allele 2 : freq = 0.6750 freq = 0.6438 freq = 0.0000 freq = 0.6516 ***************************************** **************************************** Analysis of Marker 13: rs13 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.649237 pvalue = 0.420386 df = 1 ***************************************** RCHI test RCHI statistic value = 0.139113 pvalue = 0.709165 df = 1 ***************************************** RW test RW statistic value = 0.022688 pvalue = 0.88027 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5133 sd = 0.0540 freq = 0.4904 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 allele 2 : freq = 0.4867 sd = 0.0540 freq = 0.5096 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5312 freq = 0.5125 freq = 0.0000 freq = 0.5172 allele 2 : freq = 0.4688 freq = 0.4875 freq = 0.0000 freq = 0.4828 ***************************************** **************************************** Analysis of Marker 14: rs14 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.595007 pvalue = 0.44049 df = 1 ***************************************** RCHI test RCHI statistic value = 1.244666 pvalue = 0.264574 df = 1 ***************************************** RW test RW statistic value = 0.444057 pvalue = 0.505171 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5900 sd = 0.0531 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 allele 2 : freq = 0.4100 sd = 0.0531 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6062 freq = 0.6604 freq = 0.0000 freq = 0.6469 allele 2 : freq = 0.3937 freq = 0.3396 freq = 0.0000 freq = 0.3531 ***************************************** **************************************** Analysis of Marker 15: rs15 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.243184 pvalue = 0.621916 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 1.393730 pvalue = 0.237776 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8700 sd = 0.0238 allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1300 sd = 0.0238 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8500 freq = 0.8500 freq = 0.0000 freq = 0.8500 allele 2 : freq = 0.1500 freq = 0.1500 freq = 0.0000 freq = 0.1500 ***************************************** **************************************** Analysis of Marker 16: rs16 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.131096 pvalue = 0.717298 df = 1 ***************************************** RCHI test RCHI statistic value = 0.290161 pvalue = 0.590118 df = 1 ***************************************** RW test RW statistic value = 1.950244 pvalue = 0.162561 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5033 sd = 0.0540 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.4967 sd = 0.0540 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5062 freq = 0.4792 freq = 0.0000 freq = 0.4859 allele 2 : freq = 0.4938 freq = 0.5208 freq = 0.0000 freq = 0.5141 ***************************************** **************************************** Analysis of Marker 17: rs17 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.815121 pvalue = 0.366611 df = 1 ***************************************** RCHI test RCHI statistic value = 1.138553 pvalue = 0.285958 df = 1 ***************************************** RW test RW statistic value = 0.012729 pvalue = 0.910171 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4050 sd = 0.0530 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 allele 2 : freq = 0.5950 sd = 0.0530 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.3604 freq = 0.0000 freq = 0.3734 allele 2 : freq = 0.5875 freq = 0.6396 freq = 0.0000 freq = 0.6266 ***************************************** **************************************** Analysis of Marker 18: rs18 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.515168 pvalue = 0.218352 df = 1 ***************************************** RCHI test RCHI statistic value = 0.498513 pvalue = 0.480154 df = 1 ***************************************** RW test RW statistic value = 0.387036 pvalue = 0.533862 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1883 sd = 0.0422 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.8117 sd = 0.0422 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1625 freq = 0.0000 freq = 0.1688 allele 2 : freq = 0.8125 freq = 0.8375 freq = 0.0000 freq = 0.8313 ***************************************** **************************************** Analysis of Marker 19: rs19 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.029284 pvalue = 0.864126 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.066726 pvalue = 0.796165 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7633 sd = 0.0459 freq = 0.7712 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 allele 2 : freq = 0.2367 sd = 0.0459 freq = 0.2288 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.7562 freq = 0.0000 freq = 0.7562 allele 2 : freq = 0.2437 freq = 0.2437 freq = 0.0000 freq = 0.2437 ***************************************** **************************************** Analysis of Marker 20: rs20 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.288826 pvalue = 0.590974 df = 1 ***************************************** RCHI test RCHI statistic value = 0.391001 pvalue = 0.531774 df = 1 ***************************************** RW test RW statistic value = 0.638246 pvalue = 0.424347 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.5437 freq = 0.0000 freq = 0.5516 allele 2 : freq = 0.4250 freq = 0.4562 freq = 0.0000 freq = 0.4484 ***************************************** **************************************** Analysis of Marker 21: rs21 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.092789 pvalue = 0.760661 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001989 pvalue = 0.964427 df = 1 ***************************************** RW test RW statistic value = 0.003475 pvalue = 0.952995 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3500 sd = 0.0515 freq = 0.3212 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.6500 sd = 0.0515 freq = 0.6788 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3312 freq = 0.3292 freq = 0.0000 freq = 0.3297 allele 2 : freq = 0.6687 freq = 0.6708 freq = 0.0000 freq = 0.6703 ***************************************** **************************************** Analysis of Marker 22: rs22 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.765091 pvalue = 0.38174 df = 1 ***************************************** RCHI test RCHI statistic value = 0.933919 pvalue = 0.333847 df = 1 ***************************************** RW test RW statistic value = 0.072307 pvalue = 0.788007 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.8021 freq = 0.0000 freq = 0.7922 allele 2 : freq = 0.2375 freq = 0.1979 freq = 0.0000 freq = 0.2078 ***************************************** **************************************** Analysis of Marker 23: rs23 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.495171 pvalue = 0.0615481 df = 1 ***************************************** RCHI test RCHI statistic value = 2.478737 pvalue = 0.115395 df = 1 ***************************************** RW test RW statistic value = 1.729199 pvalue = 0.188513 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7233 sd = 0.0483 freq = 0.6365 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335 allele 2 : freq = 0.2767 sd = 0.0483 freq = 0.3635 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7375 freq = 0.6625 freq = 0.0000 freq = 0.6813 allele 2 : freq = 0.2625 freq = 0.3375 freq = 0.0000 freq = 0.3187 ***************************************** **************************************** Analysis of Marker 24: rs24 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.595238 pvalue = 0.440401 df = 1 ***************************************** RCHI test RCHI statistic value = 0.109916 pvalue = 0.740239 df = 1 ***************************************** RW test RW statistic value = 0.082691 pvalue = 0.773683 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4417 sd = 0.0536 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 allele 2 : freq = 0.5583 sd = 0.0536 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.4667 freq = 0.0000 freq = 0.4625 allele 2 : freq = 0.5500 freq = 0.5333 freq = 0.0000 freq = 0.5375 ***************************************** **************************************** Analysis of Marker 25: rs25 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.245474 pvalue = 0.62028 df = 1 ***************************************** RCHI test RCHI statistic value = 0.113692 pvalue = 0.735979 df = 1 ***************************************** RW test RW statistic value = 0.012413 pvalue = 0.911289 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2333 sd = 0.0457 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 allele 2 : freq = 0.7667 sd = 0.0457 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 freq = 0.2396 freq = 0.0000 freq = 0.2359 allele 2 : freq = 0.7750 freq = 0.7604 freq = 0.0000 freq = 0.7641 ***************************************** **************************************** Analysis of Marker 26: rs26 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.972947 pvalue = 0.160135 df = 1 ***************************************** RCHI test RCHI statistic value = 0.486215 pvalue = 0.485621 df = 1 ***************************************** RW test RW statistic value = 0.100362 pvalue = 0.751395 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5833 sd = 0.0533 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 allele 2 : freq = 0.4167 sd = 0.0533 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.6208 freq = 0.0000 freq = 0.6125 allele 2 : freq = 0.4125 freq = 0.3792 freq = 0.0000 freq = 0.3875 ***************************************** **************************************** Analysis of Marker 27: rs27 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.014760 pvalue = 0.903301 df = 1 ***************************************** RCHI test RCHI statistic value = 0.194115 pvalue = 0.659513 df = 1 ***************************************** RW test RW statistic value = 1.098655 pvalue = 0.294561 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6417 sd = 0.0518 freq = 0.6423 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 allele 2 : freq = 0.3583 sd = 0.0518 freq = 0.3577 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6687 freq = 0.6479 freq = 0.0000 freq = 0.6531 allele 2 : freq = 0.3312 freq = 0.3521 freq = 0.0000 freq = 0.3469 ***************************************** **************************************** Analysis of Marker 28: rs28 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.012922 pvalue = 0.909497 df = 1 ***************************************** RCHI test RCHI statistic value = 0.011155 pvalue = 0.915886 df = 1 ***************************************** RW test RW statistic value = 0.791930 pvalue = 0.373517 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1817 sd = 0.0416 freq = 0.1904 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 allele 2 : freq = 0.8183 sd = 0.0416 freq = 0.8096 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1938 freq = 0.1896 freq = 0.0000 freq = 0.1906 allele 2 : freq = 0.8063 freq = 0.8104 freq = 0.0000 freq = 0.8094 ***************************************** **************************************** Analysis of Marker 29: rs29 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.688291 pvalue = 0.193826 df = 1 ***************************************** RCHI test RCHI statistic value = 1.061435 pvalue = 0.302888 df = 1 ***************************************** RW test RW statistic value = 0.096608 pvalue = 0.755939 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327 allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2562 freq = 0.3042 freq = 0.0000 freq = 0.2922 allele 2 : freq = 0.7438 freq = 0.6958 freq = 0.0000 freq = 0.7078 ***************************************** **************************************** Analysis of Marker 30: rs30 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.030037 pvalue = 0.862405 df = 1 ***************************************** RCHI test RCHI statistic value = 0.357050 pvalue = 0.550149 df = 1 ***************************************** RW test RW statistic value = 2.277075 pvalue = 0.131299 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6150 sd = 0.0526 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 allele 2 : freq = 0.3850 sd = 0.0526 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6188 freq = 0.5896 freq = 0.0000 freq = 0.5969 allele 2 : freq = 0.3812 freq = 0.4104 freq = 0.0000 freq = 0.4031 ***************************************** **************************************** Analysis of Marker 31: rs31 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.014790 pvalue = 0.903205 df = 1 ***************************************** RCHI test RCHI statistic value = 0.202589 pvalue = 0.652639 df = 1 ***************************************** RW test RW statistic value = 0.214084 pvalue = 0.643585 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2283 sd = 0.0453 freq = 0.2038 sd = 0.0306 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 allele 2 : freq = 0.7717 sd = 0.0453 freq = 0.7962 sd = 0.0306 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2188 freq = 0.2000 freq = 0.0000 freq = 0.2047 allele 2 : freq = 0.7812 freq = 0.8000 freq = 0.0000 freq = 0.7953 ***************************************** **************************************** Analysis of Marker 32: rs32 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.846129 pvalue = 0.35765 df = 1 ***************************************** RCHI test RCHI statistic value = 1.375123 pvalue = 0.240934 df = 1 ***************************************** RW test RW statistic value = 3.816160 pvalue = 0.0507604 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2733 sd = 0.0481 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 allele 2 : freq = 0.7267 sd = 0.0481 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2625 freq = 0.2125 freq = 0.0000 freq = 0.2250 allele 2 : freq = 0.7375 freq = 0.7875 freq = 0.0000 freq = 0.7750 ***************************************** **************************************** Analysis of Marker 33: rs33 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.174668 pvalue = 0.278444 df = 1 ***************************************** RCHI test RCHI statistic value = 0.500194 pvalue = 0.479415 df = 1 ***************************************** RW test RW statistic value = 0.000756 pvalue = 0.978067 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5017 sd = 0.0540 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 allele 2 : freq = 0.4983 sd = 0.0540 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5062 freq = 0.4708 freq = 0.0000 freq = 0.4797 allele 2 : freq = 0.4938 freq = 0.5292 freq = 0.0000 freq = 0.5203 ***************************************** **************************************** Analysis of Marker 34: rs34 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.910875 pvalue = 0.339882 df = 1 ***************************************** RCHI test RCHI statistic value = 0.621134 pvalue = 0.430626 df = 1 ***************************************** RW test RW statistic value = 0.102725 pvalue = 0.748584 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8712 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1288 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8938 freq = 0.8667 freq = 0.0000 freq = 0.8734 allele 2 : freq = 0.1062 freq = 0.1333 freq = 0.0000 freq = 0.1266 ***************************************** **************************************** Analysis of Marker 35: rs35 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.007475 pvalue = 0.931101 df = 1 ***************************************** RCHI test RCHI statistic value = 0.070431 pvalue = 0.79071 df = 1 ***************************************** RW test RW statistic value = 0.432537 pvalue = 0.510747 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3067 sd = 0.0498 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 allele 2 : freq = 0.6933 sd = 0.0498 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.3375 freq = 0.0000 freq = 0.3344 allele 2 : freq = 0.6750 freq = 0.6625 freq = 0.0000 freq = 0.6656 ***************************************** **************************************** Analysis of Marker 36: rs36 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001557 pvalue = 0.968529 df = 1 ***************************************** RCHI test RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1 ***************************************** RW test RW statistic value = 1.612144 pvalue = 0.204191 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7033 sd = 0.0493 freq = 0.6904 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 allele 2 : freq = 0.2967 sd = 0.0493 freq = 0.3096 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.6833 freq = 0.0000 freq = 0.6859 allele 2 : freq = 0.3063 freq = 0.3167 freq = 0.0000 freq = 0.3141 ***************************************** **************************************** Analysis of Marker 37: rs37 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.644061 pvalue = 0.422244 df = 1 ***************************************** RCHI test RCHI statistic value = 1.275304 pvalue = 0.258774 df = 1 ***************************************** RW test RW statistic value = 0.185373 pvalue = 0.666796 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6417 sd = 0.0518 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 allele 2 : freq = 0.3583 sd = 0.0518 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6250 freq = 0.6792 freq = 0.0000 freq = 0.6656 allele 2 : freq = 0.3750 freq = 0.3208 freq = 0.0000 freq = 0.3344 ***************************************** **************************************** Analysis of Marker 38: rs38 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.289286 pvalue = 0.590679 df = 1 ***************************************** RCHI test RCHI statistic value = 1.394290 pvalue = 0.237682 df = 1 ***************************************** RW test RW statistic value = 0.351019 pvalue = 0.553537 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6833 sd = 0.0502 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335 allele 2 : freq = 0.3167 sd = 0.0502 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6687 freq = 0.6125 freq = 0.0000 freq = 0.6266 allele 2 : freq = 0.3312 freq = 0.3875 freq = 0.0000 freq = 0.3734 ***************************************** **************************************** Analysis of Marker 39: rs39 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.058346 pvalue = 0.80913 df = 1 ***************************************** RCHI test RCHI statistic value = 0.027692 pvalue = 0.867834 df = 1 ***************************************** RW test RW statistic value = 0.000756 pvalue = 0.978067 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5500 sd = 0.0537 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 allele 2 : freq = 0.4500 sd = 0.0537 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5563 freq = 0.5479 freq = 0.0000 freq = 0.5500 allele 2 : freq = 0.4437 freq = 0.4521 freq = 0.0000 freq = 0.4500 ***************************************** **************************************** Analysis of Marker 40: rs40 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.682782 pvalue = 0.194555 df = 1 ***************************************** RCHI test RCHI statistic value = 0.826953 pvalue = 0.363155 df = 1 ***************************************** RW test RW statistic value = 0.176959 pvalue = 0.673999 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9062 freq = 0.8750 freq = 0.0000 freq = 0.8828 allele 2 : freq = 0.0938 freq = 0.1250 freq = 0.0000 freq = 0.1172 ***************************************** **************************************** Analysis of Marker 41: rs41 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.253593 pvalue = 0.262867 df = 1 ***************************************** RCHI test RCHI statistic value = 1.687694 pvalue = 0.193905 df = 1 ***************************************** RW test RW statistic value = 3.108208 pvalue = 0.0778986 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 sd = 0.0451 freq = 0.2923 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316 allele 2 : freq = 0.7750 sd = 0.0451 freq = 0.7077 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.2958 freq = 0.0000 freq = 0.2812 allele 2 : freq = 0.7625 freq = 0.7042 freq = 0.0000 freq = 0.7188 ***************************************** **************************************** Analysis of Marker 42: rs42 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.460924 pvalue = 0.226783 df = 1 ***************************************** RCHI test RCHI statistic value = 1.349309 pvalue = 0.245399 df = 1 ***************************************** RW test RW statistic value = 1.879024 pvalue = 0.170445 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.4667 freq = 0.0000 freq = 0.4813 allele 2 : freq = 0.4750 freq = 0.5333 freq = 0.0000 freq = 0.5188 ***************************************** **************************************** Analysis of Marker 43: rs43 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.312307 pvalue = 0.251977 df = 1 ***************************************** RCHI test RCHI statistic value = 0.826953 pvalue = 0.363155 df = 1 ***************************************** RW test RW statistic value = 0.231131 pvalue = 0.630687 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8883 sd = 0.0340 freq = 0.8635 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 allele 2 : freq = 0.1117 sd = 0.0340 freq = 0.1365 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9000 freq = 0.8688 freq = 0.0000 freq = 0.8766 allele 2 : freq = 0.1000 freq = 0.1313 freq = 0.0000 freq = 0.1234 ***************************************** **************************************** Analysis of Marker 44: rs44 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.007232 pvalue = 0.315567 df = 1 ***************************************** RCHI test RCHI statistic value = 0.833912 pvalue = 0.361144 df = 1 ***************************************** RW test RW statistic value = 0.192624 pvalue = 0.660741 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5083 sd = 0.0540 freq = 0.4692 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 allele 2 : freq = 0.4917 sd = 0.0540 freq = 0.5308 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5125 freq = 0.4667 freq = 0.0000 freq = 0.4781 allele 2 : freq = 0.4875 freq = 0.5333 freq = 0.0000 freq = 0.5219 ***************************************** **************************************** Analysis of Marker 45: rs45 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.686621 pvalue = 0.407316 df = 1 ***************************************** RCHI test RCHI statistic value = 0.015465 pvalue = 0.901032 df = 1 ***************************************** RW test RW statistic value = 0.067724 pvalue = 0.79468 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5483 sd = 0.0538 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 allele 2 : freq = 0.4517 sd = 0.0538 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5625 freq = 0.5563 freq = 0.0000 freq = 0.5578 allele 2 : freq = 0.4375 freq = 0.4437 freq = 0.0000 freq = 0.4422 ***************************************** **************************************** Analysis of Marker 46: rs46 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.208627 pvalue = 0.647845 df = 1 ***************************************** RCHI test RCHI statistic value = 0.628933 pvalue = 0.427747 df = 1 ***************************************** RW test RW statistic value = 0.290135 pvalue = 0.590134 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6813 freq = 0.6438 freq = 0.0000 freq = 0.6531 allele 2 : freq = 0.3187 freq = 0.3563 freq = 0.0000 freq = 0.3469 ***************************************** **************************************** Analysis of Marker 47: rs47 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.342038 pvalue = 0.558655 df = 1 ***************************************** RCHI test RCHI statistic value = 0.007124 pvalue = 0.932734 df = 1 ***************************************** RW test RW statistic value = 0.525799 pvalue = 0.468378 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6300 sd = 0.0521 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 allele 2 : freq = 0.3700 sd = 0.0521 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6312 freq = 0.6354 freq = 0.0000 freq = 0.6344 allele 2 : freq = 0.3688 freq = 0.3646 freq = 0.0000 freq = 0.3656 ***************************************** **************************************** Analysis of Marker 48: rs48 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.330760 pvalue = 0.0679954 df = 1 ***************************************** RCHI test RCHI statistic value = 3.516245 pvalue = 0.06077 df = 1 ***************************************** RW test RW statistic value = 0.733591 pvalue = 0.391722 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7950 sd = 0.0436 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.2050 sd = 0.0436 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 freq = 0.8458 freq = 0.0000 freq = 0.8281 allele 2 : freq = 0.2250 freq = 0.1542 freq = 0.0000 freq = 0.1719 ***************************************** **************************************** Analysis of Marker 49: rs49 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.189261 pvalue = 0.138976 df = 1 ***************************************** RCHI test RCHI statistic value = 4.614799 pvalue = 0.0316972 df = 1 ***************************************** RW test RW statistic value = 0.325624 pvalue = 0.568247 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5400 sd = 0.0538 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.4600 sd = 0.0538 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5437 freq = 0.6500 freq = 0.0000 freq = 0.6234 allele 2 : freq = 0.4562 freq = 0.3500 freq = 0.0000 freq = 0.3766 ***************************************** **************************************** Analysis of Marker 50: rs50 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.344434 pvalue = 0.0371301 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 5.392372 pvalue = 0.020225 df = 1 ***************************************** RW test RW statistic value = 5.881487 pvalue = 0.0153009 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6033 sd = 0.0528 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 allele 2 : freq = 0.3967 sd = 0.0528 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.4833 freq = 0.0000 freq = 0.5125 allele 2 : freq = 0.4000 freq = 0.5167 freq = 0.0000 freq = 0.4875 ***************************************** **************************************** Analysis of Marker 51: rs51 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.774408 pvalue = 0.378857 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.920777 pvalue = 0.337271 df = 1 The p-value might not be exact because of the small number of allele 1 in cases ***************************************** RW test RW statistic value = 0.000831 pvalue = 0.977005 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0483 sd = 0.0232 freq = 0.0673 sd = 0.0190 freq = 0.0000 sd = 0.0000 freq = 0.0600 sd = 0.0168 allele 2 : freq = 0.9517 sd = 0.0232 freq = 0.9327 sd = 0.0190 freq = 0.0000 sd = 0.0000 freq = 0.9400 sd = 0.0168 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0437 freq = 0.0667 freq = 0.0000 freq = 0.0609 allele 2 : freq = 0.9563 freq = 0.9333 freq = 0.0000 freq = 0.9391 ***************************************** **************************************** Analysis of Marker 52: rs52 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.523736 pvalue = 0.469253 df = 1 ***************************************** RCHI test RCHI statistic value = 0.317306 pvalue = 0.573231 df = 1 ***************************************** RW test RW statistic value = 0.138572 pvalue = 0.709705 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2967 sd = 0.0493 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 allele 2 : freq = 0.7033 sd = 0.0493 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2938 freq = 0.2687 freq = 0.0000 freq = 0.2750 allele 2 : freq = 0.7063 freq = 0.7312 freq = 0.0000 freq = 0.7250 ***************************************** **************************************** Analysis of Marker 53: rs53 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.255068 pvalue = 0.613529 df = 1 ***************************************** RCHI test RCHI statistic value = 0.128329 pvalue = 0.720171 df = 1 ***************************************** RW test RW statistic value = 2.746106 pvalue = 0.0974916 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8467 sd = 0.0389 freq = 0.8692 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 allele 2 : freq = 0.1533 sd = 0.0389 freq = 0.1308 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8562 freq = 0.0000 freq = 0.8531 allele 2 : freq = 0.1562 freq = 0.1437 freq = 0.0000 freq = 0.1469 ***************************************** **************************************** Analysis of Marker 54: rs54 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.147793 pvalue = 0.700653 df = 1 ***************************************** RCHI test RCHI statistic value = 0.066284 pvalue = 0.796826 df = 1 ***************************************** RW test RW statistic value = 0.275199 pvalue = 0.599866 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6267 sd = 0.0522 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 allele 2 : freq = 0.3733 sd = 0.0522 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6125 freq = 0.6250 freq = 0.0000 freq = 0.6219 allele 2 : freq = 0.3875 freq = 0.3750 freq = 0.0000 freq = 0.3781 ***************************************** **************************************** Analysis of Marker 55: rs55 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.040562 pvalue = 0.840385 df = 1 ***************************************** RCHI test RCHI statistic value = 0.006892 pvalue = 0.933838 df = 1 ***************************************** RW test RW statistic value = 0.415535 pvalue = 0.519174 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 sd = 0.0539 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 allele 2 : freq = 0.4750 sd = 0.0539 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5437 freq = 0.5479 freq = 0.0000 freq = 0.5469 allele 2 : freq = 0.4562 freq = 0.4521 freq = 0.0000 freq = 0.4531 ***************************************** **************************************** Analysis of Marker 56: rs56 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.134490 pvalue = 0.713821 df = 1 ***************************************** RCHI test RCHI statistic value = 0.429761 pvalue = 0.512106 df = 1 ***************************************** RW test RW statistic value = 0.159919 pvalue = 0.689231 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.7292 freq = 0.0000 freq = 0.7359 allele 2 : freq = 0.2437 freq = 0.2708 freq = 0.0000 freq = 0.2641 ***************************************** **************************************** Analysis of Marker 57: rs57 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 7.533044 pvalue = 0.00605775 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 5.971322 pvalue = 0.0145404 df = 1 ***************************************** RW test RW statistic value = 1.466864 pvalue = 0.225841 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1450 sd = 0.0380 freq = 0.0615 sd = 0.0183 freq = 0.0000 sd = 0.0000 freq = 0.0800 sd = 0.0192 allele 2 : freq = 0.8550 sd = 0.0380 freq = 0.9385 sd = 0.0183 freq = 0.0000 sd = 0.0000 freq = 0.9200 sd = 0.0192 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1437 freq = 0.0771 freq = 0.0000 freq = 0.0938 allele 2 : freq = 0.8562 freq = 0.9229 freq = 0.0000 freq = 0.9062 ***************************************** **************************************** Analysis of Marker 58: rs58 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.008342 pvalue = 0.927226 df = 1 ***************************************** RCHI test RCHI statistic value = 0.071606 pvalue = 0.789013 df = 1 ***************************************** RW test RW statistic value = 0.146802 pvalue = 0.701611 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6583 sd = 0.0512 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.3417 sd = 0.0512 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 freq = 0.6625 freq = 0.0000 freq = 0.6656 allele 2 : freq = 0.3250 freq = 0.3375 freq = 0.0000 freq = 0.3344 ***************************************** **************************************** Analysis of Marker 59: rs59 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.733593 pvalue = 0.187953 df = 1 ***************************************** RCHI test RCHI statistic value = 2.443788 pvalue = 0.117991 df = 1 ***************************************** RW test RW statistic value = 3.420763 pvalue = 0.0643812 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8283 sd = 0.0407 freq = 0.7692 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 allele 2 : freq = 0.1717 sd = 0.0407 freq = 0.2308 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.7604 freq = 0.0000 freq = 0.7766 allele 2 : freq = 0.1750 freq = 0.2396 freq = 0.0000 freq = 0.2234 ***************************************** **************************************** Analysis of Marker 60: rs60 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.440215 pvalue = 0.230105 df = 1 ***************************************** RCHI test RCHI statistic value = 0.579405 pvalue = 0.446546 df = 1 ***************************************** RW test RW statistic value = 3.558291 pvalue = 0.0592487 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4400 sd = 0.0536 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 allele 2 : freq = 0.5600 sd = 0.0536 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.4188 freq = 0.0000 freq = 0.4281 allele 2 : freq = 0.5437 freq = 0.5813 freq = 0.0000 freq = 0.5719 ***************************************** **************************************** Analysis of Marker 61: rs61 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.540961 pvalue = 0.462035 df = 1 ***************************************** RCHI test RCHI statistic value = 0.172442 pvalue = 0.677951 df = 1 ***************************************** RW test RW statistic value = 0.535522 pvalue = 0.464295 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3133 sd = 0.0501 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 allele 2 : freq = 0.6867 sd = 0.0501 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3125 freq = 0.2938 freq = 0.0000 freq = 0.2984 allele 2 : freq = 0.6875 freq = 0.7063 freq = 0.0000 freq = 0.7016 ***************************************** **************************************** Analysis of Marker 62: rs62 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.215359 pvalue = 0.642599 df = 1 ***************************************** RCHI test RCHI statistic value = 0.058006 pvalue = 0.809675 df = 1 ***************************************** RW test RW statistic value = 0.082076 pvalue = 0.774503 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2150 sd = 0.0444 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 allele 2 : freq = 0.7850 sd = 0.0444 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 freq = 0.2354 freq = 0.0000 freq = 0.2328 allele 2 : freq = 0.7750 freq = 0.7646 freq = 0.0000 freq = 0.7672 ***************************************** **************************************** Analysis of Marker 63: rs63 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.008387 pvalue = 0.31529 df = 1 ***************************************** RCHI test RCHI statistic value = 0.439885 pvalue = 0.507178 df = 1 ***************************************** RW test RW statistic value = 5.679821 pvalue = 0.0171611 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4100 sd = 0.0531 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 allele 2 : freq = 0.5900 sd = 0.0531 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.4708 freq = 0.0000 freq = 0.4625 allele 2 : freq = 0.5625 freq = 0.5292 freq = 0.0000 freq = 0.5375 ***************************************** **************************************** Analysis of Marker 64: rs64 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.021143 pvalue = 0.884391 df = 1 ***************************************** RCHI test RCHI statistic value = 0.133972 pvalue = 0.714349 df = 1 ***************************************** RW test RW statistic value = 0.408656 pvalue = 0.522652 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280 allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.7917 freq = 0.0000 freq = 0.7953 allele 2 : freq = 0.1938 freq = 0.2083 freq = 0.0000 freq = 0.2047 ***************************************** **************************************** Analysis of Marker 65: rs65 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.224113 pvalue = 0.635924 df = 1 ***************************************** RCHI test RCHI statistic value = 0.081331 pvalue = 0.775502 df = 1 ***************************************** RW test RW statistic value = 0.015786 pvalue = 0.900015 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7283 sd = 0.0480 freq = 0.7442 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 allele 2 : freq = 0.2717 sd = 0.0480 freq = 0.2558 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7250 freq = 0.7375 freq = 0.0000 freq = 0.7344 allele 2 : freq = 0.2750 freq = 0.2625 freq = 0.0000 freq = 0.2656 ***************************************** **************************************** Analysis of Marker 66: rs66 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.040521 pvalue = 0.840466 df = 1 ***************************************** RCHI test RCHI statistic value = 0.041103 pvalue = 0.839338 df = 1 ***************************************** RW test RW statistic value = 0.241334 pvalue = 0.623244 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9050 sd = 0.0317 freq = 0.8865 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217 allele 2 : freq = 0.0950 sd = 0.0317 freq = 0.1135 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9000 freq = 0.8938 freq = 0.0000 freq = 0.8953 allele 2 : freq = 0.1000 freq = 0.1062 freq = 0.0000 freq = 0.1047 ***************************************** **************************************** Analysis of Marker 67: rs67 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.346484 pvalue = 0.55611 df = 1 ***************************************** RCHI test RCHI statistic value = 0.620742 pvalue = 0.430772 df = 1 ***************************************** RW test RW statistic value = 0.192239 pvalue = 0.66106 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5417 sd = 0.0538 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 allele 2 : freq = 0.4583 sd = 0.0538 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.5396 freq = 0.0000 freq = 0.5297 allele 2 : freq = 0.5000 freq = 0.4604 freq = 0.0000 freq = 0.4703 ***************************************** **************************************** Analysis of Marker 68: rs68 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.078702 pvalue = 0.779065 df = 1 ***************************************** RCHI test RCHI statistic value = 0.293062 pvalue = 0.588265 df = 1 ***************************************** RW test RW statistic value = 0.118329 pvalue = 0.730854 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5367 sd = 0.0539 freq = 0.5558 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 allele 2 : freq = 0.4633 sd = 0.0539 freq = 0.4442 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5437 freq = 0.5708 freq = 0.0000 freq = 0.5641 allele 2 : freq = 0.4562 freq = 0.4292 freq = 0.0000 freq = 0.4359 ***************************************** **************************************** Analysis of Marker 69: rs69 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.373844 pvalue = 0.540916 df = 1 ***************************************** RCHI test RCHI statistic value = 0.379219 pvalue = 0.538022 df = 1 ***************************************** RW test RW statistic value = 0.531620 pvalue = 0.465927 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2233 sd = 0.0450 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 allele 2 : freq = 0.7767 sd = 0.0450 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 freq = 0.2000 freq = 0.0000 freq = 0.2062 allele 2 : freq = 0.7750 freq = 0.8000 freq = 0.0000 freq = 0.7937 ***************************************** **************************************** Analysis of Marker 70: rs70 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.981920 pvalue = 0.321725 df = 1 ***************************************** RCHI test RCHI statistic value = 2.656072 pvalue = 0.103155 df = 1 ***************************************** RW test RW statistic value = 3.526349 pvalue = 0.0604007 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4533 sd = 0.0538 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.5467 sd = 0.0538 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4625 freq = 0.3812 freq = 0.0000 freq = 0.4016 allele 2 : freq = 0.5375 freq = 0.6188 freq = 0.0000 freq = 0.5984 ***************************************** **************************************** Analysis of Marker 71: rs71 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.070070 pvalue = 0.791235 df = 1 ***************************************** RCHI test RCHI statistic value = 0.084708 pvalue = 0.771015 df = 1 ***************************************** RW test RW statistic value = 0.668191 pvalue = 0.413683 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7688 freq = 0.7562 freq = 0.0000 freq = 0.7594 allele 2 : freq = 0.2313 freq = 0.2437 freq = 0.0000 freq = 0.2406 ***************************************** **************************************** Analysis of Marker 72: rs72 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.666917 pvalue = 0.414128 df = 1 ***************************************** RCHI test RCHI statistic value = 0.448645 pvalue = 0.502979 df = 1 ***************************************** RW test RW statistic value = 0.224919 pvalue = 0.635317 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 sd = 0.0451 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 allele 2 : freq = 0.2250 sd = 0.0451 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7521 freq = 0.0000 freq = 0.7594 allele 2 : freq = 0.2188 freq = 0.2479 freq = 0.0000 freq = 0.2406 ***************************************** **************************************** Analysis of Marker 73: rs73 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.314937 pvalue = 0.128137 df = 1 ***************************************** RCHI test RCHI statistic value = 1.911484 pvalue = 0.166799 df = 1 ***************************************** RW test RW statistic value = 0.633245 pvalue = 0.426168 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6550 sd = 0.0513 freq = 0.6942 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.3450 sd = 0.0513 freq = 0.3058 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6250 freq = 0.6896 freq = 0.0000 freq = 0.6734 allele 2 : freq = 0.3750 freq = 0.3104 freq = 0.0000 freq = 0.3266 ***************************************** **************************************** Analysis of Marker 74: rs74 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.104620 pvalue = 0.293254 df = 1 ***************************************** RCHI test RCHI statistic value = 2.818974 pvalue = 0.0931559 df = 1 ***************************************** RW test RW statistic value = 0.997178 pvalue = 0.317994 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4233 sd = 0.0534 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349 allele 2 : freq = 0.5767 sd = 0.0534 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.3667 freq = 0.0000 freq = 0.3875 allele 2 : freq = 0.5500 freq = 0.6333 freq = 0.0000 freq = 0.6125 ***************************************** **************************************** Analysis of Marker 75: rs75 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.282911 pvalue = 0.130806 df = 1 ***************************************** RCHI test RCHI statistic value = 2.679990 pvalue = 0.101616 df = 1 ***************************************** RW test RW statistic value = 0.024662 pvalue = 0.875212 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1567 sd = 0.0393 freq = 0.2019 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 allele 2 : freq = 0.8433 sd = 0.0393 freq = 0.7981 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1437 freq = 0.2083 freq = 0.0000 freq = 0.1922 allele 2 : freq = 0.8562 freq = 0.7917 freq = 0.0000 freq = 0.8078 ***************************************** **************************************** Analysis of Marker 76: rs76 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.141769 pvalue = 0.285279 df = 1 ***************************************** RCHI test RCHI statistic value = 0.489942 pvalue = 0.483953 df = 1 ***************************************** RW test RW statistic value = 0.799751 pvalue = 0.371168 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2233 sd = 0.0450 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 allele 2 : freq = 0.7767 sd = 0.0450 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 freq = 0.2562 freq = 0.0000 freq = 0.2484 allele 2 : freq = 0.7750 freq = 0.7438 freq = 0.0000 freq = 0.7516 ***************************************** **************************************** Analysis of Marker 77: rs77 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.157869 pvalue = 0.691126 df = 1 ***************************************** RCHI test RCHI statistic value = 0.207810 pvalue = 0.648489 df = 1 ***************************************** RW test RW statistic value = 0.000188 pvalue = 0.989075 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4950 sd = 0.0540 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 allele 2 : freq = 0.5050 sd = 0.0540 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.5021 freq = 0.0000 freq = 0.5078 allele 2 : freq = 0.4750 freq = 0.4979 freq = 0.0000 freq = 0.4922 ***************************************** **************************************** Analysis of Marker 78: rs78 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.572503 pvalue = 0.449266 df = 1 ***************************************** RCHI test RCHI statistic value = 0.838880 pvalue = 0.359717 df = 1 ***************************************** RW test RW statistic value = 1.203518 pvalue = 0.27262 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1717 sd = 0.0407 freq = 0.1558 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 allele 2 : freq = 0.8283 sd = 0.0407 freq = 0.8442 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.1417 freq = 0.0000 freq = 0.1500 allele 2 : freq = 0.8250 freq = 0.8583 freq = 0.0000 freq = 0.8500 ***************************************** **************************************** Analysis of Marker 79: rs79 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.457927 pvalue = 0.22726 df = 1 ***************************************** RCHI test RCHI statistic value = 0.969370 pvalue = 0.324837 df = 1 ***************************************** RW test RW statistic value = 0.207435 pvalue = 0.648785 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7183 sd = 0.0486 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 allele 2 : freq = 0.2817 sd = 0.0486 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7250 freq = 0.7667 freq = 0.0000 freq = 0.7562 allele 2 : freq = 0.2750 freq = 0.2333 freq = 0.0000 freq = 0.2437 ***************************************** **************************************** Analysis of Marker 80: rs80 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.794771 pvalue = 0.0945723 df = 1 ***************************************** RCHI test RCHI statistic value = 3.891946 pvalue = 0.0485182 df = 1 ***************************************** RW test RW statistic value = 2.863041 pvalue = 0.090636 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4617 sd = 0.0538 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349 allele 2 : freq = 0.5383 sd = 0.0538 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4813 freq = 0.3833 freq = 0.0000 freq = 0.4078 allele 2 : freq = 0.5188 freq = 0.6167 freq = 0.0000 freq = 0.5922 ***************************************** **************************************** Analysis of Marker 81: rs81 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.094901 pvalue = 0.758037 df = 1 ***************************************** RCHI test RCHI statistic value = 0.744392 pvalue = 0.388257 df = 1 ***************************************** RW test RW statistic value = 0.586997 pvalue = 0.443583 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8317 sd = 0.0404 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 allele 2 : freq = 0.1683 sd = 0.0404 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8187 freq = 0.8521 freq = 0.0000 freq = 0.8438 allele 2 : freq = 0.1812 freq = 0.1479 freq = 0.0000 freq = 0.1562 ***************************************** **************************************** Analysis of Marker 82: rs82 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.676462 pvalue = 0.410808 df = 1 ***************************************** RCHI test RCHI statistic value = 2.200047 pvalue = 0.138007 df = 1 ***************************************** RW test RW statistic value = 0.451768 pvalue = 0.501497 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.4058 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.5942 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.4479 freq = 0.0000 freq = 0.4297 allele 2 : freq = 0.6250 freq = 0.5521 freq = 0.0000 freq = 0.5703 ***************************************** **************************************** Analysis of Marker 83: rs83 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.943211 pvalue = 0.0470609 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 4.432342 pvalue = 0.0352641 df = 1 ***************************************** RW test RW statistic value = 1.735219 pvalue = 0.187746 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327 allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.6646 freq = 0.0000 freq = 0.6891 allele 2 : freq = 0.2375 freq = 0.3354 freq = 0.0000 freq = 0.3109 ***************************************** **************************************** Analysis of Marker 84: rs84 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.136428 pvalue = 0.711858 df = 1 ***************************************** RCHI test RCHI statistic value = 0.086624 pvalue = 0.768513 df = 1 ***************************************** RW test RW statistic value = 0.000193 pvalue = 0.988915 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4267 sd = 0.0534 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 allele 2 : freq = 0.5733 sd = 0.0534 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4313 freq = 0.4167 freq = 0.0000 freq = 0.4203 allele 2 : freq = 0.5687 freq = 0.5833 freq = 0.0000 freq = 0.5797 ***************************************** **************************************** Analysis of Marker 85: rs85 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.058432 pvalue = 0.808992 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001720 pvalue = 0.966924 df = 1 ***************************************** RW test RW statistic value = 0.001690 pvalue = 0.967212 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4717 sd = 0.0539 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.5283 sd = 0.0539 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4938 freq = 0.4917 freq = 0.0000 freq = 0.4922 allele 2 : freq = 0.5062 freq = 0.5083 freq = 0.0000 freq = 0.5078 ***************************************** **************************************** Analysis of Marker 86: rs86 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.576324 pvalue = 0.447757 df = 1 ***************************************** RCHI test RCHI statistic value = 0.016029 pvalue = 0.899251 df = 1 ***************************************** RW test RW statistic value = 0.032862 pvalue = 0.856148 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3683 sd = 0.0521 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 allele 2 : freq = 0.6317 sd = 0.0521 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.3688 freq = 0.0000 freq = 0.3672 allele 2 : freq = 0.6375 freq = 0.6312 freq = 0.0000 freq = 0.6328 ***************************************** **************************************** Analysis of Marker 87: rs87 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.087900 pvalue = 0.766865 df = 1 ***************************************** RCHI test RCHI statistic value = 0.076043 pvalue = 0.782733 df = 1 ***************************************** RW test RW statistic value = 0.260360 pvalue = 0.609873 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1783 sd = 0.0413 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.8217 sd = 0.0413 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1979 freq = 0.0000 freq = 0.1953 allele 2 : freq = 0.8125 freq = 0.8021 freq = 0.0000 freq = 0.8047 ***************************************** **************************************** Analysis of Marker 88: rs88 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.414265 pvalue = 0.519813 df = 1 ***************************************** RCHI test RCHI statistic value = 1.472200 pvalue = 0.224999 df = 1 ***************************************** RW test RW statistic value = 1.721564 pvalue = 0.189492 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1667 sd = 0.0403 freq = 0.1654 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.8333 sd = 0.0403 freq = 0.8346 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1812 freq = 0.1354 freq = 0.0000 freq = 0.1469 allele 2 : freq = 0.8187 freq = 0.8646 freq = 0.0000 freq = 0.8531 ***************************************** **************************************** Analysis of Marker 89: rs89 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.814777 pvalue = 0.177936 df = 1 ***************************************** RCHI test RCHI statistic value = 0.718050 pvalue = 0.396784 df = 1 ***************************************** RW test RW statistic value = 0.182633 pvalue = 0.66912 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3667 sd = 0.0521 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.6333 sd = 0.0521 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.3354 freq = 0.0000 freq = 0.3453 allele 2 : freq = 0.6250 freq = 0.6646 freq = 0.0000 freq = 0.6547 ***************************************** **************************************** Analysis of Marker 90: rs90 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.018149 pvalue = 0.312959 df = 1 ***************************************** RCHI test RCHI statistic value = 0.757089 pvalue = 0.384241 df = 1 ***************************************** RW test RW statistic value = 1.691579 pvalue = 0.193393 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4650 sd = 0.0539 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.5350 sd = 0.0539 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.5000 freq = 0.0000 freq = 0.4891 allele 2 : freq = 0.5437 freq = 0.5000 freq = 0.0000 freq = 0.5109 ***************************************** **************************************** Analysis of Marker 91: rs91 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.758121 pvalue = 0.184859 df = 1 ***************************************** RCHI test RCHI statistic value = 0.447044 pvalue = 0.503742 df = 1 ***************************************** RW test RW statistic value = 4.521566 pvalue = 0.0334702 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6367 sd = 0.0519 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 allele 2 : freq = 0.3633 sd = 0.0519 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6312 freq = 0.5979 freq = 0.0000 freq = 0.6062 allele 2 : freq = 0.3688 freq = 0.4021 freq = 0.0000 freq = 0.3937 ***************************************** **************************************** Analysis of Marker 92: rs92 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.329243 pvalue = 0.0680582 df = 1 ***************************************** RCHI test RCHI statistic value = 1.289785 pvalue = 0.256088 df = 1 ***************************************** RW test RW statistic value = 0.072999 pvalue = 0.787019 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6283 sd = 0.0522 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 allele 2 : freq = 0.3717 sd = 0.0522 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6250 freq = 0.6771 freq = 0.0000 freq = 0.6641 allele 2 : freq = 0.3750 freq = 0.3229 freq = 0.0000 freq = 0.3359 ***************************************** **************************************** Analysis of Marker 93: rs93 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.187890 pvalue = 0.275756 df = 1 ***************************************** RCHI test RCHI statistic value = 0.122554 pvalue = 0.726281 df = 1 ***************************************** RW test RW statistic value = 1.049666 pvalue = 0.305584 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7383 sd = 0.0475 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 allele 2 : freq = 0.2617 sd = 0.0475 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7312 freq = 0.7458 freq = 0.0000 freq = 0.7422 allele 2 : freq = 0.2687 freq = 0.2542 freq = 0.0000 freq = 0.2578 ***************************************** **************************************** Analysis of Marker 94: rs94 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.453619 pvalue = 0.500621 df = 1 ***************************************** RCHI test RCHI statistic value = 0.664681 pvalue = 0.414912 df = 1 ***************************************** RW test RW statistic value = 0.028947 pvalue = 0.864901 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3817 sd = 0.0525 freq = 0.3538 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 allele 2 : freq = 0.6183 sd = 0.0525 freq = 0.6462 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3937 freq = 0.3542 freq = 0.0000 freq = 0.3641 allele 2 : freq = 0.6062 freq = 0.6458 freq = 0.0000 freq = 0.6359 ***************************************** **************************************** Analysis of Marker 95: rs95 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.005784 pvalue = 0.0453444 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 2.326612 pvalue = 0.127178 df = 1 ***************************************** RW test RW statistic value = 3.086345 pvalue = 0.078952 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5783 sd = 0.0533 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 allele 2 : freq = 0.4217 sd = 0.0533 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5687 freq = 0.6417 freq = 0.0000 freq = 0.6234 allele 2 : freq = 0.4313 freq = 0.3583 freq = 0.0000 freq = 0.3766 ***************************************** **************************************** Analysis of Marker 96: rs96 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.507040 pvalue = 0.476423 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001717 pvalue = 0.96695 df = 1 ***************************************** RW test RW statistic value = 2.267935 pvalue = 0.132076 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4533 sd = 0.0538 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.5467 sd = 0.0538 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.4542 freq = 0.0000 freq = 0.4547 allele 2 : freq = 0.5437 freq = 0.5458 freq = 0.0000 freq = 0.5453 ***************************************** **************************************** Analysis of Marker 97: rs97 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.861726 pvalue = 0.0907101 df = 1 ***************************************** RCHI test RCHI statistic value = 0.585061 pvalue = 0.444335 df = 1 ***************************************** RW test RW statistic value = 0.003402 pvalue = 0.953491 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1967 sd = 0.0429 freq = 0.1423 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.8033 sd = 0.0429 freq = 0.8577 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2062 freq = 0.1792 freq = 0.0000 freq = 0.1859 allele 2 : freq = 0.7937 freq = 0.8208 freq = 0.0000 freq = 0.8141 ***************************************** **************************************** Analysis of Marker 98: rs98 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000662 pvalue = 0.979478 df = 1 ***************************************** RCHI test RCHI statistic value = 0.026170 pvalue = 0.871486 df = 1 ***************************************** RW test RW statistic value = 0.153654 pvalue = 0.695068 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8133 sd = 0.0421 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 allele 2 : freq = 0.1867 sd = 0.0421 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8187 freq = 0.8125 freq = 0.0000 freq = 0.8141 allele 2 : freq = 0.1812 freq = 0.1875 freq = 0.0000 freq = 0.1859 ***************************************** **************************************** Analysis of Marker 99: rs99 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.025920 pvalue = 0.872096 df = 1 ***************************************** RCHI test RCHI statistic value = 0.088820 pvalue = 0.765683 df = 1 ***************************************** RW test RW statistic value = 0.997622 pvalue = 0.317887 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6017 sd = 0.0529 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 allele 2 : freq = 0.3983 sd = 0.0529 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6188 freq = 0.6042 freq = 0.0000 freq = 0.6078 allele 2 : freq = 0.3812 freq = 0.3958 freq = 0.0000 freq = 0.3922 ***************************************** **************************************** Analysis of Marker 100: rs100 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.421162 pvalue = 0.516358 df = 1 ***************************************** RCHI test RCHI statistic value = 0.946905 pvalue = 0.330508 df = 1 ***************************************** RW test RW statistic value = 1.730147 pvalue = 0.188392 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6900 sd = 0.0500 freq = 0.6673 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 allele 2 : freq = 0.3100 sd = 0.0500 freq = 0.3327 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.6479 freq = 0.0000 freq = 0.6594 allele 2 : freq = 0.3063 freq = 0.3521 freq = 0.0000 freq = 0.3406 ***************************************** **************************************** Analysis of Marker 101: rs101 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.068210 pvalue = 0.793961 df = 1 ***************************************** RCHI test RCHI statistic value = 0.084663 pvalue = 0.771075 df = 1 ***************************************** RW test RW statistic value = 0.399162 pvalue = 0.527522 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4450 sd = 0.0537 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 allele 2 : freq = 0.5550 sd = 0.0537 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.4646 freq = 0.0000 freq = 0.4609 allele 2 : freq = 0.5500 freq = 0.5354 freq = 0.0000 freq = 0.5391 ***************************************** **************************************** Analysis of Marker 102: rs102 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.905888 pvalue = 0.341208 df = 1 ***************************************** RCHI test RCHI statistic value = 1.115500 pvalue = 0.290889 df = 1 ***************************************** RW test RW statistic value = 0.175376 pvalue = 0.675378 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7767 sd = 0.0450 freq = 0.8192 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.2233 sd = 0.0450 freq = 0.1808 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.8229 freq = 0.0000 freq = 0.8125 allele 2 : freq = 0.2188 freq = 0.1771 freq = 0.0000 freq = 0.1875 ***************************************** **************************************** Analysis of Marker 103: rs103 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.184305 pvalue = 0.6677 df = 1 ***************************************** RCHI test RCHI statistic value = 0.015696 pvalue = 0.900299 df = 1 ***************************************** RW test RW statistic value = 0.685468 pvalue = 0.40771 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1483 sd = 0.0384 freq = 0.1250 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 allele 2 : freq = 0.8517 sd = 0.0384 freq = 0.8750 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1437 freq = 0.1479 freq = 0.0000 freq = 0.1469 allele 2 : freq = 0.8562 freq = 0.8521 freq = 0.0000 freq = 0.8531 ***************************************** **************************************** Analysis of Marker 104: rs104 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000041 pvalue = 0.99488 df = 1 ***************************************** RCHI test RCHI statistic value = 0.682405 pvalue = 0.40876 df = 1 ***************************************** RW test RW statistic value = 0.132451 pvalue = 0.715904 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2950 sd = 0.0493 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 allele 2 : freq = 0.7050 sd = 0.0493 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3000 freq = 0.3375 freq = 0.0000 freq = 0.3281 allele 2 : freq = 0.7000 freq = 0.6625 freq = 0.0000 freq = 0.6719 ***************************************** **************************************** Analysis of Marker 105: rs105 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000058 pvalue = 0.993931 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001899 pvalue = 0.965239 df = 1 ***************************************** RW test RW statistic value = 0.013271 pvalue = 0.908287 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6733 sd = 0.0507 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 allele 2 : freq = 0.3267 sd = 0.0507 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6562 freq = 0.6583 freq = 0.0000 freq = 0.6578 allele 2 : freq = 0.3438 freq = 0.3417 freq = 0.0000 freq = 0.3422 ***************************************** **************************************** Analysis of Marker 106: rs106 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.708519 pvalue = 0.399936 df = 1 ***************************************** RCHI test RCHI statistic value = 0.098318 pvalue = 0.753857 df = 1 ***************************************** RW test RW statistic value = 0.000219 pvalue = 0.988191 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7300 sd = 0.0480 freq = 0.6981 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327 allele 2 : freq = 0.2700 sd = 0.0480 freq = 0.3019 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7312 freq = 0.7167 freq = 0.0000 freq = 0.7203 allele 2 : freq = 0.2687 freq = 0.2833 freq = 0.0000 freq = 0.2797 ***************************************** **************************************** Analysis of Marker 107: rs107 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.314197 pvalue = 0.575116 df = 1 ***************************************** RCHI test RCHI statistic value = 0.722750 pvalue = 0.395243 df = 1 ***************************************** RW test RW statistic value = 0.234047 pvalue = 0.628539 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7267 sd = 0.0481 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310 allele 2 : freq = 0.2733 sd = 0.0481 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7250 freq = 0.7625 freq = 0.0000 freq = 0.7531 allele 2 : freq = 0.2750 freq = 0.2375 freq = 0.0000 freq = 0.2469 ***************************************** **************************************** Analysis of Marker 108: rs108 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.511812 pvalue = 0.112996 df = 1 ***************************************** RCHI test RCHI statistic value = 1.027605 pvalue = 0.310722 df = 1 ***************************************** RW test RW statistic value = 0.037605 pvalue = 0.846239 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2367 sd = 0.0459 freq = 0.1962 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275 allele 2 : freq = 0.7633 sd = 0.0459 freq = 0.8038 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.2042 freq = 0.0000 freq = 0.2141 allele 2 : freq = 0.7562 freq = 0.7958 freq = 0.0000 freq = 0.7859 ***************************************** **************************************** Analysis of Marker 109: rs109 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.621670 pvalue = 0.202859 df = 1 ***************************************** RCHI test RCHI statistic value = 1.354605 pvalue = 0.244475 df = 1 ***************************************** RW test RW statistic value = 0.656656 pvalue = 0.417743 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5983 sd = 0.0530 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 allele 2 : freq = 0.4017 sd = 0.0530 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5938 freq = 0.5354 freq = 0.0000 freq = 0.5500 allele 2 : freq = 0.4062 freq = 0.4646 freq = 0.0000 freq = 0.4500 ***************************************** **************************************** Analysis of Marker 110: rs110 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.554095 pvalue = 0.456649 df = 1 ***************************************** RCHI test RCHI statistic value = 0.412021 pvalue = 0.520945 df = 1 ***************************************** RW test RW statistic value = 0.019993 pvalue = 0.887557 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5850 sd = 0.0532 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.4150 sd = 0.0532 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5938 freq = 0.6250 freq = 0.0000 freq = 0.6172 allele 2 : freq = 0.4062 freq = 0.3750 freq = 0.0000 freq = 0.3828 ***************************************** **************************************** Analysis of Marker 111: rs111 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.028862 pvalue = 0.865098 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.009248 pvalue = 0.923387 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 sd = 0.0451 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 allele 2 : freq = 0.2250 sd = 0.0451 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7688 freq = 0.7688 freq = 0.0000 freq = 0.7688 allele 2 : freq = 0.2313 freq = 0.2313 freq = 0.0000 freq = 0.2313 ***************************************** **************************************** Analysis of Marker 112: rs112 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.441557 pvalue = 0.229888 df = 1 ***************************************** RCHI test RCHI statistic value = 2.460253 pvalue = 0.11676 df = 1 ***************************************** RW test RW statistic value = 0.544859 pvalue = 0.460426 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.7346 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.2654 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7125 freq = 0.0000 freq = 0.7297 allele 2 : freq = 0.2188 freq = 0.2875 freq = 0.0000 freq = 0.2703 ***************************************** **************************************** Analysis of Marker 113: rs113 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.041271 pvalue = 0.839015 df = 1 ***************************************** RCHI test RCHI statistic value = 0.117968 pvalue = 0.731249 df = 1 ***************************************** RW test RW statistic value = 1.004959 pvalue = 0.316113 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8067 sd = 0.0427 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 allele 2 : freq = 0.1933 sd = 0.0427 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8313 freq = 0.8187 freq = 0.0000 freq = 0.8219 allele 2 : freq = 0.1688 freq = 0.1812 freq = 0.0000 freq = 0.1781 ***************************************** **************************************** Analysis of Marker 114: rs114 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.217585 pvalue = 0.136446 df = 1 ***************************************** RCHI test RCHI statistic value = 2.842310 pvalue = 0.0918122 df = 1 ***************************************** RW test RW statistic value = 2.383502 pvalue = 0.122622 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7000 sd = 0.0495 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.3000 sd = 0.0495 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7063 freq = 0.7792 freq = 0.0000 freq = 0.7609 allele 2 : freq = 0.2938 freq = 0.2208 freq = 0.0000 freq = 0.2391 ***************************************** **************************************** Analysis of Marker 115: rs115 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.037117 pvalue = 0.847228 df = 1 ***************************************** RCHI test RCHI statistic value = 0.043269 pvalue = 0.835219 df = 1 ***************************************** RW test RW statistic value = 0.054610 pvalue = 0.815227 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4300 sd = 0.0535 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 allele 2 : freq = 0.5700 sd = 0.0535 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4625 freq = 0.4521 freq = 0.0000 freq = 0.4547 allele 2 : freq = 0.5375 freq = 0.5479 freq = 0.0000 freq = 0.5453 ***************************************** **************************************** Analysis of Marker 116: rs116 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.026988 pvalue = 0.869511 df = 1 ***************************************** RCHI test RCHI statistic value = 0.027376 pvalue = 0.868585 df = 1 ***************************************** RW test RW statistic value = 0.479541 pvalue = 0.488631 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8183 sd = 0.0416 freq = 0.8231 sd = 0.0290 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.1817 sd = 0.0416 freq = 0.1769 sd = 0.0290 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.8313 freq = 0.0000 freq = 0.8297 allele 2 : freq = 0.1750 freq = 0.1688 freq = 0.0000 freq = 0.1703 ***************************************** **************************************** Analysis of Marker 117: rs117 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.032303 pvalue = 0.857365 df = 1 ***************************************** RCHI test RCHI statistic value = 0.664681 pvalue = 0.414912 df = 1 ***************************************** RW test RW statistic value = 0.218913 pvalue = 0.63987 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3883 sd = 0.0526 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 allele 2 : freq = 0.6117 sd = 0.0526 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.4146 freq = 0.0000 freq = 0.4047 allele 2 : freq = 0.6250 freq = 0.5854 freq = 0.0000 freq = 0.5953 ***************************************** **************************************** Analysis of Marker 118: rs118 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.136636 pvalue = 0.711649 df = 1 ***************************************** RCHI test RCHI statistic value = 0.112161 pvalue = 0.737697 df = 1 ***************************************** RW test RW statistic value = 0.006248 pvalue = 0.936999 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7017 sd = 0.0494 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 allele 2 : freq = 0.2983 sd = 0.0494 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7250 freq = 0.7104 freq = 0.0000 freq = 0.7141 allele 2 : freq = 0.2750 freq = 0.2896 freq = 0.0000 freq = 0.2859 ***************************************** **************************************** Analysis of Marker 119: rs119 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.040785 pvalue = 0.839953 df = 1 ***************************************** RCHI test RCHI statistic value = 0.280414 pvalue = 0.59643 df = 1 ***************************************** RW test RW statistic value = 1.500141 pvalue = 0.22065 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8600 sd = 0.0375 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 allele 2 : freq = 0.1400 sd = 0.0375 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8562 freq = 0.8375 freq = 0.0000 freq = 0.8422 allele 2 : freq = 0.1437 freq = 0.1625 freq = 0.0000 freq = 0.1578 ***************************************** **************************************** Analysis of Marker 120: rs120 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.071256 pvalue = 0.789516 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.007062 pvalue = 0.933028 df = 1 The p-value might not be exact because of the small number of allele 2 in cases ***************************************** RW test RW statistic value = 1.172707 pvalue = 0.278846 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9400 sd = 0.0257 freq = 0.9346 sd = 0.0188 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174 allele 2 : freq = 0.0600 sd = 0.0257 freq = 0.0654 sd = 0.0188 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9437 freq = 0.9458 freq = 0.0000 freq = 0.9453 allele 2 : freq = 0.0563 freq = 0.0542 freq = 0.0000 freq = 0.0547 ***************************************** **************************************** Analysis of Marker 121: rs121 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.175809 pvalue = 0.675 df = 1 ***************************************** RCHI test RCHI statistic value = 0.231425 pvalue = 0.630469 df = 1 ***************************************** RW test RW statistic value = 0.654845 pvalue = 0.418386 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.3500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335 allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.6500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.3479 freq = 0.0000 freq = 0.3422 allele 2 : freq = 0.6750 freq = 0.6521 freq = 0.0000 freq = 0.6578 ***************************************** **************************************** Analysis of Marker 122: rs122 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.090434 pvalue = 0.763627 df = 1 ***************************************** RCHI test RCHI statistic value = 0.444872 pvalue = 0.50478 df = 1 ***************************************** RW test RW statistic value = 0.616427 pvalue = 0.432378 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4583 sd = 0.0538 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.5417 sd = 0.0538 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.4167 freq = 0.0000 freq = 0.4250 allele 2 : freq = 0.5500 freq = 0.5833 freq = 0.0000 freq = 0.5750 ***************************************** **************************************** Analysis of Marker 123: rs123 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.099279 pvalue = 0.752696 df = 1 ***************************************** RCHI test RCHI statistic value = 0.145472 pvalue = 0.7029 df = 1 ***************************************** RW test RW statistic value = 0.283139 pvalue = 0.594651 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3883 sd = 0.0526 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6117 sd = 0.0526 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4062 freq = 0.3875 freq = 0.0000 freq = 0.3922 allele 2 : freq = 0.5938 freq = 0.6125 freq = 0.0000 freq = 0.6078 ***************************************** **************************************** Analysis of Marker 124: rs124 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.603482 pvalue = 0.437252 df = 1 ***************************************** RCHI test RCHI statistic value = 0.363801 pvalue = 0.546403 df = 1 ***************************************** RW test RW statistic value = 0.287906 pvalue = 0.591566 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2567 sd = 0.0472 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316 allele 2 : freq = 0.7433 sd = 0.0472 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.2708 freq = 0.0000 freq = 0.2641 allele 2 : freq = 0.7562 freq = 0.7292 freq = 0.0000 freq = 0.7359 ***************************************** **************************************** Analysis of Marker 125: rs125 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.013759 pvalue = 0.906624 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001721 pvalue = 0.966909 df = 1 ***************************************** RW test RW statistic value = 1.695819 pvalue = 0.192836 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4717 sd = 0.0539 freq = 0.4692 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 allele 2 : freq = 0.5283 sd = 0.0539 freq = 0.5308 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4688 freq = 0.4708 freq = 0.0000 freq = 0.4703 allele 2 : freq = 0.5312 freq = 0.5292 freq = 0.0000 freq = 0.5297 ***************************************** **************************************** Analysis of Marker 126: rs126 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.083435 pvalue = 0.0433055 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 3.380773 pvalue = 0.0659611 df = 1 ***************************************** RW test RW statistic value = 4.232724 pvalue = 0.0396517 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6350 sd = 0.0520 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 allele 2 : freq = 0.3650 sd = 0.0520 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 freq = 0.5583 freq = 0.0000 freq = 0.5813 allele 2 : freq = 0.3500 freq = 0.4417 freq = 0.0000 freq = 0.4188 ***************************************** **************************************** Analysis of Marker 127: rs127 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.130602 pvalue = 0.287647 df = 1 ***************************************** RCHI test RCHI statistic value = 0.493199 pvalue = 0.482504 df = 1 ***************************************** RW test RW statistic value = 0.202135 pvalue = 0.653003 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3033 sd = 0.0497 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 allele 2 : freq = 0.6967 sd = 0.0497 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2875 freq = 0.3208 freq = 0.0000 freq = 0.3125 allele 2 : freq = 0.7125 freq = 0.6792 freq = 0.0000 freq = 0.6875 ***************************************** **************************************** Analysis of Marker 128: rs128 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.370585 pvalue = 0.241711 df = 1 ***************************************** RCHI test RCHI statistic value = 0.621988 pvalue = 0.43031 df = 1 ***************************************** RW test RW statistic value = 3.277625 pvalue = 0.0702305 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.4854 freq = 0.0000 freq = 0.4953 allele 2 : freq = 0.4750 freq = 0.5146 freq = 0.0000 freq = 0.5047 ***************************************** **************************************** Analysis of Marker 129: rs129 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.059609 pvalue = 0.807115 df = 1 ***************************************** RCHI test RCHI statistic value = 0.035256 pvalue = 0.85106 df = 1 ***************************************** RW test RW statistic value = 0.754446 pvalue = 0.385072 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2700 sd = 0.0480 freq = 0.2712 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 allele 2 : freq = 0.7300 sd = 0.0480 freq = 0.7288 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2812 freq = 0.2896 freq = 0.0000 freq = 0.2875 allele 2 : freq = 0.7188 freq = 0.7104 freq = 0.0000 freq = 0.7125 ***************************************** **************************************** Analysis of Marker 130: rs130 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001656 pvalue = 0.967536 df = 1 ***************************************** RCHI test RCHI statistic value = 0.015607 pvalue = 0.900581 df = 1 ***************************************** RW test RW statistic value = 0.118329 pvalue = 0.730854 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4600 sd = 0.0538 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.5400 sd = 0.0538 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.4437 freq = 0.0000 freq = 0.4453 allele 2 : freq = 0.5500 freq = 0.5563 freq = 0.0000 freq = 0.5547 ***************************************** **************************************** Analysis of Marker 131: rs131 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.181830 pvalue = 0.669806 df = 1 ***************************************** RCHI test RCHI statistic value = 0.329617 pvalue = 0.565885 df = 1 ***************************************** RW test RW statistic value = 1.224560 pvalue = 0.268468 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7533 sd = 0.0466 freq = 0.7654 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 allele 2 : freq = 0.2467 sd = 0.0466 freq = 0.2346 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7375 freq = 0.0000 freq = 0.7438 allele 2 : freq = 0.2375 freq = 0.2625 freq = 0.0000 freq = 0.2562 ***************************************** **************************************** Analysis of Marker 132: rs132 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.064130 pvalue = 0.800084 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001989 pvalue = 0.964427 df = 1 ***************************************** RW test RW statistic value = 0.125085 pvalue = 0.723583 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3050 sd = 0.0497 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.6950 sd = 0.0497 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3000 freq = 0.2979 freq = 0.0000 freq = 0.2984 allele 2 : freq = 0.7000 freq = 0.7021 freq = 0.0000 freq = 0.7016 ***************************************** **************************************** Analysis of Marker 133: rs133 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.282678 pvalue = 0.594951 df = 1 ***************************************** RCHI test RCHI statistic value = 0.084708 pvalue = 0.771015 df = 1 ***************************************** RW test RW statistic value = 0.000257 pvalue = 0.987212 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2550 sd = 0.0471 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 allele 2 : freq = 0.7450 sd = 0.0471 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2625 freq = 0.2500 freq = 0.0000 freq = 0.2531 allele 2 : freq = 0.7375 freq = 0.7500 freq = 0.0000 freq = 0.7469 ***************************************** **************************************** Analysis of Marker 134: rs134 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.418456 pvalue = 0.517708 df = 1 ***************************************** RCHI test RCHI statistic value = 0.424472 pvalue = 0.514714 df = 1 ***************************************** RW test RW statistic value = 1.158581 pvalue = 0.28176 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6717 sd = 0.0507 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 allele 2 : freq = 0.3283 sd = 0.0507 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 freq = 0.6438 freq = 0.0000 freq = 0.6516 allele 2 : freq = 0.3250 freq = 0.3563 freq = 0.0000 freq = 0.3484 ***************************************** **************************************** Analysis of Marker 135: rs135 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.326426 pvalue = 0.249442 df = 1 ***************************************** RCHI test RCHI statistic value = 1.093649 pvalue = 0.295664 df = 1 ***************************************** RW test RW statistic value = 1.184775 pvalue = 0.276386 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8400 sd = 0.0396 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280 allele 2 : freq = 0.1600 sd = 0.0396 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8021 freq = 0.0000 freq = 0.8125 allele 2 : freq = 0.1562 freq = 0.1979 freq = 0.0000 freq = 0.1875 ***************************************** **************************************** Analysis of Marker 136: rs136 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.953136 pvalue = 0.328922 df = 1 ***************************************** RCHI test RCHI statistic value = 0.858732 pvalue = 0.354094 df = 1 ***************************************** RW test RW statistic value = 0.843795 pvalue = 0.358314 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5683 sd = 0.0535 freq = 0.5923 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.4317 sd = 0.0535 freq = 0.4077 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5500 freq = 0.5958 freq = 0.0000 freq = 0.5844 allele 2 : freq = 0.4500 freq = 0.4042 freq = 0.0000 freq = 0.4156 ***************************************** **************************************** Analysis of Marker 137: rs137 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.942677 pvalue = 0.33159 df = 1 ***************************************** RCHI test RCHI statistic value = 0.198906 pvalue = 0.655606 df = 1 ***************************************** RW test RW statistic value = 0.055593 pvalue = 0.813601 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7383 sd = 0.0475 freq = 0.6788 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.2617 sd = 0.0475 freq = 0.3212 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7312 freq = 0.7104 freq = 0.0000 freq = 0.7156 allele 2 : freq = 0.2687 freq = 0.2896 freq = 0.0000 freq = 0.2844 ***************************************** **************************************** Analysis of Marker 138: rs138 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.718893 pvalue = 0.396507 df = 1 ***************************************** RCHI test RCHI statistic value = 1.391004 pvalue = 0.238236 df = 1 ***************************************** RW test RW statistic value = 0.325624 pvalue = 0.568247 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4200 sd = 0.0533 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 allele 2 : freq = 0.5800 sd = 0.0533 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.3792 freq = 0.0000 freq = 0.3937 allele 2 : freq = 0.5625 freq = 0.6208 freq = 0.0000 freq = 0.6062 ***************************************** **************************************** Analysis of Marker 139: rs139 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.696473 pvalue = 0.403971 df = 1 ***************************************** RCHI test RCHI statistic value = 0.585142 pvalue = 0.444304 df = 1 ***************************************** RW test RW statistic value = 0.620944 pvalue = 0.430697 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3333 sd = 0.0509 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 allele 2 : freq = 0.6667 sd = 0.0509 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3021 freq = 0.0000 freq = 0.3109 allele 2 : freq = 0.6625 freq = 0.6979 freq = 0.0000 freq = 0.6891 ***************************************** **************************************** Analysis of Marker 140: rs140 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.365716 pvalue = 0.242549 df = 1 ***************************************** RCHI test RCHI statistic value = 0.352008 pvalue = 0.552979 df = 1 ***************************************** RW test RW statistic value = 0.056667 pvalue = 0.811844 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3617 sd = 0.0519 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6383 sd = 0.0519 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3667 freq = 0.0000 freq = 0.3594 allele 2 : freq = 0.6625 freq = 0.6333 freq = 0.0000 freq = 0.6406 ***************************************** **************************************** Analysis of Marker 141: rs141 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.599410 pvalue = 0.106904 df = 1 ***************************************** RCHI test RCHI statistic value = 1.519566 pvalue = 0.217685 df = 1 ***************************************** RW test RW statistic value = 0.932156 pvalue = 0.334303 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.2923 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321 allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.7077 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3563 freq = 0.3000 freq = 0.0000 freq = 0.3141 allele 2 : freq = 0.6438 freq = 0.7000 freq = 0.0000 freq = 0.6859 ***************************************** **************************************** Analysis of Marker 142: rs142 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.058954 pvalue = 0.808157 df = 1 ***************************************** RCHI test RCHI statistic value = 0.119961 pvalue = 0.729077 df = 1 ***************************************** RW test RW statistic value = 1.245049 pvalue = 0.2645 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3617 sd = 0.0519 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 allele 2 : freq = 0.6383 sd = 0.0519 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.3458 freq = 0.0000 freq = 0.3500 allele 2 : freq = 0.6375 freq = 0.6542 freq = 0.0000 freq = 0.6500 ***************************************** **************************************** Analysis of Marker 143: rs143 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.638395 pvalue = 0.424293 df = 1 ***************************************** RCHI test RCHI statistic value = 0.211880 pvalue = 0.645298 df = 1 ***************************************** RW test RW statistic value = 0.001721 pvalue = 0.966913 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5267 sd = 0.0539 freq = 0.5712 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 allele 2 : freq = 0.4733 sd = 0.0539 freq = 0.4288 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5312 freq = 0.5542 freq = 0.0000 freq = 0.5484 allele 2 : freq = 0.4688 freq = 0.4458 freq = 0.0000 freq = 0.4516 ***************************************** **************************************** Analysis of Marker 144: rs144 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.829054 pvalue = 0.0925729 df = 1 ***************************************** RCHI test RCHI statistic value = 2.442272 pvalue = 0.118105 df = 1 ***************************************** RW test RW statistic value = 1.481503 pvalue = 0.223539 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8933 sd = 0.0333 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 allele 2 : freq = 0.1067 sd = 0.0333 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.8292 freq = 0.0000 freq = 0.8438 allele 2 : freq = 0.1125 freq = 0.1708 freq = 0.0000 freq = 0.1562 ***************************************** **************************************** Analysis of Marker 145: rs145 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.990865 pvalue = 0.0457476 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 2.330625 pvalue = 0.126851 df = 1 ***************************************** RW test RW statistic value = 0.811397 pvalue = 0.367708 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7650 sd = 0.0458 freq = 0.8212 sd = 0.0291 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 allele 2 : freq = 0.2350 sd = 0.0458 freq = 0.1788 sd = 0.0291 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.8146 freq = 0.0000 freq = 0.8000 allele 2 : freq = 0.2437 freq = 0.1854 freq = 0.0000 freq = 0.2000 ***************************************** **************************************** Analysis of Marker 146: rs146 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.228477 pvalue = 0.267703 df = 1 ***************************************** RCHI test RCHI statistic value = 1.587376 pvalue = 0.207701 df = 1 ***************************************** RW test RW statistic value = 0.173307 pvalue = 0.677189 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6650 sd = 0.0510 freq = 0.7212 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 allele 2 : freq = 0.3350 sd = 0.0510 freq = 0.2788 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6562 freq = 0.7146 freq = 0.0000 freq = 0.7000 allele 2 : freq = 0.3438 freq = 0.2854 freq = 0.0000 freq = 0.3000 ***************************************** **************************************** Analysis of Marker 147: rs147 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.116206 pvalue = 0.733186 df = 1 ***************************************** RCHI test RCHI statistic value = 0.843049 pvalue = 0.358526 df = 1 ***************************************** RW test RW statistic value = 0.023011 pvalue = 0.879429 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5600 sd = 0.0536 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 allele 2 : freq = 0.4400 sd = 0.0536 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5625 freq = 0.5167 freq = 0.0000 freq = 0.5281 allele 2 : freq = 0.4375 freq = 0.4833 freq = 0.0000 freq = 0.4719 ***************************************** **************************************** Analysis of Marker 148: rs148 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.665824 pvalue = 0.414511 df = 1 ***************************************** RCHI test RCHI statistic value = 0.258663 pvalue = 0.61104 df = 1 ***************************************** RW test RW statistic value = 1.909191 pvalue = 0.167053 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1577 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8423 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1313 freq = 0.1500 freq = 0.0000 freq = 0.1453 allele 2 : freq = 0.8688 freq = 0.8500 freq = 0.0000 freq = 0.8547 ***************************************** **************************************** Analysis of Marker 149: rs149 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.721183 pvalue = 0.395756 df = 1 ***************************************** RCHI test RCHI statistic value = 0.895142 pvalue = 0.344088 df = 1 ***************************************** RW test RW statistic value = 0.921955 pvalue = 0.336962 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8817 sd = 0.0349 freq = 0.8962 sd = 0.0232 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217 allele 2 : freq = 0.1183 sd = 0.0349 freq = 0.1038 sd = 0.0232 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8750 freq = 0.9042 freq = 0.0000 freq = 0.8969 allele 2 : freq = 0.1250 freq = 0.0958 freq = 0.0000 freq = 0.1031 ***************************************** **************************************** Analysis of Marker 150: rs150 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.351305 pvalue = 0.553375 df = 1 ***************************************** RCHI test RCHI statistic value = 0.861744 pvalue = 0.353251 df = 1 ***************************************** RW test RW statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8423 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1577 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8625 freq = 0.8292 freq = 0.0000 freq = 0.8375 allele 2 : freq = 0.1375 freq = 0.1708 freq = 0.0000 freq = 0.1625 ***************************************** **************************************** Analysis of Marker 151: rs151 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.410052 pvalue = 0.521943 df = 1 ***************************************** RCHI test RCHI statistic value = 0.248430 pvalue = 0.618183 df = 1 ***************************************** RW test RW statistic value = 0.067996 pvalue = 0.794277 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5133 sd = 0.0540 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 allele 2 : freq = 0.4867 sd = 0.0540 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5062 freq = 0.5312 freq = 0.0000 freq = 0.5250 allele 2 : freq = 0.4938 freq = 0.4688 freq = 0.0000 freq = 0.4750 ***************************************** **************************************** Analysis of Marker 152: rs152 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.979428 pvalue = 0.32234 df = 1 ***************************************** RCHI test RCHI statistic value = 2.117000 pvalue = 0.145672 df = 1 ***************************************** RW test RW statistic value = 1.493121 pvalue = 0.221733 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8450 sd = 0.0391 freq = 0.8808 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 allele 2 : freq = 0.1550 sd = 0.0391 freq = 0.1192 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8938 freq = 0.0000 freq = 0.8812 allele 2 : freq = 0.1562 freq = 0.1062 freq = 0.0000 freq = 0.1187 ***************************************** **************************************** Analysis of Marker 153: rs153 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.019745 pvalue = 0.888252 df = 1 ***************************************** RCHI test RCHI statistic value = 0.043352 pvalue = 0.835063 df = 1 ***************************************** RW test RW statistic value = 0.018933 pvalue = 0.89056 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4283 sd = 0.0534 freq = 0.4346 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.5717 sd = 0.0534 freq = 0.5654 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.4271 freq = 0.0000 freq = 0.4297 allele 2 : freq = 0.5625 freq = 0.5729 freq = 0.0000 freq = 0.5703 ***************************************** **************************************** Analysis of Marker 154: rs154 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.123632 pvalue = 0.725128 df = 1 ***************************************** RCHI test RCHI statistic value = 0.062201 pvalue = 0.80305 df = 1 ***************************************** RW test RW statistic value = 0.550074 pvalue = 0.458287 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5633 sd = 0.0536 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 allele 2 : freq = 0.4367 sd = 0.0536 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5563 freq = 0.5437 freq = 0.0000 freq = 0.5469 allele 2 : freq = 0.4437 freq = 0.4562 freq = 0.0000 freq = 0.4531 ***************************************** **************************************** Analysis of Marker 155: rs155 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.625710 pvalue = 0.202298 df = 1 ***************************************** RCHI test RCHI statistic value = 2.620619 pvalue = 0.105483 df = 1 ***************************************** RW test RW statistic value = 6.648553 pvalue = 0.00992364 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4333 sd = 0.0535 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 allele 2 : freq = 0.5667 sd = 0.0535 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 freq = 0.5062 freq = 0.0000 freq = 0.4859 allele 2 : freq = 0.5750 freq = 0.4938 freq = 0.0000 freq = 0.5141 ***************************************** **************************************** Analysis of Marker 156: rs156 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.476640 pvalue = 0.489948 df = 1 ***************************************** RCHI test RCHI statistic value = 0.354427 pvalue = 0.551618 df = 1 ***************************************** RW test RW statistic value = 0.006718 pvalue = 0.934676 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2400 sd = 0.0461 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 allele 2 : freq = 0.7600 sd = 0.0461 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 freq = 0.2250 freq = 0.0000 freq = 0.2313 allele 2 : freq = 0.7500 freq = 0.7750 freq = 0.0000 freq = 0.7688 ***************************************** **************************************** Analysis of Marker 157: rs157 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.238737 pvalue = 0.134591 df = 1 ***************************************** RCHI test RCHI statistic value = 0.254849 pvalue = 0.613681 df = 1 ***************************************** RW test RW statistic value = 0.045070 pvalue = 0.831875 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2200 sd = 0.0447 freq = 0.2750 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 allele 2 : freq = 0.7800 sd = 0.0447 freq = 0.7250 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2125 freq = 0.2354 freq = 0.0000 freq = 0.2297 allele 2 : freq = 0.7875 freq = 0.7646 freq = 0.0000 freq = 0.7703 ***************************************** **************************************** Analysis of Marker 158: rs158 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.118739 pvalue = 0.145506 df = 1 ***************************************** RCHI test RCHI statistic value = 1.559421 pvalue = 0.21175 df = 1 ***************************************** RW test RW statistic value = 0.459515 pvalue = 0.497851 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2562 freq = 0.3146 freq = 0.0000 freq = 0.3000 allele 2 : freq = 0.7438 freq = 0.6854 freq = 0.0000 freq = 0.7000 ***************************************** **************************************** Analysis of Marker 159: rs159 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.185909 pvalue = 0.276156 df = 1 ***************************************** RCHI test RCHI statistic value = 0.514053 pvalue = 0.47339 df = 1 ***************************************** RW test RW statistic value = 0.002989 pvalue = 0.956401 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8365 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1635 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8688 freq = 0.8417 freq = 0.0000 freq = 0.8484 allele 2 : freq = 0.1313 freq = 0.1583 freq = 0.0000 freq = 0.1516 ***************************************** **************************************** Analysis of Marker 160: rs160 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.339008 pvalue = 0.560402 df = 1 ***************************************** RCHI test RCHI statistic value = 0.068353 pvalue = 0.79375 df = 1 ***************************************** RW test RW statistic value = 0.408656 pvalue = 0.522652 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7650 sd = 0.0458 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280 allele 2 : freq = 0.2350 sd = 0.0458 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7917 freq = 0.0000 freq = 0.7891 allele 2 : freq = 0.2188 freq = 0.2083 freq = 0.0000 freq = 0.2109 ***************************************** **************************************** Analysis of Marker 161: rs161 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.005035 pvalue = 0.943431 df = 1 ***************************************** RCHI test RCHI statistic value = 0.015179 pvalue = 0.901946 df = 1 ***************************************** RW test RW statistic value = 0.026516 pvalue = 0.870647 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1217 sd = 0.0353 freq = 0.1346 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.1300 sd = 0.0238 allele 2 : freq = 0.8783 sd = 0.0353 freq = 0.8654 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.8700 sd = 0.0238 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1313 freq = 0.1271 freq = 0.0000 freq = 0.1281 allele 2 : freq = 0.8688 freq = 0.8729 freq = 0.0000 freq = 0.8719 ***************************************** **************************************** Analysis of Marker 162: rs162 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.033875 pvalue = 0.853973 df = 1 ***************************************** RCHI test RCHI statistic value = 0.112069 pvalue = 0.737801 df = 1 ***************************************** RW test RW statistic value = 0.027530 pvalue = 0.868219 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6217 sd = 0.0524 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 allele 2 : freq = 0.3783 sd = 0.0524 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.6042 freq = 0.0000 freq = 0.6000 allele 2 : freq = 0.4125 freq = 0.3958 freq = 0.0000 freq = 0.4000 ***************************************** **************************************** Analysis of Marker 163: rs163 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.612650 pvalue = 0.433792 df = 1 ***************************************** RCHI test RCHI statistic value = 1.017186 pvalue = 0.313188 df = 1 ***************************************** RW test RW statistic value = 0.320948 pvalue = 0.571038 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2550 sd = 0.0471 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 allele 2 : freq = 0.7450 sd = 0.0471 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.1958 freq = 0.0000 freq = 0.2062 allele 2 : freq = 0.7625 freq = 0.8042 freq = 0.0000 freq = 0.7937 ***************************************** **************************************** Analysis of Marker 164: rs164 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.185257 pvalue = 0.666893 df = 1 ***************************************** RCHI test RCHI statistic value = 0.085803 pvalue = 0.769583 df = 1 ***************************************** RW test RW statistic value = 0.009368 pvalue = 0.922895 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4533 sd = 0.0538 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 allele 2 : freq = 0.5467 sd = 0.0538 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.4354 freq = 0.0000 freq = 0.4391 allele 2 : freq = 0.5500 freq = 0.5646 freq = 0.0000 freq = 0.5609 ***************************************** **************************************** Analysis of Marker 165: rs165 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.088562 pvalue = 0.766014 df = 1 ***************************************** RCHI test RCHI statistic value = 1.254058 pvalue = 0.262779 df = 1 ***************************************** RW test RW statistic value = 4.355245 pvalue = 0.0368952 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6850 sd = 0.0502 freq = 0.7212 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327 allele 2 : freq = 0.3150 sd = 0.0502 freq = 0.2788 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.7458 freq = 0.0000 freq = 0.7328 allele 2 : freq = 0.3063 freq = 0.2542 freq = 0.0000 freq = 0.2672 ***************************************** **************************************** Analysis of Marker 166: rs166 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.007888 pvalue = 0.92923 df = 1 ***************************************** RCHI test RCHI statistic value = 0.074318 pvalue = 0.78515 df = 1 ***************************************** RW test RW statistic value = 0.981790 pvalue = 0.321757 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8150 sd = 0.0419 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 allele 2 : freq = 0.1850 sd = 0.0419 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.8146 freq = 0.0000 freq = 0.8172 allele 2 : freq = 0.1750 freq = 0.1854 freq = 0.0000 freq = 0.1828 ***************************************** **************************************** Analysis of Marker 167: rs167 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.073754 pvalue = 0.785947 df = 1 ***************************************** RCHI test RCHI statistic value = 0.033078 pvalue = 0.855682 df = 1 ***************************************** RW test RW statistic value = 0.385619 pvalue = 0.534611 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1346 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8654 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1437 freq = 0.1375 freq = 0.0000 freq = 0.1391 allele 2 : freq = 0.8562 freq = 0.8625 freq = 0.0000 freq = 0.8609 ***************************************** **************************************** Analysis of Marker 168: rs168 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.749491 pvalue = 0.386637 df = 1 ***************************************** RCHI test RCHI statistic value = 0.891151 pvalue = 0.345166 df = 1 ***************************************** RW test RW statistic value = 0.157601 pvalue = 0.691375 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3350 sd = 0.0510 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 allele 2 : freq = 0.6650 sd = 0.0510 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3833 freq = 0.0000 freq = 0.3719 allele 2 : freq = 0.6625 freq = 0.6167 freq = 0.0000 freq = 0.6281 ***************************************** **************************************** Analysis of Marker 169: rs169 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.044061 pvalue = 0.83374 df = 1 ***************************************** RCHI test RCHI statistic value = 0.603547 pvalue = 0.437228 df = 1 ***************************************** RW test RW statistic value = 0.637792 pvalue = 0.424512 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3683 sd = 0.0521 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339 allele 2 : freq = 0.6317 sd = 0.0521 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.4000 freq = 0.0000 freq = 0.3906 allele 2 : freq = 0.6375 freq = 0.6000 freq = 0.0000 freq = 0.6094 ***************************************** **************************************** Analysis of Marker 170: rs170 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.017964 pvalue = 0.893379 df = 1 ***************************************** RCHI test RCHI statistic value = 0.018222 pvalue = 0.892619 df = 1 ***************************************** RW test RW statistic value = 0.849736 pvalue = 0.356627 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6833 sd = 0.0502 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 allele 2 : freq = 0.3167 sd = 0.0502 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7000 freq = 0.6937 freq = 0.0000 freq = 0.6953 allele 2 : freq = 0.3000 freq = 0.3063 freq = 0.0000 freq = 0.3047 ***************************************** **************************************** Analysis of Marker 171: rs171 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.669095 pvalue = 0.19638 df = 1 ***************************************** RCHI test RCHI statistic value = 1.711590 pvalue = 0.190779 df = 1 ***************************************** RW test RW statistic value = 0.001750 pvalue = 0.966631 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5517 sd = 0.0537 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 allele 2 : freq = 0.4483 sd = 0.0537 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5437 freq = 0.6083 freq = 0.0000 freq = 0.5922 allele 2 : freq = 0.4562 freq = 0.3917 freq = 0.0000 freq = 0.4078 ***************************************** **************************************** Analysis of Marker 172: rs172 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.065490 pvalue = 0.79802 df = 1 ***************************************** RCHI test RCHI statistic value = 0.519031 pvalue = 0.471255 df = 1 ***************************************** RW test RW statistic value = 0.550788 pvalue = 0.457996 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4150 sd = 0.0532 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.5850 sd = 0.0532 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3937 freq = 0.4292 freq = 0.0000 freq = 0.4203 allele 2 : freq = 0.6062 freq = 0.5708 freq = 0.0000 freq = 0.5797 ***************************************** **************************************** Analysis of Marker 173: rs173 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.108963 pvalue = 0.741328 df = 1 ***************************************** RCHI test RCHI statistic value = 0.004064 pvalue = 0.949168 df = 1 ***************************************** RW test RW statistic value = 0.074991 pvalue = 0.784204 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8833 sd = 0.0347 freq = 0.8788 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.8800 sd = 0.0230 allele 2 : freq = 0.1167 sd = 0.0347 freq = 0.1212 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.1200 sd = 0.0230 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8938 freq = 0.8958 freq = 0.0000 freq = 0.8953 allele 2 : freq = 0.1062 freq = 0.1042 freq = 0.0000 freq = 0.1047 ***************************************** **************************************** Analysis of Marker 174: rs174 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.616532 pvalue = 0.432339 df = 1 ***************************************** RCHI test RCHI statistic value = 0.855637 pvalue = 0.354962 df = 1 ***************************************** RW test RW statistic value = 2.967731 pvalue = 0.0849409 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5650 sd = 0.0535 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 allele 2 : freq = 0.4350 sd = 0.0535 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5563 freq = 0.6021 freq = 0.0000 freq = 0.5906 allele 2 : freq = 0.4437 freq = 0.3979 freq = 0.0000 freq = 0.4094 ***************************************** **************************************** Analysis of Marker 175: rs175 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000154 pvalue = 0.990108 df = 1 ***************************************** RCHI test RCHI statistic value = 0.096646 pvalue = 0.755892 df = 1 ***************************************** RW test RW statistic value = 0.310952 pvalue = 0.577097 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3067 sd = 0.0498 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 allele 2 : freq = 0.6933 sd = 0.0498 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.3396 freq = 0.0000 freq = 0.3359 allele 2 : freq = 0.6750 freq = 0.6604 freq = 0.0000 freq = 0.6641 ***************************************** **************************************** Analysis of Marker 176: rs176 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.194771 pvalue = 0.13848 df = 1 ***************************************** RCHI test RCHI statistic value = 1.420400 pvalue = 0.233338 df = 1 ***************************************** RW test RW statistic value = 0.007658 pvalue = 0.930266 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9283 sd = 0.0279 freq = 0.8885 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221 allele 2 : freq = 0.0717 sd = 0.0279 freq = 0.1115 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9313 freq = 0.8938 freq = 0.0000 freq = 0.9031 allele 2 : freq = 0.0688 freq = 0.1062 freq = 0.0000 freq = 0.0969 ***************************************** **************************************** Analysis of Marker 177: rs177 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.585220 pvalue = 0.444274 df = 1 ***************************************** RCHI test RCHI statistic value = 0.025099 pvalue = 0.874121 df = 1 ***************************************** RW test RW statistic value = 0.010961 pvalue = 0.916618 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8417 sd = 0.0394 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.1583 sd = 0.0394 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8375 freq = 0.0000 freq = 0.8391 allele 2 : freq = 0.1562 freq = 0.1625 freq = 0.0000 freq = 0.1609 ***************************************** **************************************** Analysis of Marker 178: rs178 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.311653 pvalue = 0.576668 df = 1 ***************************************** RCHI test RCHI statistic value = 0.939518 pvalue = 0.332402 df = 1 ***************************************** RW test RW statistic value = 0.102575 pvalue = 0.748761 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3533 sd = 0.0516 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 allele 2 : freq = 0.6467 sd = 0.0516 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.2979 freq = 0.0000 freq = 0.3094 allele 2 : freq = 0.6562 freq = 0.7021 freq = 0.0000 freq = 0.6906 ***************************************** **************************************** Analysis of Marker 179: rs179 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.972790 pvalue = 0.0462411 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 1.822243 pvalue = 0.177047 df = 1 ***************************************** RW test RW statistic value = 6.165005 pvalue = 0.0130302 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7188 freq = 0.0000 freq = 0.7344 allele 2 : freq = 0.2188 freq = 0.2812 freq = 0.0000 freq = 0.2656 ***************************************** **************************************** Analysis of Marker 180: rs180 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.259590 pvalue = 0.610402 df = 1 ***************************************** RCHI test RCHI statistic value = 0.782566 pvalue = 0.376357 df = 1 ***************************************** RW test RW statistic value = 0.133499 pvalue = 0.714831 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6667 sd = 0.0509 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 allele 2 : freq = 0.3333 sd = 0.0509 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.6458 freq = 0.0000 freq = 0.6562 allele 2 : freq = 0.3125 freq = 0.3542 freq = 0.0000 freq = 0.3438 ***************************************** **************************************** Analysis of Marker 181: rs181 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.558715 pvalue = 0.454778 df = 1 ***************************************** RCHI test RCHI statistic value = 0.700907 pvalue = 0.402479 df = 1 ***************************************** RW test RW statistic value = 0.012244 pvalue = 0.911892 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1483 sd = 0.0384 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 allele 2 : freq = 0.8517 sd = 0.0384 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1437 freq = 0.1750 freq = 0.0000 freq = 0.1672 allele 2 : freq = 0.8562 freq = 0.8250 freq = 0.0000 freq = 0.8328 ***************************************** **************************************** Analysis of Marker 182: rs182 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.175221 pvalue = 0.278331 df = 1 ***************************************** RCHI test RCHI statistic value = 1.210532 pvalue = 0.271227 df = 1 ***************************************** RW test RW statistic value = 1.455170 pvalue = 0.2277 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7400 sd = 0.0474 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 allele 2 : freq = 0.2600 sd = 0.0474 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7438 freq = 0.7896 freq = 0.0000 freq = 0.7781 allele 2 : freq = 0.2562 freq = 0.2104 freq = 0.0000 freq = 0.2219 ***************************************** **************************************** Analysis of Marker 183: rs183 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.398068 pvalue = 0.0652728 df = 1 ***************************************** RCHI test RCHI statistic value = 1.407367 pvalue = 0.235494 df = 1 ***************************************** RW test RW statistic value = 0.248894 pvalue = 0.617855 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8767 sd = 0.0355 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 allele 2 : freq = 0.1233 sd = 0.0355 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.8417 freq = 0.0000 freq = 0.8531 allele 2 : freq = 0.1125 freq = 0.1583 freq = 0.0000 freq = 0.1469 ***************************************** **************************************** Analysis of Marker 184: rs184 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.971922 pvalue = 0.324201 df = 1 ***************************************** RCHI test RCHI statistic value = 2.268391 pvalue = 0.132037 df = 1 ***************************************** RW test RW statistic value = 0.703757 pvalue = 0.401524 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3817 sd = 0.0525 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340 allele 2 : freq = 0.6183 sd = 0.0525 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3937 freq = 0.3208 freq = 0.0000 freq = 0.3391 allele 2 : freq = 0.6062 freq = 0.6792 freq = 0.0000 freq = 0.6609 ***************************************** **************************************** Analysis of Marker 185: rs185 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001744 pvalue = 0.966688 df = 1 ***************************************** RCHI test RCHI statistic value = 0.249702 pvalue = 0.617285 df = 1 ***************************************** RW test RW statistic value = 0.014420 pvalue = 0.904418 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6917 sd = 0.0499 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 allele 2 : freq = 0.3083 sd = 0.0499 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.6708 freq = 0.0000 freq = 0.6766 allele 2 : freq = 0.3063 freq = 0.3292 freq = 0.0000 freq = 0.3234 ***************************************** **************************************** Analysis of Marker 186: rs186 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.404288 pvalue = 0.524883 df = 1 ***************************************** RCHI test RCHI statistic value = 0.017339 pvalue = 0.895239 df = 1 ***************************************** RW test RW statistic value = 0.659621 pvalue = 0.416694 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 sd = 0.0523 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 allele 2 : freq = 0.6250 sd = 0.0523 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3688 freq = 0.3625 freq = 0.0000 freq = 0.3641 allele 2 : freq = 0.6312 freq = 0.6375 freq = 0.0000 freq = 0.6359 ***************************************** **************************************** Analysis of Marker 187: rs187 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.248948 pvalue = 0.133705 df = 1 ***************************************** RCHI test RCHI statistic value = 1.748834 pvalue = 0.186023 df = 1 ***************************************** RW test RW statistic value = 2.338953 pvalue = 0.126174 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7433 sd = 0.0472 freq = 0.8019 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2567 sd = 0.0472 freq = 0.1981 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7375 freq = 0.7917 freq = 0.0000 freq = 0.7781 allele 2 : freq = 0.2625 freq = 0.2083 freq = 0.0000 freq = 0.2219 ***************************************** **************************************** Analysis of Marker 188: rs188 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.275981 pvalue = 0.599348 df = 1 ***************************************** RCHI test RCHI statistic value = 0.584519 pvalue = 0.444546 df = 1 ***************************************** RW test RW statistic value = 4.671240 pvalue = 0.0306718 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3933 sd = 0.0528 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 allele 2 : freq = 0.6067 sd = 0.0528 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4062 freq = 0.3688 freq = 0.0000 freq = 0.3781 allele 2 : freq = 0.5938 freq = 0.6312 freq = 0.0000 freq = 0.6219 ***************************************** **************************************** Analysis of Marker 189: rs189 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.181422 pvalue = 0.670154 df = 1 ***************************************** RCHI test RCHI statistic value = 0.030825 pvalue = 0.860632 df = 1 ***************************************** RW test RW statistic value = 2.733559 pvalue = 0.0982601 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6350 sd = 0.0520 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 allele 2 : freq = 0.3650 sd = 0.0520 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6375 freq = 0.6292 freq = 0.0000 freq = 0.6312 allele 2 : freq = 0.3625 freq = 0.3708 freq = 0.0000 freq = 0.3688 ***************************************** **************************************** Analysis of Marker 190: rs190 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.993245 pvalue = 0.318951 df = 1 ***************************************** RCHI test RCHI statistic value = 1.859713 pvalue = 0.172658 df = 1 ***************************************** RW test RW statistic value = 1.713183 pvalue = 0.190573 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8808 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1192 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9062 freq = 0.8625 freq = 0.0000 freq = 0.8734 allele 2 : freq = 0.0938 freq = 0.1375 freq = 0.0000 freq = 0.1266 ***************************************** **************************************** Analysis of Marker 191: rs191 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.015000 pvalue = 0.902522 df = 1 ***************************************** RCHI test RCHI statistic value = 0.061828 pvalue = 0.80363 df = 1 ***************************************** RW test RW statistic value = 0.036751 pvalue = 0.847972 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4933 sd = 0.0540 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 allele 2 : freq = 0.5067 sd = 0.0540 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5125 freq = 0.5000 freq = 0.0000 freq = 0.5031 allele 2 : freq = 0.4875 freq = 0.5000 freq = 0.0000 freq = 0.4969 ***************************************** **************************************** Analysis of Marker 192: rs192 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.036535 pvalue = 0.848415 df = 1 ***************************************** RCHI test RCHI statistic value = 0.344229 pvalue = 0.557398 df = 1 ***************************************** RW test RW statistic value = 1.385371 pvalue = 0.239188 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5767 sd = 0.0534 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 allele 2 : freq = 0.4233 sd = 0.0534 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.6042 freq = 0.0000 freq = 0.5969 allele 2 : freq = 0.4250 freq = 0.3958 freq = 0.0000 freq = 0.4031 ***************************************** **************************************** Analysis of Marker 193: rs193 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.609525 pvalue = 0.204559 df = 1 ***************************************** RCHI test RCHI statistic value = 1.609078 pvalue = 0.204622 df = 1 ***************************************** RW test RW statistic value = 2.287780 pvalue = 0.130396 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8733 sd = 0.0359 freq = 0.8288 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.1267 sd = 0.0359 freq = 0.1712 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8688 freq = 0.8208 freq = 0.0000 freq = 0.8328 allele 2 : freq = 0.1313 freq = 0.1792 freq = 0.0000 freq = 0.1672 ***************************************** **************************************** Analysis of Marker 194: rs194 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.046658 pvalue = 0.828985 df = 1 ***************************************** RCHI test RCHI statistic value = 0.114450 pvalue = 0.735133 df = 1 ***************************************** RW test RW statistic value = 1.098238 pvalue = 0.294653 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4083 sd = 0.0531 freq = 0.4058 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 allele 2 : freq = 0.5917 sd = 0.0531 freq = 0.5942 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3937 freq = 0.4104 freq = 0.0000 freq = 0.4062 allele 2 : freq = 0.6062 freq = 0.5896 freq = 0.0000 freq = 0.5938 ***************************************** **************************************** Analysis of Marker 195: rs195 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.071708 pvalue = 0.150053 df = 1 ***************************************** RCHI test RCHI statistic value = 1.510400 pvalue = 0.219078 df = 1 ***************************************** RW test RW statistic value = 0.063530 pvalue = 0.801001 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4267 sd = 0.0534 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.5733 sd = 0.0534 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.3958 freq = 0.0000 freq = 0.4109 allele 2 : freq = 0.5437 freq = 0.6042 freq = 0.0000 freq = 0.5891 ***************************************** **************************************** Analysis of Marker 196: rs196 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.182461 pvalue = 0.139591 df = 1 ***************************************** RCHI test RCHI statistic value = 0.792017 pvalue = 0.373491 df = 1 ***************************************** RW test RW statistic value = 0.880202 pvalue = 0.348146 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6633 sd = 0.0510 freq = 0.6038 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.3367 sd = 0.0510 freq = 0.3962 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 freq = 0.6312 freq = 0.0000 freq = 0.6422 allele 2 : freq = 0.3250 freq = 0.3688 freq = 0.0000 freq = 0.3578 ***************************************** **************************************** Analysis of Marker 197: rs197 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.347146 pvalue = 0.125513 df = 1 ***************************************** RCHI test RCHI statistic value = 2.469775 pvalue = 0.116055 df = 1 ***************************************** RW test RW statistic value = 2.789232 pvalue = 0.0948997 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5633 sd = 0.0536 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 allele 2 : freq = 0.4367 sd = 0.0536 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5500 freq = 0.6271 freq = 0.0000 freq = 0.6078 allele 2 : freq = 0.4500 freq = 0.3729 freq = 0.0000 freq = 0.3922 ***************************************** **************************************** Analysis of Marker 198: rs198 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.754866 pvalue = 0.38494 df = 1 ***************************************** RCHI test RCHI statistic value = 0.950061 pvalue = 0.329704 df = 1 ***************************************** RW test RW statistic value = 0.033137 pvalue = 0.855554 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6450 sd = 0.0517 freq = 0.6038 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.3550 sd = 0.0517 freq = 0.3962 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6375 freq = 0.5896 freq = 0.0000 freq = 0.6016 allele 2 : freq = 0.3625 freq = 0.4104 freq = 0.0000 freq = 0.3984 ***************************************** **************************************** Analysis of Marker 199: rs199 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.177327 pvalue = 0.67368 df = 1 ***************************************** RCHI test RCHI statistic value = 0.145472 pvalue = 0.7029 df = 1 ***************************************** RW test RW statistic value = 1.518441 pvalue = 0.217856 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4100 sd = 0.0531 freq = 0.4096 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.5900 sd = 0.0531 freq = 0.5904 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.3937 freq = 0.0000 freq = 0.3984 allele 2 : freq = 0.5875 freq = 0.6062 freq = 0.0000 freq = 0.6016 ***************************************** **************************************** Analysis of Marker 200: rs200 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.403165 pvalue = 0.525459 df = 1 ***************************************** RCHI test RCHI statistic value = 0.089117 pvalue = 0.765302 df = 1 ***************************************** RW test RW statistic value = 0.031524 pvalue = 0.859076 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8233 sd = 0.0412 freq = 0.8673 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 allele 2 : freq = 0.1767 sd = 0.0412 freq = 0.1327 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8479 freq = 0.0000 freq = 0.8453 allele 2 : freq = 0.1625 freq = 0.1521 freq = 0.0000 freq = 0.1547 ***************************************** **************************************** Analysis of Marker 201: rs201 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.421310 pvalue = 0.516284 df = 1 ***************************************** RCHI test RCHI statistic value = 0.101119 pvalue = 0.750491 df = 1 ***************************************** RW test RW statistic value = 1.167990 pvalue = 0.279815 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6883 sd = 0.0500 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 allele 2 : freq = 0.3117 sd = 0.0500 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 freq = 0.6896 freq = 0.0000 freq = 0.6859 allele 2 : freq = 0.3250 freq = 0.3104 freq = 0.0000 freq = 0.3141 ***************************************** **************************************** Analysis of Marker 202: rs202 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.396618 pvalue = 0.237291 df = 1 ***************************************** RCHI test RCHI statistic value = 1.933322 pvalue = 0.164395 df = 1 ***************************************** RW test RW statistic value = 0.620308 pvalue = 0.430933 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1417 sd = 0.0377 freq = 0.1000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221 allele 2 : freq = 0.8583 sd = 0.0377 freq = 0.9000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1375 freq = 0.0938 freq = 0.0000 freq = 0.1047 allele 2 : freq = 0.8625 freq = 0.9062 freq = 0.0000 freq = 0.8953 ***************************************** **************************************** Analysis of Marker 203: rs203 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.210292 pvalue = 0.271274 df = 1 ***************************************** RCHI test RCHI statistic value = 0.280573 pvalue = 0.596326 df = 1 ***************************************** RW test RW statistic value = 0.553300 pvalue = 0.456973 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0783 sd = 0.0290 freq = 0.1077 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221 allele 2 : freq = 0.9217 sd = 0.0290 freq = 0.8923 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0750 freq = 0.0917 freq = 0.0000 freq = 0.0875 allele 2 : freq = 0.9250 freq = 0.9083 freq = 0.0000 freq = 0.9125 ***************************************** **************************************** Analysis of Marker 204: rs204 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.114226 pvalue = 0.735384 df = 1 ***************************************** RCHI test RCHI statistic value = 0.008923 pvalue = 0.924743 df = 1 ***************************************** RW test RW statistic value = 0.515342 pvalue = 0.472835 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2350 sd = 0.0458 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310 allele 2 : freq = 0.7650 sd = 0.0458 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.2479 freq = 0.0000 freq = 0.2469 allele 2 : freq = 0.7562 freq = 0.7521 freq = 0.0000 freq = 0.7531 ***************************************** **************************************** Analysis of Marker 205: rs205 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.449687 pvalue = 0.228578 df = 1 ***************************************** RCHI test RCHI statistic value = 1.674883 pvalue = 0.195606 df = 1 ***************************************** RW test RW statistic value = 0.325086 pvalue = 0.568567 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1417 sd = 0.0377 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 allele 2 : freq = 0.8583 sd = 0.0377 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1437 freq = 0.1938 freq = 0.0000 freq = 0.1812 allele 2 : freq = 0.8562 freq = 0.8063 freq = 0.0000 freq = 0.8187 ***************************************** **************************************** Analysis of Marker 206: rs206 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.073784 pvalue = 0.785905 df = 1 ***************************************** RCHI test RCHI statistic value = 0.128329 pvalue = 0.720171 df = 1 ***************************************** RW test RW statistic value = 0.374009 pvalue = 0.540827 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1400 sd = 0.0375 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8600 sd = 0.0375 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1562 freq = 0.1688 freq = 0.0000 freq = 0.1656 allele 2 : freq = 0.8438 freq = 0.8313 freq = 0.0000 freq = 0.8344 ***************************************** **************************************** Analysis of Marker 207: rs207 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.039915 pvalue = 0.841647 df = 1 ***************************************** RCHI test RCHI statistic value = 0.017902 pvalue = 0.893563 df = 1 ***************************************** RW test RW statistic value = 0.026277 pvalue = 0.871227 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7067 sd = 0.0492 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.2933 sd = 0.0492 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.6875 freq = 0.0000 freq = 0.6891 allele 2 : freq = 0.3063 freq = 0.3125 freq = 0.0000 freq = 0.3109 ***************************************** **************************************** Analysis of Marker 208: rs208 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.019996 pvalue = 0.88755 df = 1 ***************************************** RCHI test RCHI statistic value = 0.040687 pvalue = 0.840142 df = 1 ***************************************** RW test RW statistic value = 2.199161 pvalue = 0.138086 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 sd = 0.0451 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 allele 2 : freq = 0.2250 sd = 0.0451 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7896 freq = 0.0000 freq = 0.7875 allele 2 : freq = 0.2188 freq = 0.2104 freq = 0.0000 freq = 0.2125 ***************************************** **************************************** Analysis of Marker 209: rs209 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001646 pvalue = 0.967634 df = 1 ***************************************** RCHI test RCHI statistic value = 0.473893 pvalue = 0.491202 df = 1 ***************************************** RW test RW statistic value = 0.552111 pvalue = 0.457456 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7133 sd = 0.0488 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 allele 2 : freq = 0.2867 sd = 0.0488 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7250 freq = 0.7562 freq = 0.0000 freq = 0.7484 allele 2 : freq = 0.2750 freq = 0.2437 freq = 0.0000 freq = 0.2516 ***************************************** **************************************** Analysis of Marker 210: rs210 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.073893 pvalue = 0.300068 df = 1 ***************************************** RCHI test RCHI statistic value = 2.577818 pvalue = 0.108371 df = 1 ***************************************** RW test RW statistic value = 0.042564 pvalue = 0.836549 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3300 sd = 0.0508 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.6700 sd = 0.0508 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.2687 freq = 0.0000 freq = 0.2875 allele 2 : freq = 0.6562 freq = 0.7312 freq = 0.0000 freq = 0.7125 ***************************************** **************************************** Analysis of Marker 211: rs211 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.457151 pvalue = 0.116991 df = 1 ***************************************** RCHI test RCHI statistic value = 1.252642 pvalue = 0.263049 df = 1 ***************************************** RW test RW statistic value = 2.438068 pvalue = 0.118422 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5867 sd = 0.0532 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 allele 2 : freq = 0.4133 sd = 0.0532 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.5312 freq = 0.0000 freq = 0.5453 allele 2 : freq = 0.4125 freq = 0.4688 freq = 0.0000 freq = 0.4547 ***************************************** **************************************** Analysis of Marker 212: rs212 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.009836 pvalue = 0.920999 df = 1 ***************************************** RCHI test RCHI statistic value = 0.174984 pvalue = 0.67572 df = 1 ***************************************** RW test RW statistic value = 0.687760 pvalue = 0.406927 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1933 sd = 0.0427 freq = 0.2096 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280 allele 2 : freq = 0.8067 sd = 0.0427 freq = 0.7904 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2062 freq = 0.2229 freq = 0.0000 freq = 0.2188 allele 2 : freq = 0.7937 freq = 0.7771 freq = 0.0000 freq = 0.7812 ***************************************** **************************************** Analysis of Marker 213: rs213 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.251046 pvalue = 0.61634 df = 1 ***************************************** RCHI test RCHI statistic value = 0.695113 pvalue = 0.404431 df = 1 ***************************************** RW test RW statistic value = 1.436054 pvalue = 0.230779 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4617 sd = 0.0538 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.5383 sd = 0.0538 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4313 freq = 0.4729 freq = 0.0000 freq = 0.4625 allele 2 : freq = 0.5687 freq = 0.5271 freq = 0.0000 freq = 0.5375 ***************************************** **************************************** Analysis of Marker 214: rs214 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.432925 pvalue = 0.231288 df = 1 ***************************************** RCHI test RCHI statistic value = 1.583745 pvalue = 0.208222 df = 1 ***************************************** RW test RW statistic value = 0.607890 pvalue = 0.435584 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0933 sd = 0.0314 freq = 0.0750 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186 allele 2 : freq = 0.9067 sd = 0.0314 freq = 0.9250 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1000 freq = 0.0667 freq = 0.0000 freq = 0.0750 allele 2 : freq = 0.9000 freq = 0.9333 freq = 0.0000 freq = 0.9250 ***************************************** **************************************** Analysis of Marker 215: rs215 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.495564 pvalue = 0.481456 df = 1 ***************************************** RCHI test RCHI statistic value = 0.304173 pvalue = 0.581278 df = 1 ***************************************** RW test RW statistic value = 2.513603 pvalue = 0.112868 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2083 sd = 0.0439 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.7917 sd = 0.0439 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1938 freq = 0.1729 freq = 0.0000 freq = 0.1781 allele 2 : freq = 0.8063 freq = 0.8271 freq = 0.0000 freq = 0.8219 ***************************************** **************************************** Analysis of Marker 216: rs216 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.171720 pvalue = 0.678587 df = 1 ***************************************** RCHI test RCHI statistic value = 0.114176 pvalue = 0.735439 df = 1 ***************************************** RW test RW statistic value = 1.916709 pvalue = 0.16622 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8904 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217 allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1096 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9062 freq = 0.8958 freq = 0.0000 freq = 0.8984 allele 2 : freq = 0.0938 freq = 0.1042 freq = 0.0000 freq = 0.1016 ***************************************** **************************************** Analysis of Marker 217: rs217 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.003186 pvalue = 0.95499 df = 1 ***************************************** RCHI test RCHI statistic value = 0.062527 pvalue = 0.802545 df = 1 ***************************************** RW test RW statistic value = 2.311232 pvalue = 0.128442 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2133 sd = 0.0442 freq = 0.2077 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 allele 2 : freq = 0.7867 sd = 0.0442 freq = 0.7923 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2188 freq = 0.2083 freq = 0.0000 freq = 0.2109 allele 2 : freq = 0.7812 freq = 0.7917 freq = 0.0000 freq = 0.7891 ***************************************** **************************************** Analysis of Marker 218: rs218 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.017339 pvalue = 0.89524 df = 1 ***************************************** RCHI test RCHI statistic value = 0.362942 pvalue = 0.546877 df = 1 ***************************************** RW test RW statistic value = 0.427794 pvalue = 0.513074 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6333 sd = 0.0521 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340 allele 2 : freq = 0.3667 sd = 0.0521 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6312 freq = 0.6021 freq = 0.0000 freq = 0.6094 allele 2 : freq = 0.3688 freq = 0.3979 freq = 0.0000 freq = 0.3906 ***************************************** **************************************** Analysis of Marker 219: rs219 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.383849 pvalue = 0.239447 df = 1 ***************************************** RCHI test RCHI statistic value = 1.651253 pvalue = 0.198789 df = 1 ***************************************** RW test RW statistic value = 0.132451 pvalue = 0.715904 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7383 sd = 0.0475 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 allele 2 : freq = 0.2617 sd = 0.0475 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.6979 freq = 0.0000 freq = 0.7125 allele 2 : freq = 0.2437 freq = 0.3021 freq = 0.0000 freq = 0.2875 ***************************************** **************************************** Analysis of Marker 220: rs220 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.221852 pvalue = 0.637632 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.387036 pvalue = 0.533862 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1250 freq = 0.1250 freq = 0.0000 freq = 0.1250 allele 2 : freq = 0.8750 freq = 0.8750 freq = 0.0000 freq = 0.8750 ***************************************** **************************************** Analysis of Marker 221: rs221 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.183065 pvalue = 0.668752 df = 1 ***************************************** RCHI test RCHI statistic value = 0.268243 pvalue = 0.604513 df = 1 ***************************************** RW test RW statistic value = 0.593048 pvalue = 0.441243 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1783 sd = 0.0413 freq = 0.1981 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 allele 2 : freq = 0.8217 sd = 0.0413 freq = 0.8019 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.2083 freq = 0.0000 freq = 0.2031 allele 2 : freq = 0.8125 freq = 0.7917 freq = 0.0000 freq = 0.7969 ***************************************** **************************************** Analysis of Marker 222: rs222 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.659322 pvalue = 0.416799 df = 1 ***************************************** RCHI test RCHI statistic value = 0.115461 pvalue = 0.734011 df = 1 ***************************************** RW test RW statistic value = 0.038605 pvalue = 0.844233 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5850 sd = 0.0532 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 allele 2 : freq = 0.4150 sd = 0.0532 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5687 freq = 0.5854 freq = 0.0000 freq = 0.5813 allele 2 : freq = 0.4313 freq = 0.4146 freq = 0.0000 freq = 0.4188 ***************************************** **************************************** Analysis of Marker 223: rs223 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.363098 pvalue = 0.546791 df = 1 ***************************************** RCHI test RCHI statistic value = 0.409559 pvalue = 0.522193 df = 1 ***************************************** RW test RW statistic value = 0.076465 pvalue = 0.782146 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2467 sd = 0.0466 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 allele 2 : freq = 0.7533 sd = 0.0466 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 freq = 0.2229 freq = 0.0000 freq = 0.2297 allele 2 : freq = 0.7500 freq = 0.7771 freq = 0.0000 freq = 0.7703 ***************************************** **************************************** Analysis of Marker 224: rs224 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.663307 pvalue = 0.197157 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** RCHI test RCHI statistic value = 3.114311 pvalue = 0.0776073 df = 1 The p-value might not be exact because of the small number of allele 1 in cases ***************************************** RW test RW statistic value = 10.374715 pvalue = 0.00127753 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0483 sd = 0.0232 freq = 0.0750 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174 allele 2 : freq = 0.9517 sd = 0.0232 freq = 0.9250 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0437 freq = 0.0875 freq = 0.0000 freq = 0.0766 allele 2 : freq = 0.9563 freq = 0.9125 freq = 0.0000 freq = 0.9234 ***************************************** **************************************** Analysis of Marker 225: rs225 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.755063 pvalue = 0.384878 df = 1 ***************************************** RCHI test RCHI statistic value = 0.516815 pvalue = 0.472204 df = 1 ***************************************** RW test RW statistic value = 0.122026 pvalue = 0.726847 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 sd = 0.0534 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 allele 2 : freq = 0.4250 sd = 0.0534 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5625 freq = 0.5979 freq = 0.0000 freq = 0.5891 allele 2 : freq = 0.4375 freq = 0.4021 freq = 0.0000 freq = 0.4109 ***************************************** **************************************** Analysis of Marker 226: rs226 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.225087 pvalue = 0.635191 df = 1 ***************************************** RCHI test RCHI statistic value = 0.873171 pvalue = 0.350079 df = 1 ***************************************** RW test RW statistic value = 0.806772 pvalue = 0.369076 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5967 sd = 0.0530 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 allele 2 : freq = 0.4033 sd = 0.0530 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.6458 freq = 0.0000 freq = 0.6344 allele 2 : freq = 0.4000 freq = 0.3542 freq = 0.0000 freq = 0.3656 ***************************************** **************************************** Analysis of Marker 227: rs227 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.096663 pvalue = 0.755872 df = 1 ***************************************** RCHI test RCHI statistic value = 0.627469 pvalue = 0.428285 df = 1 ***************************************** RW test RW statistic value = 0.791930 pvalue = 0.373517 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8017 sd = 0.0431 freq = 0.8096 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.1983 sd = 0.0431 freq = 0.1904 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8125 freq = 0.7812 freq = 0.0000 freq = 0.7891 allele 2 : freq = 0.1875 freq = 0.2188 freq = 0.0000 freq = 0.2109 ***************************************** **************************************** Analysis of Marker 228: rs228 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 9.120176 pvalue = 0.00252806 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 6.524756 pvalue = 0.0106383 df = 1 ***************************************** RW test RW statistic value = 5.775847 pvalue = 0.0162479 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.3404 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.6596 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4813 freq = 0.3583 freq = 0.0000 freq = 0.3891 allele 2 : freq = 0.5188 freq = 0.6417 freq = 0.0000 freq = 0.6109 ***************************************** **************************************** Analysis of Marker 229: rs229 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.936594 pvalue = 0.333155 df = 1 ***************************************** RCHI test RCHI statistic value = 1.555032 pvalue = 0.212394 df = 1 ***************************************** RW test RW statistic value = 0.950934 pvalue = 0.329482 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4883 sd = 0.0540 freq = 0.4481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 allele 2 : freq = 0.5117 sd = 0.0540 freq = 0.5519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4938 freq = 0.4313 freq = 0.0000 freq = 0.4469 allele 2 : freq = 0.5062 freq = 0.5687 freq = 0.0000 freq = 0.5531 ***************************************** **************************************** Analysis of Marker 230: rs230 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.899426 pvalue = 0.168143 df = 1 ***************************************** RCHI test RCHI statistic value = 1.079561 pvalue = 0.298796 df = 1 ***************************************** RW test RW statistic value = 0.596690 pvalue = 0.439844 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9267 sd = 0.0282 freq = 0.8827 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 allele 2 : freq = 0.0733 sd = 0.0282 freq = 0.1173 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9250 freq = 0.8917 freq = 0.0000 freq = 0.9000 allele 2 : freq = 0.0750 freq = 0.1083 freq = 0.0000 freq = 0.1000 ***************************************** **************************************** Analysis of Marker 231: rs231 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.231512 pvalue = 0.630405 df = 1 ***************************************** RCHI test RCHI statistic value = 0.339232 pvalue = 0.560273 df = 1 ***************************************** RW test RW statistic value = 0.613941 pvalue = 0.433308 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5625 freq = 0.5333 freq = 0.0000 freq = 0.5406 allele 2 : freq = 0.4375 freq = 0.4667 freq = 0.0000 freq = 0.4594 ***************************************** **************************************** Analysis of Marker 232: rs232 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.006434 pvalue = 0.936069 df = 1 ***************************************** RCHI test RCHI statistic value = 0.109502 pvalue = 0.740711 df = 1 ***************************************** RW test RW statistic value = 0.175677 pvalue = 0.675115 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8383 sd = 0.0398 freq = 0.8288 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.1617 sd = 0.0398 freq = 0.1712 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8313 freq = 0.8438 freq = 0.0000 freq = 0.8406 allele 2 : freq = 0.1688 freq = 0.1562 freq = 0.0000 freq = 0.1594 ***************************************** **************************************** Analysis of Marker 233: rs233 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.069792 pvalue = 0.791641 df = 1 ***************************************** RCHI test RCHI statistic value = 0.122554 pvalue = 0.726281 df = 1 ***************************************** RW test RW statistic value = 0.001092 pvalue = 0.973635 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7900 sd = 0.0440 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 allele 2 : freq = 0.2100 sd = 0.0440 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7875 freq = 0.7729 freq = 0.0000 freq = 0.7766 allele 2 : freq = 0.2125 freq = 0.2271 freq = 0.0000 freq = 0.2234 ***************************************** **************************************** Analysis of Marker 234: rs234 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.069181 pvalue = 0.792533 df = 1 ***************************************** RCHI test RCHI statistic value = 0.176548 pvalue = 0.674357 df = 1 ***************************************** RW test RW statistic value = 4.811875 pvalue = 0.0282643 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9200 sd = 0.0293 freq = 0.9346 sd = 0.0188 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174 allele 2 : freq = 0.0800 sd = 0.0293 freq = 0.0654 sd = 0.0188 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9313 freq = 0.9417 freq = 0.0000 freq = 0.9391 allele 2 : freq = 0.0688 freq = 0.0583 freq = 0.0000 freq = 0.0609 ***************************************** **************************************** Analysis of Marker 235: rs235 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000104 pvalue = 0.991849 df = 1 ***************************************** RCHI test RCHI statistic value = 0.174627 pvalue = 0.676032 df = 1 ***************************************** RW test RW statistic value = 0.369107 pvalue = 0.543491 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4117 sd = 0.0532 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.5883 sd = 0.0532 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4437 freq = 0.4646 freq = 0.0000 freq = 0.4594 allele 2 : freq = 0.5563 freq = 0.5354 freq = 0.0000 freq = 0.5406 ***************************************** **************************************** Analysis of Marker 236: rs236 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.023469 pvalue = 0.878244 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003277 pvalue = 0.954351 df = 1 ***************************************** RW test RW statistic value = 0.051518 pvalue = 0.820443 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1717 sd = 0.0407 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 allele 2 : freq = 0.8283 sd = 0.0407 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1625 freq = 0.1646 freq = 0.0000 freq = 0.1641 allele 2 : freq = 0.8375 freq = 0.8354 freq = 0.0000 freq = 0.8359 ***************************************** **************************************** Analysis of Marker 237: rs237 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.301221 pvalue = 0.583118 df = 1 ***************************************** RCHI test RCHI statistic value = 0.121183 pvalue = 0.727755 df = 1 ***************************************** RW test RW statistic value = 0.082691 pvalue = 0.773683 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8550 sd = 0.0380 freq = 0.8481 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1450 sd = 0.0380 freq = 0.1519 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8688 freq = 0.8562 freq = 0.0000 freq = 0.8594 allele 2 : freq = 0.1313 freq = 0.1437 freq = 0.0000 freq = 0.1406 ***************************************** **************************************** Analysis of Marker 238: rs238 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.021485 pvalue = 0.883465 df = 1 ***************************************** RCHI test RCHI statistic value = 0.421704 pvalue = 0.516088 df = 1 ***************************************** RW test RW statistic value = 0.055710 pvalue = 0.81341 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8767 sd = 0.0355 freq = 0.9000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 allele 2 : freq = 0.1233 sd = 0.0355 freq = 0.1000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.9083 freq = 0.0000 freq = 0.9031 allele 2 : freq = 0.1125 freq = 0.0917 freq = 0.0000 freq = 0.0969 ***************************************** **************************************** Analysis of Marker 239: rs239 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.820180 pvalue = 0.093086 df = 1 ***************************************** RCHI test RCHI statistic value = 1.856147 pvalue = 0.17307 df = 1 ***************************************** RW test RW statistic value = 1.939634 pvalue = 0.163708 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6650 sd = 0.0510 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 allele 2 : freq = 0.3350 sd = 0.0510 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.6208 freq = 0.0000 freq = 0.6375 allele 2 : freq = 0.3125 freq = 0.3792 freq = 0.0000 freq = 0.3625 ***************************************** **************************************** Analysis of Marker 240: rs240 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.078706 pvalue = 0.779059 df = 1 ***************************************** RCHI test RCHI statistic value = 0.009845 pvalue = 0.920961 df = 1 ***************************************** RW test RW statistic value = 0.241849 pvalue = 0.622874 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7817 sd = 0.0446 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 allele 2 : freq = 0.2183 sd = 0.0446 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7667 freq = 0.0000 freq = 0.7656 allele 2 : freq = 0.2375 freq = 0.2333 freq = 0.0000 freq = 0.2344 ***************************************** **************************************** Analysis of Marker 241: rs241 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.312392 pvalue = 0.251962 df = 1 ***************************************** RCHI test RCHI statistic value = 0.118512 pvalue = 0.730654 df = 1 ***************************************** RW test RW statistic value = 0.194286 pvalue = 0.659373 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4117 sd = 0.0532 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340 allele 2 : freq = 0.5883 sd = 0.0532 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 freq = 0.4083 freq = 0.0000 freq = 0.4125 allele 2 : freq = 0.5750 freq = 0.5917 freq = 0.0000 freq = 0.5875 ***************************************** **************************************** Analysis of Marker 242: rs242 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.390521 pvalue = 0.532026 df = 1 ***************************************** RCHI test RCHI statistic value = 0.351842 pvalue = 0.553072 df = 1 ***************************************** RW test RW statistic value = 0.731444 pvalue = 0.392415 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2083 sd = 0.0439 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 allele 2 : freq = 0.7917 sd = 0.0439 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2000 freq = 0.1771 freq = 0.0000 freq = 0.1828 allele 2 : freq = 0.8000 freq = 0.8229 freq = 0.0000 freq = 0.8172 ***************************************** **************************************** Analysis of Marker 243: rs243 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.027024 pvalue = 0.869424 df = 1 ***************************************** RCHI test RCHI statistic value = 0.059335 pvalue = 0.80755 df = 1 ***************************************** RW test RW statistic value = 1.269705 pvalue = 0.259822 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9300 sd = 0.0276 freq = 0.9308 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.9300 sd = 0.0180 allele 2 : freq = 0.0700 sd = 0.0276 freq = 0.0692 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.0700 sd = 0.0180 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9375 freq = 0.9437 freq = 0.0000 freq = 0.9422 allele 2 : freq = 0.0625 freq = 0.0563 freq = 0.0000 freq = 0.0578 ***************************************** **************************************** Analysis of Marker 244: rs244 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001429 pvalue = 0.969845 df = 1 ***************************************** RCHI test RCHI statistic value = 0.013465 pvalue = 0.907623 df = 1 ***************************************** RW test RW statistic value = 0.009188 pvalue = 0.923637 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1533 sd = 0.0389 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 allele 2 : freq = 0.8467 sd = 0.0389 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1500 freq = 0.1458 freq = 0.0000 freq = 0.1469 allele 2 : freq = 0.8500 freq = 0.8542 freq = 0.0000 freq = 0.8531 ***************************************** **************************************** Analysis of Marker 245: rs245 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.884776 pvalue = 0.346897 df = 1 ***************************************** RCHI test RCHI statistic value = 2.195562 pvalue = 0.138409 df = 1 ***************************************** RW test RW statistic value = 2.887279 pvalue = 0.0892816 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3200 sd = 0.0504 freq = 0.3635 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 allele 2 : freq = 0.6800 sd = 0.0504 freq = 0.6365 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3187 freq = 0.3896 freq = 0.0000 freq = 0.3719 allele 2 : freq = 0.6813 freq = 0.6104 freq = 0.0000 freq = 0.6281 ***************************************** **************************************** Analysis of Marker 246: rs246 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.950525 pvalue = 0.0147129 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 5.495905 pvalue = 0.0190611 df = 1 ***************************************** RW test RW statistic value = 3.023913 pvalue = 0.0820453 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6883 sd = 0.0500 freq = 0.7654 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 allele 2 : freq = 0.3117 sd = 0.0500 freq = 0.2346 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6625 freq = 0.7646 freq = 0.0000 freq = 0.7391 allele 2 : freq = 0.3375 freq = 0.2354 freq = 0.0000 freq = 0.2609 ***************************************** **************************************** Analysis of Marker 247: rs247 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.134806 pvalue = 0.7135 df = 1 ***************************************** RCHI test RCHI statistic value = 0.087243 pvalue = 0.767711 df = 1 ***************************************** RW test RW statistic value = 0.085726 pvalue = 0.769683 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.7688 freq = 0.0000 freq = 0.7656 allele 2 : freq = 0.2437 freq = 0.2313 freq = 0.0000 freq = 0.2344 ***************************************** **************************************** Analysis of Marker 248: rs248 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.860469 pvalue = 0.090781 df = 1 ***************************************** RCHI test RCHI statistic value = 1.251640 pvalue = 0.26324 df = 1 ***************************************** RW test RW statistic value = 1.111399 pvalue = 0.291778 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5950 sd = 0.0530 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.4050 sd = 0.0530 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.5188 freq = 0.0000 freq = 0.5328 allele 2 : freq = 0.4250 freq = 0.4813 freq = 0.0000 freq = 0.4672 ***************************************** **************************************** Analysis of Marker 249: rs249 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.243673 pvalue = 0.621566 df = 1 ***************************************** RCHI test RCHI statistic value = 0.357050 pvalue = 0.550149 df = 1 ***************************************** RW test RW statistic value = 1.337327 pvalue = 0.247506 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6183 sd = 0.0525 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 allele 2 : freq = 0.3817 sd = 0.0525 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6375 freq = 0.6083 freq = 0.0000 freq = 0.6156 allele 2 : freq = 0.3625 freq = 0.3917 freq = 0.0000 freq = 0.3844 ***************************************** **************************************** Analysis of Marker 250: rs250 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.687280 pvalue = 0.19396 df = 1 ***************************************** RCHI test RCHI statistic value = 1.254651 pvalue = 0.262666 df = 1 ***************************************** RW test RW statistic value = 4.810301 pvalue = 0.0282901 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5833 sd = 0.0533 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 allele 2 : freq = 0.4167 sd = 0.0533 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5813 freq = 0.5250 freq = 0.0000 freq = 0.5391 allele 2 : freq = 0.4188 freq = 0.4750 freq = 0.0000 freq = 0.4609 ***************************************** **************************************** Analysis of Marker 251: rs251 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.787329 pvalue = 0.374909 df = 1 ***************************************** RCHI test RCHI statistic value = 0.712420 pvalue = 0.398641 df = 1 ***************************************** RW test RW statistic value = 1.471810 pvalue = 0.22506 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6217 sd = 0.0524 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 allele 2 : freq = 0.3783 sd = 0.0524 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6312 freq = 0.5896 freq = 0.0000 freq = 0.6000 allele 2 : freq = 0.3688 freq = 0.4104 freq = 0.0000 freq = 0.4000 ***************************************** **************************************** Analysis of Marker 252: rs252 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 6.549328 pvalue = 0.0104924 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 3.019003 pvalue = 0.082294 df = 1 ***************************************** RW test RW statistic value = 11.013602 pvalue = 0.000904457 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4875 freq = 0.5729 freq = 0.0000 freq = 0.5516 allele 2 : freq = 0.5125 freq = 0.4271 freq = 0.0000 freq = 0.4484 ***************************************** **************************************** Analysis of Marker 253: rs253 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.894603 pvalue = 0.168684 df = 1 ***************************************** RCHI test RCHI statistic value = 2.528554 pvalue = 0.111803 df = 1 ***************************************** RW test RW statistic value = 3.132289 pvalue = 0.0767559 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 sd = 0.0539 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 allele 2 : freq = 0.4750 sd = 0.0539 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5188 freq = 0.5979 freq = 0.0000 freq = 0.5781 allele 2 : freq = 0.4813 freq = 0.4021 freq = 0.0000 freq = 0.4219 ***************************************** **************************************** Analysis of Marker 254: rs254 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.280431 pvalue = 0.0701105 df = 1 ***************************************** RCHI test RCHI statistic value = 3.950325 pvalue = 0.0468623 df = 1 ***************************************** RW test RW statistic value = 0.956687 pvalue = 0.328023 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3467 sd = 0.0514 freq = 0.4115 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 allele 2 : freq = 0.6533 sd = 0.0514 freq = 0.5885 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3312 freq = 0.4292 freq = 0.0000 freq = 0.4047 allele 2 : freq = 0.6687 freq = 0.5708 freq = 0.0000 freq = 0.5953 ***************************************** **************************************** Analysis of Marker 255: rs255 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.096153 pvalue = 0.756496 df = 1 ***************************************** RCHI test RCHI statistic value = 1.142948 pvalue = 0.28503 df = 1 ***************************************** RW test RW statistic value = 0.871587 pvalue = 0.350516 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9200 sd = 0.0293 freq = 0.9173 sd = 0.0209 freq = 0.0000 sd = 0.0000 freq = 0.9200 sd = 0.0192 allele 2 : freq = 0.0800 sd = 0.0293 freq = 0.0827 sd = 0.0209 freq = 0.0000 sd = 0.0000 freq = 0.0800 sd = 0.0192 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9187 freq = 0.8896 freq = 0.0000 freq = 0.8969 allele 2 : freq = 0.0813 freq = 0.1104 freq = 0.0000 freq = 0.1031 ***************************************** **************************************** Analysis of Marker 256: rs256 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.745679 pvalue = 0.0529442 df = 1 ***************************************** RCHI test RCHI statistic value = 2.785263 pvalue = 0.0951351 df = 1 ***************************************** RW test RW statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2917 sd = 0.0491 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 allele 2 : freq = 0.7083 sd = 0.0491 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2938 freq = 0.3750 freq = 0.0000 freq = 0.3547 allele 2 : freq = 0.7063 freq = 0.6250 freq = 0.0000 freq = 0.6453 ***************************************** **************************************** Analysis of Marker 257: rs257 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.088410 pvalue = 0.766209 df = 1 ***************************************** RCHI test RCHI statistic value = 0.832992 pvalue = 0.361409 df = 1 ***************************************** RW test RW statistic value = 0.300644 pvalue = 0.583479 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5333 sd = 0.0539 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 allele 2 : freq = 0.4667 sd = 0.0539 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.4792 freq = 0.0000 freq = 0.4906 allele 2 : freq = 0.4750 freq = 0.5208 freq = 0.0000 freq = 0.5094 ***************************************** **************************************** Analysis of Marker 258: rs258 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.072785 pvalue = 0.787325 df = 1 ***************************************** RCHI test RCHI statistic value = 0.021811 pvalue = 0.882591 df = 1 ***************************************** RW test RW statistic value = 0.288134 pvalue = 0.591419 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7750 freq = 0.0000 freq = 0.7766 allele 2 : freq = 0.2188 freq = 0.2250 freq = 0.0000 freq = 0.2234 ***************************************** **************************************** Analysis of Marker 259: rs259 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.343900 pvalue = 0.557587 df = 1 ***************************************** RCHI test RCHI statistic value = 0.005831 pvalue = 0.93913 df = 1 ***************************************** RW test RW statistic value = 1.123068 pvalue = 0.289259 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1017 sd = 0.0326 freq = 0.0808 sd = 0.0207 freq = 0.0000 sd = 0.0000 freq = 0.0800 sd = 0.0192 allele 2 : freq = 0.8983 sd = 0.0326 freq = 0.9192 sd = 0.0207 freq = 0.0000 sd = 0.0000 freq = 0.9200 sd = 0.0192 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1000 freq = 0.1021 freq = 0.0000 freq = 0.1016 allele 2 : freq = 0.9000 freq = 0.8979 freq = 0.0000 freq = 0.8984 ***************************************** **************************************** Analysis of Marker 260: rs260 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.896549 pvalue = 0.0483854 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 2.504035 pvalue = 0.113555 df = 1 ***************************************** RW test RW statistic value = 0.927697 pvalue = 0.335462 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6333 sd = 0.0521 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 allele 2 : freq = 0.3667 sd = 0.0521 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6375 freq = 0.5583 freq = 0.0000 freq = 0.5781 allele 2 : freq = 0.3625 freq = 0.4417 freq = 0.0000 freq = 0.4219 ***************************************** **************************************** Analysis of Marker 261: rs261 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.018346 pvalue = 0.0823274 df = 1 ***************************************** RCHI test RCHI statistic value = 4.422738 pvalue = 0.0354631 df = 1 ***************************************** RW test RW statistic value = 0.560012 pvalue = 0.454255 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1300 sd = 0.0363 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 allele 2 : freq = 0.8700 sd = 0.0363 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1313 freq = 0.2125 freq = 0.0000 freq = 0.1922 allele 2 : freq = 0.8688 freq = 0.7875 freq = 0.0000 freq = 0.8078 ***************************************** **************************************** Analysis of Marker 262: rs262 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001810 pvalue = 0.966061 df = 1 ***************************************** RCHI test RCHI statistic value = 0.071606 pvalue = 0.789013 df = 1 ***************************************** RW test RW statistic value = 0.017590 pvalue = 0.894488 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6783 sd = 0.0505 freq = 0.6885 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.3217 sd = 0.0505 freq = 0.3115 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.7000 freq = 0.0000 freq = 0.6969 allele 2 : freq = 0.3125 freq = 0.3000 freq = 0.0000 freq = 0.3031 ***************************************** **************************************** Analysis of Marker 263: rs263 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.514488 pvalue = 0.218456 df = 1 ***************************************** RCHI test RCHI statistic value = 2.698620 pvalue = 0.100435 df = 1 ***************************************** RW test RW statistic value = 1.208936 pvalue = 0.271543 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3650 sd = 0.0520 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 allele 2 : freq = 0.6350 sd = 0.0520 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3688 freq = 0.4500 freq = 0.0000 freq = 0.4297 allele 2 : freq = 0.6312 freq = 0.5500 freq = 0.0000 freq = 0.5703 ***************************************** **************************************** Analysis of Marker 264: rs264 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.158560 pvalue = 0.0755298 df = 1 ***************************************** RCHI test RCHI statistic value = 3.772167 pvalue = 0.0521121 df = 1 ***************************************** RW test RW statistic value = 2.199730 pvalue = 0.138035 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3067 sd = 0.0498 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339 allele 2 : freq = 0.6933 sd = 0.0498 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2938 freq = 0.3875 freq = 0.0000 freq = 0.3641 allele 2 : freq = 0.7063 freq = 0.6125 freq = 0.0000 freq = 0.6359 ***************************************** **************************************** Analysis of Marker 265: rs265 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.011249 pvalue = 0.915533 df = 1 ***************************************** RCHI test RCHI statistic value = 0.336518 pvalue = 0.561846 df = 1 ***************************************** RW test RW statistic value = 1.291352 pvalue = 0.255799 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4917 sd = 0.0540 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.5083 sd = 0.0540 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.5292 freq = 0.0000 freq = 0.5219 allele 2 : freq = 0.5000 freq = 0.4708 freq = 0.0000 freq = 0.4781 ***************************************** **************************************** Analysis of Marker 266: rs266 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.835783 pvalue = 0.360606 df = 1 ***************************************** RCHI test RCHI statistic value = 0.523202 pvalue = 0.469479 df = 1 ***************************************** RW test RW statistic value = 0.273339 pvalue = 0.601101 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3400 sd = 0.0512 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 allele 2 : freq = 0.6600 sd = 0.0512 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3042 freq = 0.0000 freq = 0.3125 allele 2 : freq = 0.6625 freq = 0.6958 freq = 0.0000 freq = 0.6875 ***************************************** **************************************** Analysis of Marker 267: rs267 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.969695 pvalue = 0.16048 df = 1 ***************************************** RCHI test RCHI statistic value = 1.552688 pvalue = 0.212739 df = 1 ***************************************** RW test RW statistic value = 1.846073 pvalue = 0.174241 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5533 sd = 0.0537 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 allele 2 : freq = 0.4467 sd = 0.0537 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.4625 freq = 0.0000 freq = 0.4781 allele 2 : freq = 0.4750 freq = 0.5375 freq = 0.0000 freq = 0.5219 ***************************************** **************************************** Analysis of Marker 268: rs268 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.097941 pvalue = 0.754315 df = 1 ***************************************** RCHI test RCHI statistic value = 0.114176 pvalue = 0.735439 df = 1 ***************************************** RW test RW statistic value = 0.363497 pvalue = 0.546571 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8883 sd = 0.0340 freq = 0.8923 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217 allele 2 : freq = 0.1117 sd = 0.0340 freq = 0.1077 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.8979 freq = 0.0000 freq = 0.8953 allele 2 : freq = 0.1125 freq = 0.1021 freq = 0.0000 freq = 0.1047 ***************************************** **************************************** Analysis of Marker 269: rs269 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.333575 pvalue = 0.24817 df = 1 ***************************************** RCHI test RCHI statistic value = 2.255496 pvalue = 0.133141 df = 1 ***************************************** RW test RW statistic value = 0.371689 pvalue = 0.542085 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6483 sd = 0.0516 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 allele 2 : freq = 0.3517 sd = 0.0516 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6687 freq = 0.5958 freq = 0.0000 freq = 0.6141 allele 2 : freq = 0.3312 freq = 0.4042 freq = 0.0000 freq = 0.3859 ***************************************** **************************************** Analysis of Marker 270: rs270 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.025071 pvalue = 0.87419 df = 1 ***************************************** RCHI test RCHI statistic value = 0.029299 pvalue = 0.86409 df = 1 ***************************************** RW test RW statistic value = 0.124955 pvalue = 0.723721 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3717 sd = 0.0522 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 allele 2 : freq = 0.6283 sd = 0.0522 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.3542 freq = 0.0000 freq = 0.3563 allele 2 : freq = 0.6375 freq = 0.6458 freq = 0.0000 freq = 0.6438 ***************************************** **************************************** Analysis of Marker 271: rs271 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.019633 pvalue = 0.888568 df = 1 ***************************************** RCHI test RCHI statistic value = 0.186280 pvalue = 0.666031 df = 1 ***************************************** RW test RW statistic value = 0.003254 pvalue = 0.95451 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3333 sd = 0.0509 freq = 0.3462 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339 allele 2 : freq = 0.6667 sd = 0.0509 freq = 0.6538 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.3229 freq = 0.0000 freq = 0.3281 allele 2 : freq = 0.6562 freq = 0.6771 freq = 0.0000 freq = 0.6719 ***************************************** **************************************** Analysis of Marker 272: rs272 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 7.243173 pvalue = 0.00711711 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 7.253290 pvalue = 0.00707712 df = 1 ***************************************** RW test RW statistic value = 3.873119 pvalue = 0.0490653 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1400 sd = 0.0375 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 allele 2 : freq = 0.8600 sd = 0.0375 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1125 freq = 0.2208 freq = 0.0000 freq = 0.1938 allele 2 : freq = 0.8875 freq = 0.7792 freq = 0.0000 freq = 0.8063 ***************************************** **************************************** Analysis of Marker 273: rs273 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.945759 pvalue = 0.0469896 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 2.482967 pvalue = 0.115085 df = 1 ***************************************** RW test RW statistic value = 4.987878 pvalue = 0.0255255 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4267 sd = 0.0534 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 allele 2 : freq = 0.5733 sd = 0.0534 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4313 freq = 0.5104 freq = 0.0000 freq = 0.4906 allele 2 : freq = 0.5687 freq = 0.4896 freq = 0.0000 freq = 0.5094 ***************************************** **************************************** Analysis of Marker 274: rs274 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.725854 pvalue = 0.188941 df = 1 ***************************************** RCHI test RCHI statistic value = 1.907506 pvalue = 0.167241 df = 1 ***************************************** RW test RW statistic value = 1.301615 pvalue = 0.253918 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1267 sd = 0.0359 freq = 0.1000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212 allele 2 : freq = 0.8733 sd = 0.0359 freq = 0.9000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1313 freq = 0.0896 freq = 0.0000 freq = 0.1000 allele 2 : freq = 0.8688 freq = 0.9104 freq = 0.0000 freq = 0.9000 ***************************************** **************************************** Analysis of Marker 275: rs275 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.447793 pvalue = 0.228882 df = 1 ***************************************** RCHI test RCHI statistic value = 1.727552 pvalue = 0.188724 df = 1 ***************************************** RW test RW statistic value = 6.081997 pvalue = 0.0136566 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6867 sd = 0.0501 freq = 0.7538 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 allele 2 : freq = 0.3133 sd = 0.0501 freq = 0.2462 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.7521 freq = 0.0000 freq = 0.7375 allele 2 : freq = 0.3063 freq = 0.2479 freq = 0.0000 freq = 0.2625 ***************************************** **************************************** Analysis of Marker 276: rs276 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.115387 pvalue = 0.734092 df = 1 ***************************************** RCHI test RCHI statistic value = 0.265427 pvalue = 0.606416 df = 1 ***************************************** RW test RW statistic value = 2.121183 pvalue = 0.145274 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8400 sd = 0.0396 freq = 0.8577 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 allele 2 : freq = 0.1600 sd = 0.0396 freq = 0.1423 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8562 freq = 0.0000 freq = 0.8516 allele 2 : freq = 0.1625 freq = 0.1437 freq = 0.0000 freq = 0.1484 ***************************************** **************************************** Analysis of Marker 277: rs277 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.012862 pvalue = 0.909706 df = 1 ***************************************** RCHI test RCHI statistic value = 0.121183 pvalue = 0.727755 df = 1 ***************************************** RW test RW statistic value = 0.082691 pvalue = 0.773683 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1500 sd = 0.0386 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 allele 2 : freq = 0.8500 sd = 0.0386 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1500 freq = 0.1375 freq = 0.0000 freq = 0.1406 allele 2 : freq = 0.8500 freq = 0.8625 freq = 0.0000 freq = 0.8594 ***************************************** **************************************** Analysis of Marker 278: rs278 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.030846 pvalue = 0.30996 df = 1 ***************************************** RCHI test RCHI statistic value = 1.780713 pvalue = 0.182062 df = 1 ***************************************** RW test RW statistic value = 1.800823 pvalue = 0.179613 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1717 sd = 0.0407 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 allele 2 : freq = 0.8283 sd = 0.0407 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.1271 freq = 0.0000 freq = 0.1391 allele 2 : freq = 0.8250 freq = 0.8729 freq = 0.0000 freq = 0.8609 ***************************************** **************************************** Analysis of Marker 279: rs279 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.277129 pvalue = 0.258434 df = 1 ***************************************** RCHI test RCHI statistic value = 0.572782 pvalue = 0.449156 df = 1 ***************************************** RW test RW statistic value = 0.006948 pvalue = 0.933568 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.4288 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.5712 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.4000 freq = 0.0000 freq = 0.3906 allele 2 : freq = 0.6375 freq = 0.6000 freq = 0.0000 freq = 0.6094 ***************************************** **************************************** Analysis of Marker 280: rs280 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.532938 pvalue = 0.0601611 df = 1 ***************************************** RCHI test RCHI statistic value = 2.243227 pvalue = 0.134201 df = 1 ***************************************** RW test RW statistic value = 0.124955 pvalue = 0.723721 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5650 sd = 0.0535 freq = 0.6346 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.4350 sd = 0.0535 freq = 0.3654 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5437 freq = 0.6167 freq = 0.0000 freq = 0.5984 allele 2 : freq = 0.4562 freq = 0.3833 freq = 0.0000 freq = 0.4016 ***************************************** **************************************** Analysis of Marker 281: rs281 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.031370 pvalue = 0.859418 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003924 pvalue = 0.950052 df = 1 ***************************************** RW test RW statistic value = 0.524811 pvalue = 0.468797 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8850 sd = 0.0345 freq = 0.8769 sd = 0.0250 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 allele 2 : freq = 0.1150 sd = 0.0345 freq = 0.1231 sd = 0.0250 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8812 freq = 0.8792 freq = 0.0000 freq = 0.8797 allele 2 : freq = 0.1187 freq = 0.1208 freq = 0.0000 freq = 0.1203 ***************************************** **************************************** Analysis of Marker 282: rs282 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001875 pvalue = 0.965465 df = 1 ***************************************** RCHI test RCHI statistic value = 0.061532 pvalue = 0.80409 df = 1 ***************************************** RW test RW statistic value = 0.812880 pvalue = 0.36727 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7917 freq = 0.0000 freq = 0.7891 allele 2 : freq = 0.2188 freq = 0.2083 freq = 0.0000 freq = 0.2109 ***************************************** **************************************** Analysis of Marker 283: rs283 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.124753 pvalue = 0.288897 df = 1 ***************************************** RCHI test RCHI statistic value = 1.648085 pvalue = 0.19922 df = 1 ***************************************** RW test RW statistic value = 0.044984 pvalue = 0.832034 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6167 sd = 0.0525 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.3833 sd = 0.0525 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.6500 freq = 0.0000 freq = 0.6344 allele 2 : freq = 0.4125 freq = 0.3500 freq = 0.0000 freq = 0.3656 ***************************************** **************************************** Analysis of Marker 284: rs284 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.012972 pvalue = 0.909321 df = 1 ***************************************** RCHI test RCHI statistic value = 0.277424 pvalue = 0.598394 df = 1 ***************************************** RW test RW statistic value = 0.353579 pvalue = 0.552094 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3167 sd = 0.0502 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 allele 2 : freq = 0.6833 sd = 0.0502 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3187 freq = 0.2938 freq = 0.0000 freq = 0.3000 allele 2 : freq = 0.6813 freq = 0.7063 freq = 0.0000 freq = 0.7000 ***************************************** **************************************** Analysis of Marker 285: rs285 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.024962 pvalue = 0.311345 df = 1 ***************************************** RCHI test RCHI statistic value = 1.566613 pvalue = 0.2107 df = 1 ***************************************** RW test RW statistic value = 0.052065 pvalue = 0.819509 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6467 sd = 0.0516 freq = 0.6385 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339 allele 2 : freq = 0.3533 sd = 0.0516 freq = 0.3615 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 freq = 0.6146 freq = 0.0000 freq = 0.6297 allele 2 : freq = 0.3250 freq = 0.3854 freq = 0.0000 freq = 0.3703 ***************************************** **************************************** Analysis of Marker 286: rs286 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.054819 pvalue = 0.81488 df = 1 ***************************************** RCHI test RCHI statistic value = 0.031157 pvalue = 0.85989 df = 1 ***************************************** RW test RW statistic value = 0.122461 pvalue = 0.726381 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8617 sd = 0.0373 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 allele 2 : freq = 0.1383 sd = 0.0373 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8625 freq = 0.8562 freq = 0.0000 freq = 0.8578 allele 2 : freq = 0.1375 freq = 0.1437 freq = 0.0000 freq = 0.1422 ***************************************** **************************************** Analysis of Marker 287: rs287 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.075574 pvalue = 0.149674 df = 1 ***************************************** RCHI test RCHI statistic value = 2.019712 pvalue = 0.155269 df = 1 ***************************************** RW test RW statistic value = 0.220509 pvalue = 0.638652 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.3083 freq = 0.0000 freq = 0.3250 allele 2 : freq = 0.6250 freq = 0.6917 freq = 0.0000 freq = 0.6750 ***************************************** **************************************** Analysis of Marker 288: rs288 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.907315 pvalue = 0.340828 df = 1 ***************************************** RCHI test RCHI statistic value = 0.484731 pvalue = 0.486287 df = 1 ***************************************** RW test RW statistic value = 0.147006 pvalue = 0.701413 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8083 sd = 0.0425 freq = 0.8500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1917 sd = 0.0425 freq = 0.1500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8187 freq = 0.8438 freq = 0.0000 freq = 0.8375 allele 2 : freq = 0.1812 freq = 0.1562 freq = 0.0000 freq = 0.1625 ***************************************** **************************************** Analysis of Marker 289: rs289 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.638764 pvalue = 0.424159 df = 1 ***************************************** RCHI test RCHI statistic value = 0.280751 pvalue = 0.59621 df = 1 ***************************************** RW test RW statistic value = 0.711580 pvalue = 0.39892 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7900 sd = 0.0440 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.2100 sd = 0.0440 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7875 freq = 0.7646 freq = 0.0000 freq = 0.7703 allele 2 : freq = 0.2125 freq = 0.2354 freq = 0.0000 freq = 0.2297 ***************************************** **************************************** Analysis of Marker 290: rs290 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.073448 pvalue = 0.149882 df = 1 ***************************************** RCHI test RCHI statistic value = 1.049710 pvalue = 0.305574 df = 1 ***************************************** RW test RW statistic value = 0.002857 pvalue = 0.957371 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7983 sd = 0.0433 freq = 0.8212 sd = 0.0291 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 allele 2 : freq = 0.2017 sd = 0.0433 freq = 0.1788 sd = 0.0291 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7688 freq = 0.8083 freq = 0.0000 freq = 0.7984 allele 2 : freq = 0.2313 freq = 0.1917 freq = 0.0000 freq = 0.2016 ***************************************** **************************************** Analysis of Marker 291: rs291 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.006196 pvalue = 0.937259 df = 1 ***************************************** RCHI test RCHI statistic value = 0.093133 pvalue = 0.760231 df = 1 ***************************************** RW test RW statistic value = 0.326510 pvalue = 0.567721 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7800 sd = 0.0447 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2200 sd = 0.0447 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7688 freq = 0.0000 freq = 0.7719 allele 2 : freq = 0.2188 freq = 0.2313 freq = 0.0000 freq = 0.2281 ***************************************** **************************************** Analysis of Marker 292: rs292 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000025 pvalue = 0.996006 df = 1 ***************************************** RCHI test RCHI statistic value = 0.146496 pvalue = 0.701906 df = 1 ***************************************** RW test RW statistic value = 0.024991 pvalue = 0.874389 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2350 sd = 0.0458 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.7650 sd = 0.0458 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.2271 freq = 0.0000 freq = 0.2313 allele 2 : freq = 0.7562 freq = 0.7729 freq = 0.0000 freq = 0.7688 ***************************************** **************************************** Analysis of Marker 293: rs293 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.295609 pvalue = 0.586648 df = 1 ***************************************** RCHI test RCHI statistic value = 0.891151 pvalue = 0.345166 df = 1 ***************************************** RW test RW statistic value = 0.218913 pvalue = 0.63987 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6317 sd = 0.0521 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 allele 2 : freq = 0.3683 sd = 0.0521 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6438 freq = 0.5979 freq = 0.0000 freq = 0.6094 allele 2 : freq = 0.3563 freq = 0.4021 freq = 0.0000 freq = 0.3906 ***************************************** **************************************** Analysis of Marker 294: rs294 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001921 pvalue = 0.965044 df = 1 ***************************************** RCHI test RCHI statistic value = 0.004217 pvalue = 0.948223 df = 1 ***************************************** RW test RW statistic value = 0.203040 pvalue = 0.652278 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8900 sd = 0.0338 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 allele 2 : freq = 0.1100 sd = 0.0338 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.8896 freq = 0.0000 freq = 0.8891 allele 2 : freq = 0.1125 freq = 0.1104 freq = 0.0000 freq = 0.1109 ***************************************** **************************************** Analysis of Marker 295: rs295 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.230138 pvalue = 0.631421 df = 1 ***************************************** RCHI test RCHI statistic value = 0.307865 pvalue = 0.578994 df = 1 ***************************************** RW test RW statistic value = 0.216590 pvalue = 0.641651 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.3896 freq = 0.0000 freq = 0.3828 allele 2 : freq = 0.6375 freq = 0.6104 freq = 0.0000 freq = 0.6172 ***************************************** **************************************** Analysis of Marker 296: rs296 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.949726 pvalue = 0.162616 df = 1 ***************************************** RCHI test RCHI statistic value = 2.230812 pvalue = 0.135283 df = 1 ***************************************** RW test RW statistic value = 0.016575 pvalue = 0.897561 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8550 sd = 0.0380 freq = 0.8865 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 allele 2 : freq = 0.1450 sd = 0.0380 freq = 0.1135 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8500 freq = 0.8979 freq = 0.0000 freq = 0.8859 allele 2 : freq = 0.1500 freq = 0.1021 freq = 0.0000 freq = 0.1141 ***************************************** **************************************** Analysis of Marker 297: rs297 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.007237 pvalue = 0.932203 df = 1 ***************************************** RCHI test RCHI statistic value = 0.005240 pvalue = 0.942291 df = 1 ***************************************** RW test RW statistic value = 0.252313 pvalue = 0.615451 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0833 sd = 0.0299 freq = 0.0827 sd = 0.0209 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202 allele 2 : freq = 0.9167 sd = 0.0299 freq = 0.9173 sd = 0.0209 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0938 freq = 0.0958 freq = 0.0000 freq = 0.0953 allele 2 : freq = 0.9062 freq = 0.9042 freq = 0.0000 freq = 0.9047 ***************************************** **************************************** Analysis of Marker 298: rs298 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.568362 pvalue = 0.450911 df = 1 ***************************************** RCHI test RCHI statistic value = 0.360879 pvalue = 0.548018 df = 1 ***************************************** RW test RW statistic value = 0.564670 pvalue = 0.452385 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3283 sd = 0.0507 freq = 0.3750 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 allele 2 : freq = 0.6717 sd = 0.0507 freq = 0.6250 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3667 freq = 0.0000 freq = 0.3594 allele 2 : freq = 0.6625 freq = 0.6333 freq = 0.0000 freq = 0.6406 ***************************************** **************************************** Analysis of Marker 299: rs299 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.193225 pvalue = 0.27468 df = 1 ***************************************** RCHI test RCHI statistic value = 1.123002 pvalue = 0.289273 df = 1 ***************************************** RW test RW statistic value = 0.852174 pvalue = 0.355938 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8033 sd = 0.0429 freq = 0.7442 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.1967 sd = 0.0429 freq = 0.2558 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7937 freq = 0.7479 freq = 0.0000 freq = 0.7594 allele 2 : freq = 0.2062 freq = 0.2521 freq = 0.0000 freq = 0.2406 ***************************************** **************************************** Analysis of Marker 300: rs300 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.917892 pvalue = 0.166089 df = 1 ***************************************** RCHI test RCHI statistic value = 0.557623 pvalue = 0.45522 df = 1 ***************************************** RW test RW statistic value = 0.018790 pvalue = 0.89097 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4667 sd = 0.0539 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 allele 2 : freq = 0.5333 sd = 0.0539 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.4938 freq = 0.0000 freq = 0.4844 allele 2 : freq = 0.5437 freq = 0.5062 freq = 0.0000 freq = 0.5156 ***************************************** **************************************** Analysis of Marker 301: rs301 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.298041 pvalue = 0.129537 df = 1 ***************************************** RCHI test RCHI statistic value = 4.198287 pvalue = 0.0404648 df = 1 ***************************************** RW test RW statistic value = 1.473736 pvalue = 0.224757 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1150 sd = 0.0345 freq = 0.0750 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207 allele 2 : freq = 0.8850 sd = 0.0345 freq = 0.9250 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1250 freq = 0.0646 freq = 0.0000 freq = 0.0797 allele 2 : freq = 0.8750 freq = 0.9354 freq = 0.0000 freq = 0.9203 ***************************************** **************************************** Analysis of Marker 302: rs302 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.289451 pvalue = 0.590573 df = 1 ***************************************** RCHI test RCHI statistic value = 0.837580 pvalue = 0.36009 df = 1 ***************************************** RW test RW statistic value = 0.067185 pvalue = 0.795481 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3283 sd = 0.0507 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 allele 2 : freq = 0.6717 sd = 0.0507 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3312 freq = 0.3750 freq = 0.0000 freq = 0.3641 allele 2 : freq = 0.6687 freq = 0.6250 freq = 0.0000 freq = 0.6359 ***************************************** **************************************** Analysis of Marker 303: rs303 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.761233 pvalue = 0.184471 df = 1 ***************************************** RCHI test RCHI statistic value = 3.670604 pvalue = 0.0553801 df = 1 ***************************************** RW test RW statistic value = 1.396394 pvalue = 0.237328 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.4375 freq = 0.0000 freq = 0.4141 allele 2 : freq = 0.6562 freq = 0.5625 freq = 0.0000 freq = 0.5859 ***************************************** **************************************** Analysis of Marker 304: rs304 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.765913 pvalue = 0.183889 df = 1 ***************************************** RCHI test RCHI statistic value = 3.306426 pvalue = 0.0690094 df = 1 ***************************************** RW test RW statistic value = 0.059142 pvalue = 0.807857 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7000 sd = 0.0495 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 allele 2 : freq = 0.3000 sd = 0.0495 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.6000 freq = 0.0000 freq = 0.6219 allele 2 : freq = 0.3125 freq = 0.4000 freq = 0.0000 freq = 0.3781 ***************************************** **************************************** Analysis of Marker 305: rs305 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.272614 pvalue = 0.0387313 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 1.959766 pvalue = 0.161538 df = 1 ***************************************** RW test RW statistic value = 2.982185 pvalue = 0.0841856 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6517 sd = 0.0515 freq = 0.7154 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 allele 2 : freq = 0.3483 sd = 0.0515 freq = 0.2846 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6438 freq = 0.7063 freq = 0.0000 freq = 0.6906 allele 2 : freq = 0.3563 freq = 0.2938 freq = 0.0000 freq = 0.3094 ***************************************** **************************************** Analysis of Marker 306: rs306 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.879955 pvalue = 0.0488659 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 2.252166 pvalue = 0.133428 df = 1 ***************************************** RW test RW statistic value = 0.148747 pvalue = 0.699736 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3600 sd = 0.0518 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.6400 sd = 0.0518 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3563 freq = 0.4313 freq = 0.0000 freq = 0.4125 allele 2 : freq = 0.6438 freq = 0.5687 freq = 0.0000 freq = 0.5875 ***************************************** **************************************** Analysis of Marker 307: rs307 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.445833 pvalue = 0.504321 df = 1 ***************************************** RCHI test RCHI statistic value = 0.921432 pvalue = 0.337099 df = 1 ***************************************** RW test RW statistic value = 2.924070 pvalue = 0.0872675 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5717 sd = 0.0534 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 allele 2 : freq = 0.4283 sd = 0.0534 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5813 freq = 0.5333 freq = 0.0000 freq = 0.5453 allele 2 : freq = 0.4188 freq = 0.4667 freq = 0.0000 freq = 0.4547 ***************************************** **************************************** Analysis of Marker 308: rs308 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.402738 pvalue = 0.525679 df = 1 ***************************************** RCHI test RCHI statistic value = 0.228901 pvalue = 0.63234 df = 1 ***************************************** RW test RW statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7267 sd = 0.0481 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 allele 2 : freq = 0.2733 sd = 0.0481 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7250 freq = 0.7458 freq = 0.0000 freq = 0.7406 allele 2 : freq = 0.2750 freq = 0.2542 freq = 0.0000 freq = 0.2594 ***************************************** **************************************** Analysis of Marker 309: rs309 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.075513 pvalue = 0.783472 df = 1 ***************************************** RCHI test RCHI statistic value = 0.042919 pvalue = 0.835878 df = 1 ***************************************** RW test RW statistic value = 0.379551 pvalue = 0.537844 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5033 sd = 0.0540 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.4967 sd = 0.0540 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4875 freq = 0.4979 freq = 0.0000 freq = 0.4953 allele 2 : freq = 0.5125 freq = 0.5021 freq = 0.0000 freq = 0.5047 ***************************************** **************************************** Analysis of Marker 310: rs310 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.014533 pvalue = 0.904045 df = 1 ***************************************** RCHI test RCHI statistic value = 0.209720 pvalue = 0.646987 df = 1 ***************************************** RW test RW statistic value = 0.060462 pvalue = 0.805767 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1683 sd = 0.0404 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 allele 2 : freq = 0.8317 sd = 0.0404 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1562 freq = 0.1729 freq = 0.0000 freq = 0.1688 allele 2 : freq = 0.8438 freq = 0.8271 freq = 0.0000 freq = 0.8313 ***************************************** **************************************** Analysis of Marker 311: rs311 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.729570 pvalue = 0.393023 df = 1 ***************************************** RCHI test RCHI statistic value = 1.243161 pvalue = 0.264863 df = 1 ***************************************** RW test RW statistic value = 1.424801 pvalue = 0.232615 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7150 sd = 0.0488 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.2850 sd = 0.0488 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7125 freq = 0.6604 freq = 0.0000 freq = 0.6734 allele 2 : freq = 0.2875 freq = 0.3396 freq = 0.0000 freq = 0.3266 ***************************************** **************************************** Analysis of Marker 312: rs312 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.761815 pvalue = 0.382761 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.048219 pvalue = 0.826192 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5967 sd = 0.0530 freq = 0.5558 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 allele 2 : freq = 0.4033 sd = 0.0530 freq = 0.4442 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.5875 freq = 0.0000 freq = 0.5875 allele 2 : freq = 0.4125 freq = 0.4125 freq = 0.0000 freq = 0.4125 ***************************************** **************************************** Analysis of Marker 313: rs313 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.104266 pvalue = 0.74677 df = 1 ***************************************** RCHI test RCHI statistic value = 0.067478 pvalue = 0.795045 df = 1 ***************************************** RW test RW statistic value = 0.222856 pvalue = 0.636872 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6200 sd = 0.0524 freq = 0.6462 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 allele 2 : freq = 0.3800 sd = 0.0524 freq = 0.3538 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6312 freq = 0.6438 freq = 0.0000 freq = 0.6406 allele 2 : freq = 0.3688 freq = 0.3563 freq = 0.0000 freq = 0.3594 ***************************************** **************************************** Analysis of Marker 314: rs314 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.874447 pvalue = 0.349727 df = 1 ***************************************** RCHI test RCHI statistic value = 0.640501 pvalue = 0.42353 df = 1 ***************************************** RW test RW statistic value = 0.607471 pvalue = 0.435742 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5500 freq = 0.5896 freq = 0.0000 freq = 0.5797 allele 2 : freq = 0.4500 freq = 0.4104 freq = 0.0000 freq = 0.4203 ***************************************** **************************************** Analysis of Marker 315: rs315 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.138100 pvalue = 0.710177 df = 1 ***************************************** RCHI test RCHI statistic value = 0.119219 pvalue = 0.729883 df = 1 ***************************************** RW test RW statistic value = 0.593048 pvalue = 0.441243 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6233 sd = 0.0523 freq = 0.6462 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339 allele 2 : freq = 0.3767 sd = 0.0523 freq = 0.3538 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6250 freq = 0.6417 freq = 0.0000 freq = 0.6375 allele 2 : freq = 0.3750 freq = 0.3583 freq = 0.0000 freq = 0.3625 ***************************************** **************************************** Analysis of Marker 316: rs316 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.413892 pvalue = 0.520001 df = 1 ***************************************** RCHI test RCHI statistic value = 0.407309 pvalue = 0.523339 df = 1 ***************************************** RW test RW statistic value = 0.036751 pvalue = 0.847972 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8650 sd = 0.0369 freq = 0.8500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1350 sd = 0.0369 freq = 0.1500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8688 freq = 0.8458 freq = 0.0000 freq = 0.8516 allele 2 : freq = 0.1313 freq = 0.1542 freq = 0.0000 freq = 0.1484 ***************************************** **************************************** Analysis of Marker 317: rs317 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.022566 pvalue = 0.311911 df = 1 ***************************************** RCHI test RCHI statistic value = 0.510907 pvalue = 0.474746 df = 1 ***************************************** RW test RW statistic value = 4.114214 pvalue = 0.0425243 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3717 sd = 0.0522 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 allele 2 : freq = 0.6283 sd = 0.0522 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3688 freq = 0.4042 freq = 0.0000 freq = 0.3953 allele 2 : freq = 0.6312 freq = 0.5958 freq = 0.0000 freq = 0.6047 ***************************************** **************************************** Analysis of Marker 318: rs318 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.645616 pvalue = 0.421684 df = 1 ***************************************** RCHI test RCHI statistic value = 0.119219 pvalue = 0.729883 df = 1 ***************************************** RW test RW statistic value = 0.468582 pvalue = 0.49364 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8733 sd = 0.0359 freq = 0.9038 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212 allele 2 : freq = 0.1267 sd = 0.0359 freq = 0.0962 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8750 freq = 0.8854 freq = 0.0000 freq = 0.8828 allele 2 : freq = 0.1250 freq = 0.1146 freq = 0.0000 freq = 0.1172 ***************************************** **************************************** Analysis of Marker 319: rs319 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.298495 pvalue = 0.584828 df = 1 ***************************************** RCHI test RCHI statistic value = 0.404090 pvalue = 0.524984 df = 1 ***************************************** RW test RW statistic value = 0.028235 pvalue = 0.866556 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3783 sd = 0.0524 freq = 0.3712 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6217 sd = 0.0524 freq = 0.6288 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.4062 freq = 0.0000 freq = 0.3984 allele 2 : freq = 0.6250 freq = 0.5938 freq = 0.0000 freq = 0.6016 ***************************************** **************************************** Analysis of Marker 320: rs320 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.109032 pvalue = 0.741249 df = 1 ***************************************** RCHI test RCHI statistic value = 0.159762 pvalue = 0.689375 df = 1 ***************************************** RW test RW statistic value = 0.310952 pvalue = 0.577097 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3317 sd = 0.0509 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 allele 2 : freq = 0.6683 sd = 0.0509 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3312 freq = 0.3125 freq = 0.0000 freq = 0.3172 allele 2 : freq = 0.6687 freq = 0.6875 freq = 0.0000 freq = 0.6828 ***************************************** **************************************** Analysis of Marker 321: rs321 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001038 pvalue = 0.974301 df = 1 ***************************************** RCHI test RCHI statistic value = 0.034063 pvalue = 0.853574 df = 1 ***************************************** RW test RW statistic value = 0.253118 pvalue = 0.614888 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2700 sd = 0.0480 freq = 0.2788 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 allele 2 : freq = 0.7300 sd = 0.0480 freq = 0.7212 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2750 freq = 0.2667 freq = 0.0000 freq = 0.2687 allele 2 : freq = 0.7250 freq = 0.7333 freq = 0.0000 freq = 0.7312 ***************************************** **************************************** Analysis of Marker 322: rs322 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.095715 pvalue = 0.295208 df = 1 ***************************************** RCHI test RCHI statistic value = 1.277347 pvalue = 0.258393 df = 1 ***************************************** RW test RW statistic value = 0.005578 pvalue = 0.940463 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6717 sd = 0.0507 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 allele 2 : freq = 0.3283 sd = 0.0507 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6625 freq = 0.7146 freq = 0.0000 freq = 0.7016 allele 2 : freq = 0.3375 freq = 0.2854 freq = 0.0000 freq = 0.2984 ***************************************** **************************************** Analysis of Marker 323: rs323 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.142551 pvalue = 0.705758 df = 1 ***************************************** RCHI test RCHI statistic value = 0.109916 pvalue = 0.740239 df = 1 ***************************************** RW test RW statistic value = 0.816783 pvalue = 0.366122 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4883 sd = 0.0540 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 allele 2 : freq = 0.5117 sd = 0.0540 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5062 freq = 0.4896 freq = 0.0000 freq = 0.4938 allele 2 : freq = 0.4938 freq = 0.5104 freq = 0.0000 freq = 0.5062 ***************************************** **************************************** Analysis of Marker 324: rs324 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.355794 pvalue = 0.550851 df = 1 ***************************************** RCHI test RCHI statistic value = 0.017608 pvalue = 0.894435 df = 1 ***************************************** RW test RW statistic value = 0.005340 pvalue = 0.941746 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7233 sd = 0.0483 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 allele 2 : freq = 0.2767 sd = 0.0483 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7063 freq = 0.7000 freq = 0.0000 freq = 0.7016 allele 2 : freq = 0.2938 freq = 0.3000 freq = 0.0000 freq = 0.2984 ***************************************** **************************************** Analysis of Marker 325: rs325 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.038433 pvalue = 0.844577 df = 1 ***************************************** RCHI test RCHI statistic value = 0.007097 pvalue = 0.932863 df = 1 ***************************************** RW test RW statistic value = 0.922247 pvalue = 0.336886 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4167 sd = 0.0533 freq = 0.4019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 allele 2 : freq = 0.5833 sd = 0.0533 freq = 0.5981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4000 freq = 0.4042 freq = 0.0000 freq = 0.4031 allele 2 : freq = 0.6000 freq = 0.5958 freq = 0.0000 freq = 0.5969 ***************************************** **************************************** Analysis of Marker 326: rs326 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.451614 pvalue = 0.228269 df = 1 ***************************************** RCHI test RCHI statistic value = 0.912635 pvalue = 0.339416 df = 1 ***************************************** RW test RW statistic value = 1.846073 pvalue = 0.174241 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4683 sd = 0.0539 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 allele 2 : freq = 0.5317 sd = 0.0539 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4813 freq = 0.5292 freq = 0.0000 freq = 0.5172 allele 2 : freq = 0.5188 freq = 0.4708 freq = 0.0000 freq = 0.4828 ***************************************** **************************************** Analysis of Marker 327: rs327 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.287027 pvalue = 0.13046 df = 1 ***************************************** RCHI test RCHI statistic value = 1.249745 pvalue = 0.263601 df = 1 ***************************************** RW test RW statistic value = 0.834924 pvalue = 0.360853 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8083 sd = 0.0425 freq = 0.8654 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 allele 2 : freq = 0.1917 sd = 0.0425 freq = 0.1346 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.8458 freq = 0.0000 freq = 0.8359 allele 2 : freq = 0.1938 freq = 0.1542 freq = 0.0000 freq = 0.1641 ***************************************** **************************************** Analysis of Marker 328: rs328 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.532790 pvalue = 0.215694 df = 1 ***************************************** RCHI test RCHI statistic value = 0.741638 pvalue = 0.389137 df = 1 ***************************************** RW test RW statistic value = 0.006248 pvalue = 0.936999 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3033 sd = 0.0497 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.6967 sd = 0.0497 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3000 freq = 0.2625 freq = 0.0000 freq = 0.2719 allele 2 : freq = 0.7000 freq = 0.7375 freq = 0.0000 freq = 0.7281 ***************************************** **************************************** Analysis of Marker 329: rs329 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.192577 pvalue = 0.27481 df = 1 ***************************************** RCHI test RCHI statistic value = 0.292501 pvalue = 0.588622 df = 1 ***************************************** RW test RW statistic value = 1.965973 pvalue = 0.160876 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3950 sd = 0.0528 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 allele 2 : freq = 0.6050 sd = 0.0528 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4000 freq = 0.4271 freq = 0.0000 freq = 0.4203 allele 2 : freq = 0.6000 freq = 0.5729 freq = 0.0000 freq = 0.5797 ***************************************** **************************************** Analysis of Marker 330: rs330 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.007071 pvalue = 0.932985 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.027756 pvalue = 0.867683 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0617 sd = 0.0260 freq = 0.0596 sd = 0.0180 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174 allele 2 : freq = 0.9383 sd = 0.0260 freq = 0.9404 sd = 0.0180 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0625 freq = 0.0625 freq = 0.0000 freq = 0.0625 allele 2 : freq = 0.9375 freq = 0.9375 freq = 0.0000 freq = 0.9375 ***************************************** **************************************** Analysis of Marker 331: rs331 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.034481 pvalue = 0.852686 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002353 pvalue = 0.961312 df = 1 ***************************************** RW test RW statistic value = 0.004110 pvalue = 0.948881 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2313 freq = 0.2333 freq = 0.0000 freq = 0.2328 allele 2 : freq = 0.7688 freq = 0.7667 freq = 0.0000 freq = 0.7672 ***************************************** **************************************** Analysis of Marker 332: rs332 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.789013 pvalue = 0.374399 df = 1 ***************************************** RCHI test RCHI statistic value = 1.994183 pvalue = 0.157904 df = 1 ***************************************** RW test RW statistic value = 0.499820 pvalue = 0.479579 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6083 sd = 0.0527 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.3917 sd = 0.0527 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.6687 freq = 0.0000 freq = 0.6516 allele 2 : freq = 0.4000 freq = 0.3312 freq = 0.0000 freq = 0.3484 ***************************************** **************************************** Analysis of Marker 333: rs333 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.682876 pvalue = 0.408598 df = 1 ***************************************** RCHI test RCHI statistic value = 0.139071 pvalue = 0.709206 df = 1 ***************************************** RW test RW statistic value = 4.050636 pvalue = 0.0441547 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5500 sd = 0.0537 freq = 0.4885 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.4500 sd = 0.0537 freq = 0.5115 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5375 freq = 0.5188 freq = 0.0000 freq = 0.5234 allele 2 : freq = 0.4625 freq = 0.4813 freq = 0.0000 freq = 0.4766 ***************************************** **************************************** Analysis of Marker 334: rs334 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.120003 pvalue = 0.145386 df = 1 ***************************************** RCHI test RCHI statistic value = 1.066607 pvalue = 0.301713 df = 1 ***************************************** RW test RW statistic value = 1.326443 pvalue = 0.249439 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7150 sd = 0.0488 freq = 0.6385 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340 allele 2 : freq = 0.2850 sd = 0.0488 freq = 0.3615 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7000 freq = 0.6500 freq = 0.0000 freq = 0.6625 allele 2 : freq = 0.3000 freq = 0.3500 freq = 0.0000 freq = 0.3375 ***************************************** **************************************** Analysis of Marker 335: rs335 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.466707 pvalue = 0.494506 df = 1 ***************************************** RCHI test RCHI statistic value = 0.386398 pvalue = 0.534199 df = 1 ***************************************** RW test RW statistic value = 0.000349 pvalue = 0.985103 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1812 freq = 0.1583 freq = 0.0000 freq = 0.1641 allele 2 : freq = 0.8187 freq = 0.8417 freq = 0.0000 freq = 0.8359 ***************************************** **************************************** Analysis of Marker 336: rs336 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.731663 pvalue = 0.392345 df = 1 ***************************************** RCHI test RCHI statistic value = 1.189094 pvalue = 0.275512 df = 1 ***************************************** RW test RW statistic value = 0.292103 pvalue = 0.588876 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0717 sd = 0.0279 freq = 0.0442 sd = 0.0156 freq = 0.0000 sd = 0.0000 freq = 0.0550 sd = 0.0161 allele 2 : freq = 0.9283 sd = 0.0279 freq = 0.9558 sd = 0.0156 freq = 0.0000 sd = 0.0000 freq = 0.9450 sd = 0.0161 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0688 freq = 0.0437 freq = 0.0000 freq = 0.0500 allele 2 : freq = 0.9313 freq = 0.9563 freq = 0.0000 freq = 0.9500 ***************************************** **************************************** Analysis of Marker 337: rs337 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.105994 pvalue = 0.744752 df = 1 ***************************************** RCHI test RCHI statistic value = 0.006873 pvalue = 0.933927 df = 1 ***************************************** RW test RW statistic value = 0.285342 pvalue = 0.593221 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5200 sd = 0.0540 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 allele 2 : freq = 0.4800 sd = 0.0540 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4938 freq = 0.4896 freq = 0.0000 freq = 0.4906 allele 2 : freq = 0.5062 freq = 0.5104 freq = 0.0000 freq = 0.5094 ***************************************** **************************************** Analysis of Marker 338: rs338 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.077293 pvalue = 0.781 df = 1 ***************************************** RCHI test RCHI statistic value = 0.042919 pvalue = 0.835878 df = 1 ***************************************** RW test RW statistic value = 0.637792 pvalue = 0.424512 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8733 sd = 0.0359 freq = 0.8942 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212 allele 2 : freq = 0.1267 sd = 0.0359 freq = 0.1058 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.8812 freq = 0.0000 freq = 0.8828 allele 2 : freq = 0.1125 freq = 0.1187 freq = 0.0000 freq = 0.1172 ***************************************** **************************************** Analysis of Marker 339: rs339 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001754 pvalue = 0.966598 df = 1 ***************************************** RCHI test RCHI statistic value = 0.069356 pvalue = 0.792277 df = 1 ***************************************** RW test RW statistic value = 0.017037 pvalue = 0.896149 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3217 sd = 0.0505 freq = 0.3462 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 allele 2 : freq = 0.6783 sd = 0.0505 freq = 0.6538 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3500 freq = 0.0000 freq = 0.3469 allele 2 : freq = 0.6625 freq = 0.6500 freq = 0.0000 freq = 0.6531 ***************************************** **************************************** Analysis of Marker 340: rs340 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.015218 pvalue = 0.313656 df = 1 ***************************************** RCHI test RCHI statistic value = 2.255923 pvalue = 0.133104 df = 1 ***************************************** RW test RW statistic value = 0.183040 pvalue = 0.668774 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2283 sd = 0.0453 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 allele 2 : freq = 0.7717 sd = 0.0453 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 freq = 0.1646 freq = 0.0000 freq = 0.1797 allele 2 : freq = 0.7750 freq = 0.8354 freq = 0.0000 freq = 0.8203 ***************************************** **************************************** Analysis of Marker 341: rs341 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.089737 pvalue = 0.764512 df = 1 ***************************************** RCHI test RCHI statistic value = 0.192277 pvalue = 0.661029 df = 1 ***************************************** RW test RW statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8683 sd = 0.0365 freq = 0.8827 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 allele 2 : freq = 0.1317 sd = 0.0365 freq = 0.1173 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8688 freq = 0.8833 freq = 0.0000 freq = 0.8797 allele 2 : freq = 0.1313 freq = 0.1167 freq = 0.0000 freq = 0.1203 ***************************************** **************************************** Analysis of Marker 342: rs342 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.534020 pvalue = 0.464922 df = 1 ***************************************** RCHI test RCHI statistic value = 0.303517 pvalue = 0.581686 df = 1 ***************************************** RW test RW statistic value = 1.044909 pvalue = 0.306683 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3683 sd = 0.0521 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6317 sd = 0.0521 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.3896 freq = 0.0000 freq = 0.3828 allele 2 : freq = 0.6375 freq = 0.6104 freq = 0.0000 freq = 0.6172 ***************************************** **************************************** Analysis of Marker 343: rs343 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 6.751576 pvalue = 0.00936649 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 6.141648 pvalue = 0.0132034 df = 1 ***************************************** RW test RW statistic value = 2.732041 pvalue = 0.0983535 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2033 sd = 0.0435 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 allele 2 : freq = 0.7967 sd = 0.0435 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.3000 freq = 0.0000 freq = 0.2719 allele 2 : freq = 0.8125 freq = 0.7000 freq = 0.0000 freq = 0.7281 ***************************************** **************************************** Analysis of Marker 344: rs344 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.107393 pvalue = 0.743132 df = 1 ***************************************** RCHI test RCHI statistic value = 0.770104 pvalue = 0.380185 df = 1 ***************************************** RW test RW statistic value = 0.320491 pvalue = 0.571313 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.5923 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.4077 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5625 freq = 0.6062 freq = 0.0000 freq = 0.5953 allele 2 : freq = 0.4375 freq = 0.3937 freq = 0.0000 freq = 0.4047 ***************************************** **************************************** Analysis of Marker 345: rs345 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.010749 pvalue = 0.917424 df = 1 ***************************************** RCHI test RCHI statistic value = 0.917337 pvalue = 0.338175 df = 1 ***************************************** RW test RW statistic value = 0.681573 pvalue = 0.409046 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4517 sd = 0.0538 freq = 0.4731 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.5483 sd = 0.0538 freq = 0.5269 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4625 freq = 0.5104 freq = 0.0000 freq = 0.4984 allele 2 : freq = 0.5375 freq = 0.4896 freq = 0.0000 freq = 0.5016 ***************************************** **************************************** Analysis of Marker 346: rs346 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.822205 pvalue = 0.364536 df = 1 ***************************************** RCHI test RCHI statistic value = 0.556730 pvalue = 0.455581 df = 1 ***************************************** RW test RW statistic value = 0.945699 pvalue = 0.330817 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5383 sd = 0.0538 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 allele 2 : freq = 0.4617 sd = 0.0538 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.4875 freq = 0.0000 freq = 0.4969 allele 2 : freq = 0.4750 freq = 0.5125 freq = 0.0000 freq = 0.5031 ***************************************** **************************************** Analysis of Marker 347: rs347 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.418562 pvalue = 0.517656 df = 1 ***************************************** RCHI test RCHI statistic value = 0.654364 pvalue = 0.418557 df = 1 ***************************************** RW test RW statistic value = 0.810605 pvalue = 0.367941 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6333 sd = 0.0521 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 allele 2 : freq = 0.3667 sd = 0.0521 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6375 freq = 0.5979 freq = 0.0000 freq = 0.6078 allele 2 : freq = 0.3625 freq = 0.4021 freq = 0.0000 freq = 0.3922 ***************************************** **************************************** Analysis of Marker 348: rs348 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.276512 pvalue = 0.598997 df = 1 ***************************************** RCHI test RCHI statistic value = 0.045102 pvalue = 0.831817 df = 1 ***************************************** RW test RW statistic value = 0.381326 pvalue = 0.536895 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.3962 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.6038 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 freq = 0.4354 freq = 0.0000 freq = 0.4328 allele 2 : freq = 0.5750 freq = 0.5646 freq = 0.0000 freq = 0.5672 ***************************************** **************************************** Analysis of Marker 349: rs349 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.064575 pvalue = 0.799405 df = 1 ***************************************** RCHI test RCHI statistic value = 0.194671 pvalue = 0.659057 df = 1 ***************************************** RW test RW statistic value = 0.001328 pvalue = 0.970926 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8267 sd = 0.0409 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.1733 sd = 0.0409 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.8417 freq = 0.0000 freq = 0.8375 allele 2 : freq = 0.1750 freq = 0.1583 freq = 0.0000 freq = 0.1625 ***************************************** **************************************** Analysis of Marker 350: rs350 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.682755 pvalue = 0.40864 df = 1 ***************************************** RCHI test RCHI statistic value = 0.568885 pvalue = 0.450702 df = 1 ***************************************** RW test RW statistic value = 1.800823 pvalue = 0.179613 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8950 sd = 0.0331 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1050 sd = 0.0331 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8750 freq = 0.8479 freq = 0.0000 freq = 0.8547 allele 2 : freq = 0.1250 freq = 0.1521 freq = 0.0000 freq = 0.1453 ***************************************** **************************************** Analysis of Marker 351: rs351 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.271386 pvalue = 0.602403 df = 1 ***************************************** RCHI test RCHI statistic value = 0.397658 pvalue = 0.528301 df = 1 ***************************************** RW test RW statistic value = 0.749114 pvalue = 0.386757 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2633 sd = 0.0476 freq = 0.2308 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 allele 2 : freq = 0.7367 sd = 0.0476 freq = 0.7692 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2562 freq = 0.2292 freq = 0.0000 freq = 0.2359 allele 2 : freq = 0.7438 freq = 0.7708 freq = 0.0000 freq = 0.7641 ***************************************** **************************************** Analysis of Marker 352: rs352 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.165648 pvalue = 0.684009 df = 1 ***************************************** RCHI test RCHI statistic value = 0.074292 pvalue = 0.785188 df = 1 ***************************************** RW test RW statistic value = 0.164249 pvalue = 0.685275 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6950 sd = 0.0497 freq = 0.7038 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 allele 2 : freq = 0.3050 sd = 0.0497 freq = 0.2962 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.7000 freq = 0.0000 freq = 0.6969 allele 2 : freq = 0.3125 freq = 0.3000 freq = 0.0000 freq = 0.3031 ***************************************** **************************************** Analysis of Marker 353: rs353 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.040730 pvalue = 0.84006 df = 1 ***************************************** RCHI test RCHI statistic value = 0.047482 pvalue = 0.827504 df = 1 ***************************************** RW test RW statistic value = 0.029860 pvalue = 0.862809 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6617 sd = 0.0511 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 allele 2 : freq = 0.3383 sd = 0.0511 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6625 freq = 0.6521 freq = 0.0000 freq = 0.6547 allele 2 : freq = 0.3375 freq = 0.3479 freq = 0.0000 freq = 0.3453 ***************************************** **************************************** Analysis of Marker 354: rs354 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.311645 pvalue = 0.252097 df = 1 ***************************************** RCHI test RCHI statistic value = 0.962704 pvalue = 0.326507 df = 1 ***************************************** RW test RW statistic value = 0.808060 pvalue = 0.368694 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7433 sd = 0.0472 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.2567 sd = 0.0472 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7312 freq = 0.6854 freq = 0.0000 freq = 0.6969 allele 2 : freq = 0.2687 freq = 0.3146 freq = 0.0000 freq = 0.3031 ***************************************** **************************************** Analysis of Marker 355: rs355 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.516246 pvalue = 0.472448 df = 1 ***************************************** RCHI test RCHI statistic value = 0.063873 pvalue = 0.800477 df = 1 ***************************************** RW test RW statistic value = 1.604102 pvalue = 0.205323 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6033 sd = 0.0528 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.3967 sd = 0.0528 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6375 freq = 0.6500 freq = 0.0000 freq = 0.6469 allele 2 : freq = 0.3625 freq = 0.3500 freq = 0.0000 freq = 0.3531 ***************************************** **************************************** Analysis of Marker 356: rs356 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.569419 pvalue = 0.45049 df = 1 ***************************************** RCHI test RCHI statistic value = 1.521863 pvalue = 0.217338 df = 1 ***************************************** RW test RW statistic value = 0.000848 pvalue = 0.976772 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 freq = 0.7083 freq = 0.0000 freq = 0.6937 allele 2 : freq = 0.3500 freq = 0.2917 freq = 0.0000 freq = 0.3063 ***************************************** **************************************** Analysis of Marker 357: rs357 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001435 pvalue = 0.969781 df = 1 ***************************************** RCHI test RCHI statistic value = 0.007956 pvalue = 0.928925 df = 1 ***************************************** RW test RW statistic value = 0.055593 pvalue = 0.813601 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6783 sd = 0.0505 freq = 0.6942 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.3217 sd = 0.0505 freq = 0.3058 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6813 freq = 0.6771 freq = 0.0000 freq = 0.6781 allele 2 : freq = 0.3187 freq = 0.3229 freq = 0.0000 freq = 0.3219 ***************************************** **************************************** Analysis of Marker 358: rs358 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.295178 pvalue = 0.255096 df = 1 ***************************************** RCHI test RCHI statistic value = 1.118104 pvalue = 0.290327 df = 1 ***************************************** RW test RW statistic value = 0.306030 pvalue = 0.580127 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6200 sd = 0.0524 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 allele 2 : freq = 0.3800 sd = 0.0524 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6250 freq = 0.6750 freq = 0.0000 freq = 0.6625 allele 2 : freq = 0.3750 freq = 0.3250 freq = 0.0000 freq = 0.3375 ***************************************** **************************************** Analysis of Marker 359: rs359 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.021057 pvalue = 0.0821899 df = 1 ***************************************** RCHI test RCHI statistic value = 3.425668 pvalue = 0.0641903 df = 1 ***************************************** RW test RW statistic value = 1.354761 pvalue = 0.244448 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 sd = 0.0410 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8250 sd = 0.0410 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1229 freq = 0.0000 freq = 0.1391 allele 2 : freq = 0.8125 freq = 0.8771 freq = 0.0000 freq = 0.8609 ***************************************** **************************************** Analysis of Marker 360: rs360 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.342455 pvalue = 0.558416 df = 1 ***************************************** RCHI test RCHI statistic value = 0.012773 pvalue = 0.910015 df = 1 ***************************************** RW test RW statistic value = 0.068335 pvalue = 0.793777 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1783 sd = 0.0413 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 allele 2 : freq = 0.8217 sd = 0.0413 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1917 freq = 0.0000 freq = 0.1906 allele 2 : freq = 0.8125 freq = 0.8083 freq = 0.0000 freq = 0.8094 ***************************************** **************************************** Analysis of Marker 361: rs361 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.581854 pvalue = 0.445586 df = 1 ***************************************** RCHI test RCHI statistic value = 1.054774 pvalue = 0.30441 df = 1 ***************************************** RW test RW statistic value = 4.803273 pvalue = 0.0284057 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3783 sd = 0.0524 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 allele 2 : freq = 0.6217 sd = 0.0524 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4000 freq = 0.3500 freq = 0.0000 freq = 0.3625 allele 2 : freq = 0.6000 freq = 0.6500 freq = 0.0000 freq = 0.6375 ***************************************** **************************************** Analysis of Marker 362: rs362 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.989740 pvalue = 0.319806 df = 1 ***************************************** RCHI test RCHI statistic value = 1.241626 pvalue = 0.265158 df = 1 ***************************************** RW test RW statistic value = 0.072901 pvalue = 0.78716 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8917 sd = 0.0336 freq = 0.9115 sd = 0.0216 freq = 0.0000 sd = 0.0000 freq = 0.9150 sd = 0.0197 allele 2 : freq = 0.1083 sd = 0.0336 freq = 0.0885 sd = 0.0216 freq = 0.0000 sd = 0.0000 freq = 0.0850 sd = 0.0197 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8938 freq = 0.9250 freq = 0.0000 freq = 0.9172 allele 2 : freq = 0.1062 freq = 0.0750 freq = 0.0000 freq = 0.0828 ***************************************** **************************************** Analysis of Marker 363: rs363 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.074416 pvalue = 0.785012 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.152362 pvalue = 0.696288 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9383 sd = 0.0260 freq = 0.9423 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.9450 sd = 0.0161 allele 2 : freq = 0.0617 sd = 0.0260 freq = 0.0577 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.0550 sd = 0.0161 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9375 freq = 0.9375 freq = 0.0000 freq = 0.9375 allele 2 : freq = 0.0625 freq = 0.0625 freq = 0.0000 freq = 0.0625 ***************************************** **************************************** Analysis of Marker 364: rs364 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.563048 pvalue = 0.453035 df = 1 ***************************************** RCHI test RCHI statistic value = 0.070431 pvalue = 0.79071 df = 1 ***************************************** RW test RW statistic value = 0.768954 pvalue = 0.380541 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3533 sd = 0.0516 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 allele 2 : freq = 0.6467 sd = 0.0516 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.3500 freq = 0.0000 freq = 0.3531 allele 2 : freq = 0.6375 freq = 0.6500 freq = 0.0000 freq = 0.6469 ***************************************** **************************************** Analysis of Marker 365: rs365 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.010104 pvalue = 0.919934 df = 1 ***************************************** RCHI test RCHI statistic value = 0.250825 pvalue = 0.616495 df = 1 ***************************************** RW test RW statistic value = 0.006846 pvalue = 0.934057 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5633 sd = 0.0536 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 allele 2 : freq = 0.4367 sd = 0.0536 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5563 freq = 0.5312 freq = 0.0000 freq = 0.5375 allele 2 : freq = 0.4437 freq = 0.4688 freq = 0.0000 freq = 0.4625 ***************************************** **************************************** Analysis of Marker 366: rs366 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.894811 pvalue = 0.344177 df = 1 ***************************************** RCHI test RCHI statistic value = 1.126195 pvalue = 0.288588 df = 1 ***************************************** RW test RW statistic value = 0.781899 pvalue = 0.376561 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3017 sd = 0.0496 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 allele 2 : freq = 0.6983 sd = 0.0496 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3125 freq = 0.2646 freq = 0.0000 freq = 0.2766 allele 2 : freq = 0.6875 freq = 0.7354 freq = 0.0000 freq = 0.7234 ***************************************** **************************************** Analysis of Marker 367: rs367 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.360003 pvalue = 0.548504 df = 1 ***************************************** RCHI test RCHI statistic value = 0.061958 pvalue = 0.803427 df = 1 ***************************************** RW test RW statistic value = 0.018790 pvalue = 0.89097 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5683 sd = 0.0535 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 allele 2 : freq = 0.4317 sd = 0.0535 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5563 freq = 0.5437 freq = 0.0000 freq = 0.5469 allele 2 : freq = 0.4437 freq = 0.4562 freq = 0.0000 freq = 0.4531 ***************************************** **************************************** Analysis of Marker 368: rs368 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.020196 pvalue = 0.886991 df = 1 ***************************************** RCHI test RCHI statistic value = 0.250241 pvalue = 0.616906 df = 1 ***************************************** RW test RW statistic value = 1.436054 pvalue = 0.230779 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5600 sd = 0.0536 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 allele 2 : freq = 0.4400 sd = 0.0536 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5563 freq = 0.5813 freq = 0.0000 freq = 0.5750 allele 2 : freq = 0.4437 freq = 0.4188 freq = 0.0000 freq = 0.4250 ***************************************** **************************************** Analysis of Marker 369: rs369 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.123195 pvalue = 0.725595 df = 1 ***************************************** RCHI test RCHI statistic value = 0.158470 pvalue = 0.690569 df = 1 ***************************************** RW test RW statistic value = 0.085439 pvalue = 0.770057 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3617 sd = 0.0519 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 allele 2 : freq = 0.6383 sd = 0.0519 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3187 freq = 0.0000 freq = 0.3234 allele 2 : freq = 0.6625 freq = 0.6813 freq = 0.0000 freq = 0.6766 ***************************************** **************************************** Analysis of Marker 370: rs370 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.275883 pvalue = 0.599412 df = 1 ***************************************** RCHI test RCHI statistic value = 0.043195 pvalue = 0.835358 df = 1 ***************************************** RW test RW statistic value = 0.068099 pvalue = 0.794125 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5283 sd = 0.0539 freq = 0.5288 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 allele 2 : freq = 0.4717 sd = 0.0539 freq = 0.4712 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5125 freq = 0.5229 freq = 0.0000 freq = 0.5203 allele 2 : freq = 0.4875 freq = 0.4771 freq = 0.0000 freq = 0.4797 ***************************************** **************************************** Analysis of Marker 371: rs371 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.426061 pvalue = 0.119332 df = 1 ***************************************** RCHI test RCHI statistic value = 1.945750 pvalue = 0.163046 df = 1 ***************************************** RW test RW statistic value = 3.565398 pvalue = 0.0589956 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2417 sd = 0.0462 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 allele 2 : freq = 0.7583 sd = 0.0462 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.3083 freq = 0.0000 freq = 0.2922 allele 2 : freq = 0.7562 freq = 0.6917 freq = 0.0000 freq = 0.7078 ***************************************** **************************************** Analysis of Marker 372: rs372 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.118533 pvalue = 0.290235 df = 1 ***************************************** RCHI test RCHI statistic value = 0.909619 pvalue = 0.340216 df = 1 ***************************************** RW test RW statistic value = 0.868077 pvalue = 0.351488 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.4771 freq = 0.0000 freq = 0.4891 allele 2 : freq = 0.4750 freq = 0.5229 freq = 0.0000 freq = 0.5109 ***************************************** **************************************** Analysis of Marker 373: rs373 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.489858 pvalue = 0.0340965 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 4.465726 pvalue = 0.0345814 df = 1 ***************************************** RW test RW statistic value = 3.023403 pvalue = 0.0820711 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5683 sd = 0.0535 freq = 0.4731 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.4317 sd = 0.0535 freq = 0.5269 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5813 freq = 0.4750 freq = 0.0000 freq = 0.5016 allele 2 : freq = 0.4188 freq = 0.5250 freq = 0.0000 freq = 0.4984 ***************************************** **************************************** Analysis of Marker 374: rs374 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.181143 pvalue = 0.670392 df = 1 ***************************************** RCHI test RCHI statistic value = 0.265427 pvalue = 0.606416 df = 1 ***************************************** RW test RW statistic value = 0.489779 pvalue = 0.484026 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1517 sd = 0.0387 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 allele 2 : freq = 0.8483 sd = 0.0387 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1437 freq = 0.1625 freq = 0.0000 freq = 0.1578 allele 2 : freq = 0.8562 freq = 0.8375 freq = 0.0000 freq = 0.8422 ***************************************** **************************************** Analysis of Marker 375: rs375 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 8.807605 pvalue = 0.00299978 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 7.935256 pvalue = 0.00484808 df = 1 ***************************************** RW test RW statistic value = 5.284271 pvalue = 0.0215189 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5117 sd = 0.0540 freq = 0.3596 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 allele 2 : freq = 0.4883 sd = 0.0540 freq = 0.6404 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.3625 freq = 0.0000 freq = 0.3969 allele 2 : freq = 0.5000 freq = 0.6375 freq = 0.0000 freq = 0.6031 ***************************************** **************************************** Analysis of Marker 376: rs376 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.693880 pvalue = 0.100734 df = 1 ***************************************** RCHI test RCHI statistic value = 1.355333 pvalue = 0.244348 df = 1 ***************************************** RW test RW statistic value = 0.113292 pvalue = 0.736427 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1917 sd = 0.0425 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 allele 2 : freq = 0.8083 sd = 0.0425 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.2250 freq = 0.0000 freq = 0.2125 allele 2 : freq = 0.8250 freq = 0.7750 freq = 0.0000 freq = 0.7875 ***************************************** **************************************** Analysis of Marker 377: rs377 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.114368 pvalue = 0.291134 df = 1 ***************************************** RCHI test RCHI statistic value = 0.556775 pvalue = 0.455563 df = 1 ***************************************** RW test RW statistic value = 0.916234 pvalue = 0.338466 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3483 sd = 0.0515 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 allele 2 : freq = 0.6517 sd = 0.0515 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3812 freq = 0.3458 freq = 0.0000 freq = 0.3547 allele 2 : freq = 0.6188 freq = 0.6542 freq = 0.0000 freq = 0.6453 ***************************************** **************************************** Analysis of Marker 378: rs378 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.304930 pvalue = 0.580808 df = 1 ***************************************** RCHI test RCHI statistic value = 0.919249 pvalue = 0.337672 df = 1 ***************************************** RW test RW statistic value = 0.162570 pvalue = 0.686801 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3567 sd = 0.0517 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 allele 2 : freq = 0.6433 sd = 0.0517 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3312 freq = 0.3771 freq = 0.0000 freq = 0.3656 allele 2 : freq = 0.6687 freq = 0.6229 freq = 0.0000 freq = 0.6344 ***************************************** **************************************** Analysis of Marker 379: rs379 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.134110 pvalue = 0.714208 df = 1 ***************************************** RCHI test RCHI statistic value = 0.225889 pvalue = 0.634589 df = 1 ***************************************** RW test RW statistic value = 1.059865 pvalue = 0.303246 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.8096 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.1904 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 freq = 0.8187 freq = 0.0000 freq = 0.8141 allele 2 : freq = 0.2000 freq = 0.1812 freq = 0.0000 freq = 0.1859 ***************************************** **************************************** Analysis of Marker 380: rs380 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.787906 pvalue = 0.181181 df = 1 ***************************************** RCHI test RCHI statistic value = 1.870294 pvalue = 0.171441 df = 1 ***************************************** RW test RW statistic value = 7.057036 pvalue = 0.00789545 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.4692 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.5308 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5437 freq = 0.4750 freq = 0.0000 freq = 0.4922 allele 2 : freq = 0.4562 freq = 0.5250 freq = 0.0000 freq = 0.5078 ***************************************** **************************************** Analysis of Marker 381: rs381 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000002 pvalue = 0.998833 df = 1 ***************************************** RCHI test RCHI statistic value = 1.168002 pvalue = 0.279812 df = 1 ***************************************** RW test RW statistic value = 6.044211 pvalue = 0.013952 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5188 freq = 0.4646 freq = 0.0000 freq = 0.4781 allele 2 : freq = 0.4813 freq = 0.5354 freq = 0.0000 freq = 0.5219 ***************************************** **************************************** Analysis of Marker 382: rs382 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.523206 pvalue = 0.469477 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.578275 pvalue = 0.446989 df = 1 The p-value might not be exact because of the small number of allele 1 in cases ***************************************** RW test RW statistic value = 0.221960 pvalue = 0.637551 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0317 sd = 0.0189 freq = 0.0481 sd = 0.0162 freq = 0.0000 sd = 0.0000 freq = 0.0500 sd = 0.0154 allele 2 : freq = 0.9683 sd = 0.0189 freq = 0.9519 sd = 0.0162 freq = 0.0000 sd = 0.0000 freq = 0.9500 sd = 0.0154 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0375 freq = 0.0542 freq = 0.0000 freq = 0.0500 allele 2 : freq = 0.9625 freq = 0.9458 freq = 0.0000 freq = 0.9500 ***************************************** **************************************** Analysis of Marker 383: rs383 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.661516 pvalue = 0.197399 df = 1 ***************************************** RCHI test RCHI statistic value = 1.663837 pvalue = 0.197086 df = 1 ***************************************** RW test RW statistic value = 0.967394 pvalue = 0.325331 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7367 sd = 0.0476 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 allele 2 : freq = 0.2633 sd = 0.0476 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7312 freq = 0.7854 freq = 0.0000 freq = 0.7719 allele 2 : freq = 0.2687 freq = 0.2146 freq = 0.0000 freq = 0.2281 ***************************************** **************************************** Analysis of Marker 384: rs384 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.965986 pvalue = 0.325683 df = 1 ***************************************** RCHI test RCHI statistic value = 1.546342 pvalue = 0.213676 df = 1 ***************************************** RW test RW statistic value = 0.604892 pvalue = 0.436717 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7100 sd = 0.0490 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 allele 2 : freq = 0.2900 sd = 0.0490 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7125 freq = 0.6542 freq = 0.0000 freq = 0.6687 allele 2 : freq = 0.2875 freq = 0.3458 freq = 0.0000 freq = 0.3312 ***************************************** **************************************** Analysis of Marker 385: rs385 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.382460 pvalue = 0.536289 df = 1 ***************************************** RCHI test RCHI statistic value = 0.254296 pvalue = 0.614066 df = 1 ***************************************** RW test RW statistic value = 0.159919 pvalue = 0.689231 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2317 sd = 0.0456 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 allele 2 : freq = 0.7683 sd = 0.0456 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.2167 freq = 0.0000 freq = 0.2219 allele 2 : freq = 0.7625 freq = 0.7833 freq = 0.0000 freq = 0.7781 ***************************************** **************************************** Analysis of Marker 386: rs386 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.606054 pvalue = 0.436277 df = 1 ***************************************** RCHI test RCHI statistic value = 0.009281 pvalue = 0.923252 df = 1 ***************************************** RW test RW statistic value = 0.184671 pvalue = 0.667389 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7733 sd = 0.0452 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.2267 sd = 0.0452 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7937 freq = 0.7896 freq = 0.0000 freq = 0.7906 allele 2 : freq = 0.2062 freq = 0.2104 freq = 0.0000 freq = 0.2094 ***************************************** **************************************** Analysis of Marker 387: rs387 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.042954 pvalue = 0.307135 df = 1 ***************************************** RCHI test RCHI statistic value = 0.233669 pvalue = 0.628816 df = 1 ***************************************** RW test RW statistic value = 0.117145 pvalue = 0.732151 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8617 sd = 0.0373 freq = 0.8904 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212 allele 2 : freq = 0.1383 sd = 0.0373 freq = 0.1096 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8688 freq = 0.8833 freq = 0.0000 freq = 0.8797 allele 2 : freq = 0.1313 freq = 0.1167 freq = 0.0000 freq = 0.1203 ***************************************** **************************************** Analysis of Marker 388: rs388 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.160605 pvalue = 0.28134 df = 1 ***************************************** RCHI test RCHI statistic value = 0.579876 pvalue = 0.446361 df = 1 ***************************************** RW test RW statistic value = 0.000219 pvalue = 0.988191 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6600 sd = 0.0512 freq = 0.6827 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327 allele 2 : freq = 0.3400 sd = 0.0512 freq = 0.3173 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6438 freq = 0.6792 freq = 0.0000 freq = 0.6703 allele 2 : freq = 0.3563 freq = 0.3208 freq = 0.0000 freq = 0.3297 ***************************************** **************************************** Analysis of Marker 389: rs389 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.160064 pvalue = 0.281452 df = 1 ***************************************** RCHI test RCHI statistic value = 0.914465 pvalue = 0.338933 df = 1 ***************************************** RW test RW statistic value = 0.454382 pvalue = 0.500261 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8750 sd = 0.0357 freq = 0.8808 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.8800 sd = 0.0230 allele 2 : freq = 0.1250 sd = 0.0357 freq = 0.1192 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.1200 sd = 0.0230 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8500 freq = 0.8812 freq = 0.0000 freq = 0.8734 allele 2 : freq = 0.1500 freq = 0.1187 freq = 0.0000 freq = 0.1266 ***************************************** **************************************** Analysis of Marker 390: rs390 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.248105 pvalue = 0.618413 df = 1 ***************************************** RCHI test RCHI statistic value = 0.112069 pvalue = 0.737801 df = 1 ***************************************** RW test RW statistic value = 0.055251 pvalue = 0.814166 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6033 sd = 0.0528 freq = 0.5750 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 allele 2 : freq = 0.3967 sd = 0.0528 freq = 0.4250 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6062 freq = 0.6229 freq = 0.0000 freq = 0.6188 allele 2 : freq = 0.3937 freq = 0.3771 freq = 0.0000 freq = 0.3812 ***************************************** **************************************** Analysis of Marker 391: rs391 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.072785 pvalue = 0.787325 df = 1 ***************************************** RCHI test RCHI statistic value = 0.021811 pvalue = 0.882591 df = 1 ***************************************** RW test RW statistic value = 1.017068 pvalue = 0.313216 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1867 sd = 0.0421 freq = 0.2346 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 allele 2 : freq = 0.8133 sd = 0.0421 freq = 0.7654 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2188 freq = 0.2250 freq = 0.0000 freq = 0.2234 allele 2 : freq = 0.7812 freq = 0.7750 freq = 0.0000 freq = 0.7766 ***************************************** **************************************** Analysis of Marker 392: rs392 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.836821 pvalue = 0.360308 df = 1 ***************************************** RCHI test RCHI statistic value = 0.018760 pvalue = 0.891057 df = 1 ***************************************** RW test RW statistic value = 0.153842 pvalue = 0.69489 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7433 sd = 0.0472 freq = 0.7154 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321 allele 2 : freq = 0.2567 sd = 0.0472 freq = 0.2846 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7688 freq = 0.0000 freq = 0.7672 allele 2 : freq = 0.2375 freq = 0.2313 freq = 0.0000 freq = 0.2328 ***************************************** **************************************** Analysis of Marker 393: rs393 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.703818 pvalue = 0.401504 df = 1 ***************************************** RCHI test RCHI statistic value = 0.440591 pvalue = 0.506837 df = 1 ***************************************** RW test RW statistic value = 0.568405 pvalue = 0.450894 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4967 sd = 0.0540 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 allele 2 : freq = 0.5033 sd = 0.0540 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5125 freq = 0.4792 freq = 0.0000 freq = 0.4875 allele 2 : freq = 0.4875 freq = 0.5208 freq = 0.0000 freq = 0.5125 ***************************************** **************************************** Analysis of Marker 394: rs394 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.366305 pvalue = 0.545025 df = 1 ***************************************** RCHI test RCHI statistic value = 0.033078 pvalue = 0.855682 df = 1 ***************************************** RW test RW statistic value = 0.006420 pvalue = 0.936136 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8900 sd = 0.0338 freq = 0.8750 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 allele 2 : freq = 0.1100 sd = 0.0338 freq = 0.1250 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.8812 freq = 0.0000 freq = 0.8828 allele 2 : freq = 0.1125 freq = 0.1187 freq = 0.0000 freq = 0.1172 ***************************************** **************************************** Analysis of Marker 395: rs395 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.293295 pvalue = 0.588117 df = 1 ***************************************** RCHI test RCHI statistic value = 0.429761 pvalue = 0.512106 df = 1 ***************************************** RW test RW statistic value = 0.722133 pvalue = 0.395445 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7688 freq = 0.7958 freq = 0.0000 freq = 0.7891 allele 2 : freq = 0.2313 freq = 0.2042 freq = 0.0000 freq = 0.2109 ***************************************** **************************************** Analysis of Marker 396: rs396 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.177202 pvalue = 0.673789 df = 1 ***************************************** RCHI test RCHI statistic value = 0.013108 pvalue = 0.908851 df = 1 ***************************************** RW test RW statistic value = 0.516611 pvalue = 0.472291 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 sd = 0.0410 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 allele 2 : freq = 0.8250 sd = 0.0410 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.1792 freq = 0.0000 freq = 0.1781 allele 2 : freq = 0.8250 freq = 0.8208 freq = 0.0000 freq = 0.8219 ***************************************** **************************************** Analysis of Marker 397: rs397 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.752273 pvalue = 0.385758 df = 1 ***************************************** RCHI test RCHI statistic value = 0.259786 pvalue = 0.610267 df = 1 ***************************************** RW test RW statistic value = 0.003151 pvalue = 0.955232 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5767 sd = 0.0534 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 allele 2 : freq = 0.4233 sd = 0.0534 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5687 freq = 0.5938 freq = 0.0000 freq = 0.5875 allele 2 : freq = 0.4313 freq = 0.4062 freq = 0.0000 freq = 0.4125 ***************************************** **************************************** Analysis of Marker 398: rs398 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.893661 pvalue = 0.344487 df = 1 ***************************************** RCHI test RCHI statistic value = 1.252642 pvalue = 0.263049 df = 1 ***************************************** RW test RW statistic value = 3.624648 pvalue = 0.0569296 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4400 sd = 0.0536 freq = 0.5000 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 allele 2 : freq = 0.5600 sd = 0.0536 freq = 0.5000 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.5062 freq = 0.0000 freq = 0.4922 allele 2 : freq = 0.5500 freq = 0.4938 freq = 0.0000 freq = 0.5078 ***************************************** **************************************** Analysis of Marker 399: rs399 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.275078 pvalue = 0.131468 df = 1 ***************************************** RCHI test RCHI statistic value = 1.138763 pvalue = 0.285914 df = 1 ***************************************** RW test RW statistic value = 0.052881 pvalue = 0.818124 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 sd = 0.0506 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316 allele 2 : freq = 0.3250 sd = 0.0506 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6625 freq = 0.7104 freq = 0.0000 freq = 0.6984 allele 2 : freq = 0.3375 freq = 0.2896 freq = 0.0000 freq = 0.3016 ***************************************** **************************************** Analysis of Marker 400: rs400 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.239150 pvalue = 0.624821 df = 1 ***************************************** RCHI test RCHI statistic value = 0.023701 pvalue = 0.877648 df = 1 ***************************************** RW test RW statistic value = 0.014088 pvalue = 0.905517 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7783 sd = 0.0449 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 allele 2 : freq = 0.2217 sd = 0.0449 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7688 freq = 0.7625 freq = 0.0000 freq = 0.7641 allele 2 : freq = 0.2313 freq = 0.2375 freq = 0.0000 freq = 0.2359 ***************************************** **************************************** Analysis of Marker 401: rs401 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 6.032616 pvalue = 0.0140439 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 3.238076 pvalue = 0.0719451 df = 1 ***************************************** RW test RW statistic value = 0.781899 pvalue = 0.376561 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6283 sd = 0.0522 freq = 0.7269 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.3717 sd = 0.0522 freq = 0.2731 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6188 freq = 0.7000 freq = 0.0000 freq = 0.6797 allele 2 : freq = 0.3812 freq = 0.3000 freq = 0.0000 freq = 0.3203 ***************************************** **************************************** Analysis of Marker 402: rs402 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.125227 pvalue = 0.288796 df = 1 ***************************************** RCHI test RCHI statistic value = 0.803363 pvalue = 0.37009 df = 1 ***************************************** RW test RW statistic value = 3.518140 pvalue = 0.0607005 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5283 sd = 0.0539 freq = 0.6250 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 allele 2 : freq = 0.4717 sd = 0.0539 freq = 0.3750 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.6188 freq = 0.0000 freq = 0.6078 allele 2 : freq = 0.4250 freq = 0.3812 freq = 0.0000 freq = 0.3922 ***************************************** **************************************** Analysis of Marker 403: rs403 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.088036 pvalue = 0.76669 df = 1 ***************************************** RCHI test RCHI statistic value = 0.022152 pvalue = 0.881684 df = 1 ***************************************** RW test RW statistic value = 0.107488 pvalue = 0.743022 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7833 sd = 0.0445 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 allele 2 : freq = 0.2167 sd = 0.0445 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7875 freq = 0.7812 freq = 0.0000 freq = 0.7828 allele 2 : freq = 0.2125 freq = 0.2188 freq = 0.0000 freq = 0.2172 ***************************************** **************************************** Analysis of Marker 404: rs404 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.524487 pvalue = 0.468934 df = 1 ***************************************** RCHI test RCHI statistic value = 0.061902 pvalue = 0.803514 df = 1 ***************************************** RW test RW statistic value = 0.099311 pvalue = 0.752658 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5400 sd = 0.0538 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.4600 sd = 0.0538 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5188 freq = 0.5062 freq = 0.0000 freq = 0.5094 allele 2 : freq = 0.4813 freq = 0.4938 freq = 0.0000 freq = 0.4906 ***************************************** **************************************** Analysis of Marker 405: rs405 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.939561 pvalue = 0.332391 df = 1 ***************************************** RCHI test RCHI statistic value = 0.650999 pvalue = 0.419756 df = 1 ***************************************** RW test RW statistic value = 3.298603 pvalue = 0.0693388 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7500 freq = 0.7833 freq = 0.0000 freq = 0.7750 allele 2 : freq = 0.2500 freq = 0.2167 freq = 0.0000 freq = 0.2250 ***************************************** **************************************** Analysis of Marker 406: rs406 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.401856 pvalue = 0.121191 df = 1 ***************************************** RCHI test RCHI statistic value = 3.305326 pvalue = 0.0690557 df = 1 ***************************************** RW test RW statistic value = 2.499101 pvalue = 0.113911 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6967 sd = 0.0497 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 allele 2 : freq = 0.3033 sd = 0.0497 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7000 freq = 0.7792 freq = 0.0000 freq = 0.7594 allele 2 : freq = 0.3000 freq = 0.2208 freq = 0.0000 freq = 0.2406 ***************************************** **************************************** Analysis of Marker 407: rs407 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.811601 pvalue = 0.367647 df = 1 ***************************************** RCHI test RCHI statistic value = 0.770623 pvalue = 0.380024 df = 1 ***************************************** RW test RW statistic value = 1.666091 pvalue = 0.196783 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6933 sd = 0.0498 freq = 0.6538 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 allele 2 : freq = 0.3067 sd = 0.0498 freq = 0.3462 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7000 freq = 0.6583 freq = 0.0000 freq = 0.6687 allele 2 : freq = 0.3000 freq = 0.3417 freq = 0.0000 freq = 0.3312 ***************************************** **************************************** Analysis of Marker 408: rs408 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.556279 pvalue = 0.455763 df = 1 ***************************************** RCHI test RCHI statistic value = 0.908254 pvalue = 0.340578 df = 1 ***************************************** RW test RW statistic value = 1.140454 pvalue = 0.285556 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.4904 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.5096 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5312 freq = 0.4833 freq = 0.0000 freq = 0.4953 allele 2 : freq = 0.4688 freq = 0.5167 freq = 0.0000 freq = 0.5047 ***************************************** **************************************** Analysis of Marker 409: rs409 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.421521 pvalue = 0.516179 df = 1 ***************************************** RCHI test RCHI statistic value = 0.116981 pvalue = 0.732332 df = 1 ***************************************** RW test RW statistic value = 0.051087 pvalue = 0.821182 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7635 sd = 0.0323 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2365 sd = 0.0323 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7375 freq = 0.7521 freq = 0.0000 freq = 0.7484 allele 2 : freq = 0.2625 freq = 0.2479 freq = 0.0000 freq = 0.2516 ***************************************** **************************************** Analysis of Marker 410: rs410 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.058883 pvalue = 0.80827 df = 1 ***************************************** RCHI test RCHI statistic value = 0.212891 pvalue = 0.644511 df = 1 ***************************************** RW test RW statistic value = 1.601219 pvalue = 0.205731 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6967 sd = 0.0497 freq = 0.7288 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.3033 sd = 0.0497 freq = 0.2712 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7250 freq = 0.7042 freq = 0.0000 freq = 0.7094 allele 2 : freq = 0.2750 freq = 0.2958 freq = 0.0000 freq = 0.2906 ***************************************** **************************************** Analysis of Marker 411: rs411 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.702219 pvalue = 0.402039 df = 1 ***************************************** RCHI test RCHI statistic value = 1.492104 pvalue = 0.22189 df = 1 ***************************************** RW test RW statistic value = 1.427313 pvalue = 0.232203 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2283 sd = 0.0453 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 allele 2 : freq = 0.7717 sd = 0.0453 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2125 freq = 0.2646 freq = 0.0000 freq = 0.2516 allele 2 : freq = 0.7875 freq = 0.7354 freq = 0.0000 freq = 0.7484 ***************************************** **************************************** Analysis of Marker 412: rs412 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.034556 pvalue = 0.85253 df = 1 ***************************************** RCHI test RCHI statistic value = 0.404090 pvalue = 0.524984 df = 1 ***************************************** RW test RW statistic value = 0.433140 pvalue = 0.510452 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6067 sd = 0.0528 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.3933 sd = 0.0528 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6062 freq = 0.6375 freq = 0.0000 freq = 0.6297 allele 2 : freq = 0.3937 freq = 0.3625 freq = 0.0000 freq = 0.3703 ***************************************** **************************************** Analysis of Marker 413: rs413 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.362410 pvalue = 0.547171 df = 1 ***************************************** RCHI test RCHI statistic value = 0.205980 pvalue = 0.649937 df = 1 ***************************************** RW test RW statistic value = 2.199161 pvalue = 0.138086 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7600 sd = 0.0461 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 allele 2 : freq = 0.2400 sd = 0.0461 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7812 freq = 0.0000 freq = 0.7766 allele 2 : freq = 0.2375 freq = 0.2188 freq = 0.0000 freq = 0.2234 ***************************************** **************************************** Analysis of Marker 414: rs414 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.175138 pvalue = 0.675586 df = 1 ***************************************** RCHI test RCHI statistic value = 0.052482 pvalue = 0.818799 df = 1 ***************************************** RW test RW statistic value = 0.464125 pvalue = 0.495702 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0650 sd = 0.0266 freq = 0.0904 sd = 0.0218 freq = 0.0000 sd = 0.0000 freq = 0.0800 sd = 0.0192 allele 2 : freq = 0.9350 sd = 0.0266 freq = 0.9096 sd = 0.0218 freq = 0.0000 sd = 0.0000 freq = 0.9200 sd = 0.0192 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0688 freq = 0.0750 freq = 0.0000 freq = 0.0734 allele 2 : freq = 0.9313 freq = 0.9250 freq = 0.0000 freq = 0.9266 ***************************************** **************************************** Analysis of Marker 415: rs415 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.350931 pvalue = 0.553586 df = 1 ***************************************** RCHI test RCHI statistic value = 1.616896 pvalue = 0.203525 df = 1 ***************************************** RW test RW statistic value = 0.190935 pvalue = 0.66214 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.8038 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.1962 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.8333 freq = 0.0000 freq = 0.8203 allele 2 : freq = 0.2188 freq = 0.1667 freq = 0.0000 freq = 0.1797 ***************************************** **************************************** Analysis of Marker 416: rs416 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.005403 pvalue = 0.0829873 df = 1 ***************************************** RCHI test RCHI statistic value = 2.907408 pvalue = 0.0881735 df = 1 ***************************************** RW test RW statistic value = 0.737062 pvalue = 0.390604 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1017 sd = 0.0326 freq = 0.0577 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.0700 sd = 0.0180 allele 2 : freq = 0.8983 sd = 0.0326 freq = 0.9423 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.9300 sd = 0.0180 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1062 freq = 0.0625 freq = 0.0000 freq = 0.0734 allele 2 : freq = 0.8938 freq = 0.9375 freq = 0.0000 freq = 0.9266 ***************************************** **************************************** Analysis of Marker 417: rs417 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.718511 pvalue = 0.396633 df = 1 ***************************************** RCHI test RCHI statistic value = 1.319878 pvalue = 0.250614 df = 1 ***************************************** RW test RW statistic value = 2.584865 pvalue = 0.10789 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0900 sd = 0.0309 freq = 0.1212 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217 allele 2 : freq = 0.9100 sd = 0.0309 freq = 0.8788 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0875 freq = 0.1229 freq = 0.0000 freq = 0.1141 allele 2 : freq = 0.9125 freq = 0.8771 freq = 0.0000 freq = 0.8859 ***************************************** **************************************** Analysis of Marker 418: rs418 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.571973 pvalue = 0.209921 df = 1 ***************************************** RCHI test RCHI statistic value = 2.637457 pvalue = 0.104371 df = 1 ***************************************** RW test RW statistic value = 1.001421 pvalue = 0.316967 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2933 sd = 0.0492 freq = 0.3500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 allele 2 : freq = 0.7067 sd = 0.0492 freq = 0.6500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2938 freq = 0.3708 freq = 0.0000 freq = 0.3516 allele 2 : freq = 0.7063 freq = 0.6292 freq = 0.0000 freq = 0.6484 ***************************************** **************************************** Analysis of Marker 419: rs419 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.031243 pvalue = 0.859699 df = 1 ***************************************** RCHI test RCHI statistic value = 0.045780 pvalue = 0.830576 df = 1 ***************************************** RW test RW statistic value = 1.279540 pvalue = 0.257985 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6233 sd = 0.0523 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.3767 sd = 0.0523 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6312 freq = 0.6208 freq = 0.0000 freq = 0.6234 allele 2 : freq = 0.3688 freq = 0.3792 freq = 0.0000 freq = 0.3766 ***************************************** **************************************** Analysis of Marker 420: rs420 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.181144 pvalue = 0.0228333 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 3.852666 pvalue = 0.049667 df = 1 ***************************************** RW test RW statistic value = 2.077175 pvalue = 0.149517 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1133 sd = 0.0342 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 allele 2 : freq = 0.8867 sd = 0.0342 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1000 freq = 0.1750 freq = 0.0000 freq = 0.1562 allele 2 : freq = 0.9000 freq = 0.8250 freq = 0.0000 freq = 0.8438 ***************************************** **************************************** Analysis of Marker 421: rs421 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.402260 pvalue = 0.525925 df = 1 ***************************************** RCHI test RCHI statistic value = 1.252642 pvalue = 0.263049 df = 1 ***************************************** RW test RW statistic value = 3.121876 pvalue = 0.0772478 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.5308 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.4692 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5312 freq = 0.4750 freq = 0.0000 freq = 0.4891 allele 2 : freq = 0.4688 freq = 0.5250 freq = 0.0000 freq = 0.5109 ***************************************** **************************************** Analysis of Marker 422: rs422 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.234940 pvalue = 0.627885 df = 1 ***************************************** RCHI test RCHI statistic value = 0.284022 pvalue = 0.594077 df = 1 ***************************************** RW test RW statistic value = 0.000861 pvalue = 0.976586 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6483 sd = 0.0516 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 allele 2 : freq = 0.3517 sd = 0.0516 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6625 freq = 0.6875 freq = 0.0000 freq = 0.6813 allele 2 : freq = 0.3375 freq = 0.3125 freq = 0.0000 freq = 0.3187 ***************************************** **************************************** Analysis of Marker 423: rs423 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000755 pvalue = 0.978075 df = 1 ***************************************** RCHI test RCHI statistic value = 0.132074 pvalue = 0.716291 df = 1 ***************************************** RW test RW statistic value = 0.519107 pvalue = 0.471223 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3183 sd = 0.0503 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 allele 2 : freq = 0.6817 sd = 0.0503 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3000 freq = 0.3167 freq = 0.0000 freq = 0.3125 allele 2 : freq = 0.7000 freq = 0.6833 freq = 0.0000 freq = 0.6875 ***************************************** **************************************** Analysis of Marker 424: rs424 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.171403 pvalue = 0.279113 df = 1 ***************************************** RCHI test RCHI statistic value = 1.651288 pvalue = 0.198784 df = 1 ***************************************** RW test RW statistic value = 0.000188 pvalue = 0.989072 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5150 sd = 0.0540 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 allele 2 : freq = 0.4850 sd = 0.0540 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.4604 freq = 0.0000 freq = 0.4766 allele 2 : freq = 0.4750 freq = 0.5396 freq = 0.0000 freq = 0.5234 ***************************************** **************************************** Analysis of Marker 425: rs425 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.895455 pvalue = 0.344003 df = 1 ***************************************** RCHI test RCHI statistic value = 0.443929 pvalue = 0.505232 df = 1 ***************************************** RW test RW statistic value = 0.231924 pvalue = 0.630101 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3950 sd = 0.0528 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.6050 sd = 0.0528 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4062 freq = 0.4396 freq = 0.0000 freq = 0.4313 allele 2 : freq = 0.5938 freq = 0.5604 freq = 0.0000 freq = 0.5687 ***************************************** **************************************** Analysis of Marker 426: rs426 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.310472 pvalue = 0.577391 df = 1 ***************************************** RCHI test RCHI statistic value = 0.028036 pvalue = 0.867024 df = 1 ***************************************** RW test RW statistic value = 0.229912 pvalue = 0.631589 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8267 sd = 0.0409 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 allele 2 : freq = 0.1733 sd = 0.0409 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8125 freq = 0.8187 freq = 0.0000 freq = 0.8172 allele 2 : freq = 0.1875 freq = 0.1812 freq = 0.0000 freq = 0.1828 ***************************************** **************************************** Analysis of Marker 427: rs427 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.365492 pvalue = 0.545472 df = 1 ***************************************** RCHI test RCHI statistic value = 0.499338 pvalue = 0.479791 df = 1 ***************************************** RW test RW statistic value = 0.490652 pvalue = 0.483636 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5417 sd = 0.0538 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 allele 2 : freq = 0.4583 sd = 0.0538 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5625 freq = 0.5271 freq = 0.0000 freq = 0.5359 allele 2 : freq = 0.4375 freq = 0.4729 freq = 0.0000 freq = 0.4641 ***************************************** **************************************** Analysis of Marker 428: rs428 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.328214 pvalue = 0.566712 df = 1 ***************************************** RCHI test RCHI statistic value = 0.303139 pvalue = 0.581921 df = 1 ***************************************** RW test RW statistic value = 0.827405 pvalue = 0.363024 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9000 sd = 0.0324 freq = 0.9308 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186 allele 2 : freq = 0.1000 sd = 0.0324 freq = 0.0692 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9125 freq = 0.9271 freq = 0.0000 freq = 0.9234 allele 2 : freq = 0.0875 freq = 0.0729 freq = 0.0000 freq = 0.0766 ***************************************** **************************************** Analysis of Marker 429: rs429 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.012790 pvalue = 0.909956 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.089254 pvalue = 0.765128 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3050 sd = 0.0497 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 allele 2 : freq = 0.6950 sd = 0.0497 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3063 freq = 0.3063 freq = 0.0000 freq = 0.3063 allele 2 : freq = 0.6937 freq = 0.6937 freq = 0.0000 freq = 0.6937 ***************************************** **************************************** Analysis of Marker 430: rs430 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.012324 pvalue = 0.911607 df = 1 ***************************************** RCHI test RCHI statistic value = 0.007004 pvalue = 0.933302 df = 1 ***************************************** RW test RW statistic value = 1.163137 pvalue = 0.280816 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4183 sd = 0.0533 freq = 0.4308 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 allele 2 : freq = 0.5817 sd = 0.0533 freq = 0.5692 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 freq = 0.4292 freq = 0.0000 freq = 0.4281 allele 2 : freq = 0.5750 freq = 0.5708 freq = 0.0000 freq = 0.5719 ***************************************** **************************************** Analysis of Marker 431: rs431 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.193891 pvalue = 0.659698 df = 1 ***************************************** RCHI test RCHI statistic value = 0.404090 pvalue = 0.524984 df = 1 ***************************************** RW test RW statistic value = 1.350793 pvalue = 0.245139 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3812 freq = 0.4125 freq = 0.0000 freq = 0.4047 allele 2 : freq = 0.6188 freq = 0.5875 freq = 0.0000 freq = 0.5953 ***************************************** **************************************** Analysis of Marker 432: rs432 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.121396 pvalue = 0.727525 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002259 pvalue = 0.96209 df = 1 ***************************************** RW test RW statistic value = 0.948139 pvalue = 0.330193 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2350 sd = 0.0458 freq = 0.2442 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7650 sd = 0.0458 freq = 0.7558 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.2396 freq = 0.0000 freq = 0.2391 allele 2 : freq = 0.7625 freq = 0.7604 freq = 0.0000 freq = 0.7609 ***************************************** **************************************** Analysis of Marker 433: rs433 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.128417 pvalue = 0.720079 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002178 pvalue = 0.962781 df = 1 ***************************************** RW test RW statistic value = 0.439577 pvalue = 0.507326 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2433 sd = 0.0463 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 allele 2 : freq = 0.7567 sd = 0.0463 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 freq = 0.2479 freq = 0.0000 freq = 0.2484 allele 2 : freq = 0.7500 freq = 0.7521 freq = 0.0000 freq = 0.7516 ***************************************** **************************************** Analysis of Marker 434: rs434 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.523012 pvalue = 0.46956 df = 1 ***************************************** RCHI test RCHI statistic value = 0.766362 pvalue = 0.381345 df = 1 ***************************************** RW test RW statistic value = 0.012143 pvalue = 0.912256 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4417 sd = 0.0536 freq = 0.4327 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.5583 sd = 0.0536 freq = 0.5673 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4188 freq = 0.4625 freq = 0.0000 freq = 0.4516 allele 2 : freq = 0.5813 freq = 0.5375 freq = 0.0000 freq = 0.5484 ***************************************** **************************************** Analysis of Marker 435: rs435 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.202733 pvalue = 0.652523 df = 1 ***************************************** RCHI test RCHI statistic value = 0.611166 pvalue = 0.434349 df = 1 ***************************************** RW test RW statistic value = 0.031539 pvalue = 0.859044 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 freq = 0.7417 freq = 0.0000 freq = 0.7500 allele 2 : freq = 0.2250 freq = 0.2583 freq = 0.0000 freq = 0.2500 ***************************************** **************************************** Analysis of Marker 436: rs436 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.216030 pvalue = 0.0223796 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 7.116378 pvalue = 0.00763829 df = 1 ***************************************** RW test RW statistic value = 1.272963 pvalue = 0.259212 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8517 sd = 0.0384 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275 allele 2 : freq = 0.1483 sd = 0.0384 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8812 freq = 0.7771 freq = 0.0000 freq = 0.8031 allele 2 : freq = 0.1187 freq = 0.2229 freq = 0.0000 freq = 0.1969 ***************************************** **************************************** Analysis of Marker 437: rs437 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.692970 pvalue = 0.405156 df = 1 ***************************************** RCHI test RCHI statistic value = 0.174366 pvalue = 0.67626 df = 1 ***************************************** RW test RW statistic value = 0.094010 pvalue = 0.75914 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2533 sd = 0.0470 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316 allele 2 : freq = 0.7467 sd = 0.0470 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.2562 freq = 0.0000 freq = 0.2516 allele 2 : freq = 0.7625 freq = 0.7438 freq = 0.0000 freq = 0.7484 ***************************************** **************************************** Analysis of Marker 438: rs438 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.726948 pvalue = 0.393874 df = 1 ***************************************** RCHI test RCHI statistic value = 1.008875 pvalue = 0.315173 df = 1 ***************************************** RW test RW statistic value = 2.230484 pvalue = 0.135311 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 sd = 0.0506 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321 allele 2 : freq = 0.3250 sd = 0.0506 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6813 freq = 0.7271 freq = 0.0000 freq = 0.7156 allele 2 : freq = 0.3187 freq = 0.2729 freq = 0.0000 freq = 0.2844 ***************************************** **************************************** Analysis of Marker 439: rs439 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.883765 pvalue = 0.347172 df = 1 ***************************************** RCHI test RCHI statistic value = 1.676519 pvalue = 0.195388 df = 1 ***************************************** RW test RW statistic value = 0.468582 pvalue = 0.49364 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2133 sd = 0.0442 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 allele 2 : freq = 0.7867 sd = 0.0442 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 freq = 0.1729 freq = 0.0000 freq = 0.1859 allele 2 : freq = 0.7750 freq = 0.8271 freq = 0.0000 freq = 0.8141 ***************************************** **************************************** Analysis of Marker 440: rs440 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.597378 pvalue = 0.43958 df = 1 ***************************************** RCHI test RCHI statistic value = 0.933919 pvalue = 0.333847 df = 1 ***************************************** RW test RW statistic value = 1.762759 pvalue = 0.184281 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 sd = 0.0410 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 allele 2 : freq = 0.8250 sd = 0.0410 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.2271 freq = 0.0000 freq = 0.2172 allele 2 : freq = 0.8125 freq = 0.7729 freq = 0.0000 freq = 0.7828 ***************************************** **************************************** Analysis of Marker 441: rs441 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.492200 pvalue = 0.482948 df = 1 ***************************************** RCHI test RCHI statistic value = 0.459845 pvalue = 0.497696 df = 1 ***************************************** RW test RW statistic value = 0.153753 pvalue = 0.694974 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1633 sd = 0.0399 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 allele 2 : freq = 0.8367 sd = 0.0399 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1812 freq = 0.1562 freq = 0.0000 freq = 0.1625 allele 2 : freq = 0.8187 freq = 0.8438 freq = 0.0000 freq = 0.8375 ***************************************** **************************************** Analysis of Marker 442: rs442 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.465742 pvalue = 0.494952 df = 1 ***************************************** RCHI test RCHI statistic value = 0.563041 pvalue = 0.453037 df = 1 ***************************************** RW test RW statistic value = 2.641777 pvalue = 0.104087 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5933 sd = 0.0531 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 allele 2 : freq = 0.4067 sd = 0.0531 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5813 freq = 0.5437 freq = 0.0000 freq = 0.5531 allele 2 : freq = 0.4188 freq = 0.4562 freq = 0.0000 freq = 0.4469 ***************************************** **************************************** Analysis of Marker 443: rs443 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.146319 pvalue = 0.702078 df = 1 ***************************************** RCHI test RCHI statistic value = 0.493199 pvalue = 0.482504 df = 1 ***************************************** RW test RW statistic value = 0.202135 pvalue = 0.653003 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6450 sd = 0.0517 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 allele 2 : freq = 0.3550 sd = 0.0517 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6562 freq = 0.6896 freq = 0.0000 freq = 0.6813 allele 2 : freq = 0.3438 freq = 0.3104 freq = 0.0000 freq = 0.3187 ***************************************** **************************************** Analysis of Marker 444: rs444 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.003350 pvalue = 0.953842 df = 1 ***************************************** RCHI test RCHI statistic value = 0.109971 pvalue = 0.740177 df = 1 ***************************************** RW test RW statistic value = 0.243131 pvalue = 0.621953 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4833 sd = 0.0540 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 allele 2 : freq = 0.5167 sd = 0.0540 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 freq = 0.4583 freq = 0.0000 freq = 0.4625 allele 2 : freq = 0.5250 freq = 0.5417 freq = 0.0000 freq = 0.5375 ***************************************** **************************************** Analysis of Marker 445: rs445 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.031501 pvalue = 0.859128 df = 1 ***************************************** RCHI test RCHI statistic value = 0.090040 pvalue = 0.764127 df = 1 ***************************************** RW test RW statistic value = 0.629144 pvalue = 0.427669 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2083 sd = 0.0439 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 allele 2 : freq = 0.7917 sd = 0.0439 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2062 freq = 0.1938 freq = 0.0000 freq = 0.1969 allele 2 : freq = 0.7937 freq = 0.8063 freq = 0.0000 freq = 0.8031 ***************************************** **************************************** Analysis of Marker 446: rs446 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.343259 pvalue = 0.24646 df = 1 ***************************************** RCHI test RCHI statistic value = 0.998839 pvalue = 0.317592 df = 1 ***************************************** RW test RW statistic value = 0.681573 pvalue = 0.409046 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6117 sd = 0.0526 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 allele 2 : freq = 0.3883 sd = 0.0526 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.5500 freq = 0.0000 freq = 0.5625 allele 2 : freq = 0.4000 freq = 0.4500 freq = 0.0000 freq = 0.4375 ***************************************** **************************************** Analysis of Marker 447: rs447 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.655568 pvalue = 0.198203 df = 1 ***************************************** RCHI test RCHI statistic value = 1.629234 pvalue = 0.201809 df = 1 ***************************************** RW test RW statistic value = 1.800823 pvalue = 0.179613 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8800 sd = 0.0351 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1200 sd = 0.0351 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.8417 freq = 0.0000 freq = 0.8531 allele 2 : freq = 0.1125 freq = 0.1583 freq = 0.0000 freq = 0.1469 ***************************************** **************************************** Analysis of Marker 448: rs448 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.035236 pvalue = 0.851101 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 2.870400 pvalue = 0.0902225 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.4562 freq = 0.0000 freq = 0.4562 allele 2 : freq = 0.5437 freq = 0.5437 freq = 0.0000 freq = 0.5437 ***************************************** **************************************** Analysis of Marker 449: rs449 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.790283 pvalue = 0.016115 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 4.073779 pvalue = 0.0435537 df = 1 ***************************************** RW test RW statistic value = 2.288403 pvalue = 0.130344 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6850 sd = 0.0502 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 allele 2 : freq = 0.3150 sd = 0.0502 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6813 freq = 0.7667 freq = 0.0000 freq = 0.7453 allele 2 : freq = 0.3187 freq = 0.2333 freq = 0.0000 freq = 0.2547 ***************************************** **************************************** Analysis of Marker 450: rs450 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.065286 pvalue = 0.798329 df = 1 ***************************************** RCHI test RCHI statistic value = 0.056480 pvalue = 0.812149 df = 1 ***************************************** RW test RW statistic value = 0.544859 pvalue = 0.460426 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7700 sd = 0.0455 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 allele 2 : freq = 0.2300 sd = 0.0455 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7729 freq = 0.0000 freq = 0.7703 allele 2 : freq = 0.2375 freq = 0.2271 freq = 0.0000 freq = 0.2297 ***************************************** **************************************** Analysis of Marker 451: rs451 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.170864 pvalue = 0.0411248 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 4.822847 pvalue = 0.0280849 df = 1 ***************************************** RW test RW statistic value = 0.720563 pvalue = 0.395959 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.5327 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.4673 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 freq = 0.5354 freq = 0.0000 freq = 0.5078 allele 2 : freq = 0.5750 freq = 0.4646 freq = 0.0000 freq = 0.4922 ***************************************** **************************************** Analysis of Marker 452: rs452 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.200599 pvalue = 0.654238 df = 1 ***************************************** RCHI test RCHI statistic value = 0.020076 pvalue = 0.887324 df = 1 ***************************************** RW test RW statistic value = 1.406719 pvalue = 0.235602 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2750 sd = 0.0482 freq = 0.2692 sd = 0.0337 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310 allele 2 : freq = 0.7250 sd = 0.0482 freq = 0.7308 sd = 0.0337 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2812 freq = 0.2750 freq = 0.0000 freq = 0.2766 allele 2 : freq = 0.7188 freq = 0.7250 freq = 0.0000 freq = 0.7234 ***************************************** **************************************** Analysis of Marker 453: rs453 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.278902 pvalue = 0.597422 df = 1 ***************************************** RCHI test RCHI statistic value = 0.443784 pvalue = 0.505302 df = 1 ***************************************** RW test RW statistic value = 0.699642 pvalue = 0.402904 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6683 sd = 0.0509 freq = 0.6827 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 allele 2 : freq = 0.3317 sd = 0.0509 freq = 0.3173 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6625 freq = 0.6937 freq = 0.0000 freq = 0.6859 allele 2 : freq = 0.3375 freq = 0.3063 freq = 0.0000 freq = 0.3141 ***************************************** **************************************** Analysis of Marker 454: rs454 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.037289 pvalue = 0.308453 df = 1 ***************************************** RCHI test RCHI statistic value = 1.458375 pvalue = 0.227189 df = 1 ***************************************** RW test RW statistic value = 0.118329 pvalue = 0.730854 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.4558 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.5442 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4875 freq = 0.4271 freq = 0.0000 freq = 0.4422 allele 2 : freq = 0.5125 freq = 0.5729 freq = 0.0000 freq = 0.5578 ***************************************** **************************************** Analysis of Marker 455: rs455 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.945941 pvalue = 0.0860935 df = 1 ***************************************** RCHI test RCHI statistic value = 2.390639 pvalue = 0.122064 df = 1 ***************************************** RW test RW statistic value = 1.510176 pvalue = 0.219112 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.4396 freq = 0.0000 freq = 0.4203 allele 2 : freq = 0.6375 freq = 0.5604 freq = 0.0000 freq = 0.5797 ***************************************** **************************************** Analysis of Marker 456: rs456 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.713060 pvalue = 0.190589 df = 1 ***************************************** RCHI test RCHI statistic value = 1.393102 pvalue = 0.237882 df = 1 ***************************************** RW test RW statistic value = 2.761317 pvalue = 0.0965687 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2450 sd = 0.0465 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 allele 2 : freq = 0.7550 sd = 0.0465 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 freq = 0.2021 freq = 0.0000 freq = 0.2141 allele 2 : freq = 0.7500 freq = 0.7979 freq = 0.0000 freq = 0.7859 ***************************************** **************************************** Analysis of Marker 457: rs457 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.023268 pvalue = 0.878763 df = 1 ***************************************** RCHI test RCHI statistic value = 0.070143 pvalue = 0.791128 df = 1 ***************************************** RW test RW statistic value = 0.275692 pvalue = 0.599539 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1050 sd = 0.0331 freq = 0.1000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221 allele 2 : freq = 0.8950 sd = 0.0331 freq = 0.9000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1125 freq = 0.1042 freq = 0.0000 freq = 0.1062 allele 2 : freq = 0.8875 freq = 0.8958 freq = 0.0000 freq = 0.8938 ***************************************** **************************************** Analysis of Marker 458: rs458 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.104511 pvalue = 0.042769 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 5.583574 pvalue = 0.0181297 df = 1 ***************************************** RW test RW statistic value = 1.050141 pvalue = 0.305475 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2817 sd = 0.0486 freq = 0.2096 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 allele 2 : freq = 0.7183 sd = 0.0486 freq = 0.7904 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2938 freq = 0.1938 freq = 0.0000 freq = 0.2188 allele 2 : freq = 0.7063 freq = 0.8063 freq = 0.0000 freq = 0.7812 ***************************************** **************************************** Analysis of Marker 459: rs459 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.227985 pvalue = 0.633022 df = 1 ***************************************** RCHI test RCHI statistic value = 0.011631 pvalue = 0.914116 df = 1 ***************************************** RW test RW statistic value = 0.001270 pvalue = 0.971573 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8400 sd = 0.0396 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 allele 2 : freq = 0.1600 sd = 0.0396 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8479 freq = 0.0000 freq = 0.8469 allele 2 : freq = 0.1562 freq = 0.1521 freq = 0.0000 freq = 0.1531 ***************************************** **************************************** Analysis of Marker 460: rs460 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.079753 pvalue = 0.777632 df = 1 ***************************************** RCHI test RCHI statistic value = 0.265427 pvalue = 0.606416 df = 1 ***************************************** RW test RW statistic value = 1.606003 pvalue = 0.205055 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8500 freq = 0.8313 freq = 0.0000 freq = 0.8359 allele 2 : freq = 0.1500 freq = 0.1688 freq = 0.0000 freq = 0.1641 ***************************************** **************************************** Analysis of Marker 461: rs461 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.215856 pvalue = 0.0400479 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 3.905171 pvalue = 0.0481377 df = 1 ***************************************** RW test RW statistic value = 2.597151 pvalue = 0.107056 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3383 sd = 0.0511 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 allele 2 : freq = 0.6617 sd = 0.0511 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3312 freq = 0.4292 freq = 0.0000 freq = 0.4047 allele 2 : freq = 0.6687 freq = 0.5708 freq = 0.0000 freq = 0.5953 ***************************************** **************************************** Analysis of Marker 462: rs462 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.640334 pvalue = 0.20028 df = 1 ***************************************** RCHI test RCHI statistic value = 2.403557 pvalue = 0.12106 df = 1 ***************************************** RW test RW statistic value = 0.767043 pvalue = 0.381133 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1833 sd = 0.0418 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 allele 2 : freq = 0.8167 sd = 0.0418 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1812 freq = 0.2458 freq = 0.0000 freq = 0.2297 allele 2 : freq = 0.8187 freq = 0.7542 freq = 0.0000 freq = 0.7703 ***************************************** **************************************** Analysis of Marker 463: rs463 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.821793 pvalue = 0.364656 df = 1 ***************************************** RCHI test RCHI statistic value = 0.556451 pvalue = 0.455694 df = 1 ***************************************** RW test RW statistic value = 0.697716 pvalue = 0.403552 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 sd = 0.0537 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 allele 2 : freq = 0.5500 sd = 0.0537 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.4875 freq = 0.0000 freq = 0.4781 allele 2 : freq = 0.5500 freq = 0.5125 freq = 0.0000 freq = 0.5219 ***************************************** **************************************** Analysis of Marker 464: rs464 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.390306 pvalue = 0.532139 df = 1 ***************************************** RCHI test RCHI statistic value = 0.386585 pvalue = 0.5341 df = 1 ***************************************** RW test RW statistic value = 0.582281 pvalue = 0.445419 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3300 sd = 0.0508 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 allele 2 : freq = 0.6700 sd = 0.0508 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.3146 freq = 0.0000 freq = 0.3219 allele 2 : freq = 0.6562 freq = 0.6854 freq = 0.0000 freq = 0.6781 ***************************************** **************************************** Analysis of Marker 465: rs465 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.629075 pvalue = 0.201831 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** RCHI test RCHI statistic value = 1.687747 pvalue = 0.193898 df = 1 The p-value might not be exact because of the small number of allele 2 in cases ***************************************** RW test RW statistic value = 0.564313 pvalue = 0.452528 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9467 sd = 0.0243 freq = 0.9231 sd = 0.0202 freq = 0.0000 sd = 0.0000 freq = 0.9300 sd = 0.0180 allele 2 : freq = 0.0533 sd = 0.0243 freq = 0.0769 sd = 0.0202 freq = 0.0000 sd = 0.0000 freq = 0.0700 sd = 0.0180 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9563 freq = 0.9229 freq = 0.0000 freq = 0.9313 allele 2 : freq = 0.0437 freq = 0.0771 freq = 0.0000 freq = 0.0688 ***************************************** **************************************** Analysis of Marker 466: rs466 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.497382 pvalue = 0.480653 df = 1 ***************************************** RCHI test RCHI statistic value = 0.250241 pvalue = 0.616906 df = 1 ***************************************** RW test RW statistic value = 0.437134 pvalue = 0.508509 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.4375 freq = 0.0000 freq = 0.4313 allele 2 : freq = 0.5875 freq = 0.5625 freq = 0.0000 freq = 0.5687 ***************************************** **************************************** Analysis of Marker 467: rs467 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000359 pvalue = 0.984892 df = 1 ***************************************** RCHI test RCHI statistic value = 0.062706 pvalue = 0.802269 df = 1 ***************************************** RW test RW statistic value = 0.128556 pvalue = 0.719934 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4383 sd = 0.0536 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 allele 2 : freq = 0.5617 sd = 0.0536 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4437 freq = 0.4562 freq = 0.0000 freq = 0.4531 allele 2 : freq = 0.5563 freq = 0.5437 freq = 0.0000 freq = 0.5469 ***************************************** **************************************** Analysis of Marker 468: rs468 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.099689 pvalue = 0.294334 df = 1 ***************************************** RCHI test RCHI statistic value = 1.086114 pvalue = 0.297334 df = 1 ***************************************** RW test RW statistic value = 0.851690 pvalue = 0.356075 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5050 sd = 0.0540 freq = 0.4308 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.4950 sd = 0.0540 freq = 0.5692 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4875 freq = 0.4354 freq = 0.0000 freq = 0.4484 allele 2 : freq = 0.5125 freq = 0.5646 freq = 0.0000 freq = 0.5516 ***************************************** **************************************** Analysis of Marker 469: rs469 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.224508 pvalue = 0.268478 df = 1 ***************************************** RCHI test RCHI statistic value = 0.209424 pvalue = 0.647219 df = 1 ***************************************** RW test RW statistic value = 0.333331 pvalue = 0.563704 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4950 sd = 0.0540 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 allele 2 : freq = 0.5050 sd = 0.0540 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5125 freq = 0.4896 freq = 0.0000 freq = 0.4953 allele 2 : freq = 0.4875 freq = 0.5104 freq = 0.0000 freq = 0.5047 ***************************************** **************************************** Analysis of Marker 470: rs470 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.920887 pvalue = 0.165759 df = 1 ***************************************** RCHI test RCHI statistic value = 1.486758 pvalue = 0.22272 df = 1 ***************************************** RW test RW statistic value = 2.168667 pvalue = 0.140848 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3433 sd = 0.0513 freq = 0.4250 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 allele 2 : freq = 0.6567 sd = 0.0513 freq = 0.5750 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3563 freq = 0.4167 freq = 0.0000 freq = 0.4016 allele 2 : freq = 0.6438 freq = 0.5833 freq = 0.0000 freq = 0.5984 ***************************************** **************************************** Analysis of Marker 471: rs471 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.017107 pvalue = 0.895939 df = 1 ***************************************** RCHI test RCHI statistic value = 0.043657 pvalue = 0.834494 df = 1 ***************************************** RW test RW statistic value = 0.003050 pvalue = 0.955954 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5687 freq = 0.5583 freq = 0.0000 freq = 0.5609 allele 2 : freq = 0.4313 freq = 0.4417 freq = 0.0000 freq = 0.4391 ***************************************** **************************************** Analysis of Marker 472: rs472 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.165666 pvalue = 0.683992 df = 1 ***************************************** RCHI test RCHI statistic value = 0.133972 pvalue = 0.714349 df = 1 ***************************************** RW test RW statistic value = 4.890740 pvalue = 0.0270011 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.2019 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280 allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.7981 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1812 freq = 0.1958 freq = 0.0000 freq = 0.1922 allele 2 : freq = 0.8187 freq = 0.8042 freq = 0.0000 freq = 0.8078 ***************************************** **************************************** Analysis of Marker 473: rs473 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.805915 pvalue = 0.369331 df = 1 ***************************************** RCHI test RCHI statistic value = 1.237895 pvalue = 0.265877 df = 1 ***************************************** RW test RW statistic value = 0.719741 pvalue = 0.396229 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3433 sd = 0.0513 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 allele 2 : freq = 0.6567 sd = 0.0513 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.3979 freq = 0.0000 freq = 0.3844 allele 2 : freq = 0.6562 freq = 0.6021 freq = 0.0000 freq = 0.6156 ***************************************** **************************************** Analysis of Marker 474: rs474 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.387785 pvalue = 0.122287 df = 1 ***************************************** RCHI test RCHI statistic value = 2.092595 pvalue = 0.148015 df = 1 ***************************************** RW test RW statistic value = 0.115065 pvalue = 0.73445 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2400 sd = 0.0461 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 allele 2 : freq = 0.7600 sd = 0.0461 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2125 freq = 0.2771 freq = 0.0000 freq = 0.2609 allele 2 : freq = 0.7875 freq = 0.7229 freq = 0.0000 freq = 0.7391 ***************************************** **************************************** Analysis of Marker 475: rs475 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.822566 pvalue = 0.177008 df = 1 ***************************************** RCHI test RCHI statistic value = 1.548467 pvalue = 0.213362 df = 1 ***************************************** RW test RW statistic value = 1.191858 pvalue = 0.274955 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4350 sd = 0.0535 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 allele 2 : freq = 0.5650 sd = 0.0535 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 freq = 0.3646 freq = 0.0000 freq = 0.3797 allele 2 : freq = 0.5750 freq = 0.6354 freq = 0.0000 freq = 0.6203 ***************************************** **************************************** Analysis of Marker 476: rs476 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.002917 pvalue = 0.956931 df = 1 ***************************************** RCHI test RCHI statistic value = 0.152791 pvalue = 0.695882 df = 1 ***************************************** RW test RW statistic value = 0.504616 pvalue = 0.477479 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7667 sd = 0.0457 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 allele 2 : freq = 0.2333 sd = 0.0457 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7688 freq = 0.7854 freq = 0.0000 freq = 0.7812 allele 2 : freq = 0.2313 freq = 0.2146 freq = 0.0000 freq = 0.2188 ***************************************** **************************************** Analysis of Marker 477: rs477 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.989584 pvalue = 0.319844 df = 1 ***************************************** RCHI test RCHI statistic value = 1.450022 pvalue = 0.228524 df = 1 ***************************************** RW test RW statistic value = 2.675654 pvalue = 0.101893 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2783 sd = 0.0484 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.7217 sd = 0.0484 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2812 freq = 0.3375 freq = 0.0000 freq = 0.3234 allele 2 : freq = 0.7188 freq = 0.6625 freq = 0.0000 freq = 0.6766 ***************************************** **************************************** Analysis of Marker 478: rs478 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.129906 pvalue = 0.0421317 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 4.124584 pvalue = 0.0422644 df = 1 ***************************************** RW test RW statistic value = 1.718457 pvalue = 0.189892 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8117 sd = 0.0422 freq = 0.7346 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310 allele 2 : freq = 0.1883 sd = 0.0422 freq = 0.2654 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8125 freq = 0.7229 freq = 0.0000 freq = 0.7453 allele 2 : freq = 0.1875 freq = 0.2771 freq = 0.0000 freq = 0.2547 ***************************************** **************************************** Analysis of Marker 479: rs479 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.070477 pvalue = 0.790644 df = 1 ***************************************** RCHI test RCHI statistic value = 0.046860 pvalue = 0.82862 df = 1 ***************************************** RW test RW statistic value = 0.149185 pvalue = 0.699316 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3533 sd = 0.0516 freq = 0.3577 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 allele 2 : freq = 0.6467 sd = 0.0516 freq = 0.6423 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.3542 freq = 0.0000 freq = 0.3516 allele 2 : freq = 0.6562 freq = 0.6458 freq = 0.0000 freq = 0.6484 ***************************************** **************************************** Analysis of Marker 480: rs480 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.887833 pvalue = 0.169447 df = 1 ***************************************** RCHI test RCHI statistic value = 1.072972 pvalue = 0.300275 df = 1 ***************************************** RW test RW statistic value = 3.415959 pvalue = 0.0645689 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 sd = 0.0534 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.4250 sd = 0.0534 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5625 freq = 0.5104 freq = 0.0000 freq = 0.5234 allele 2 : freq = 0.4375 freq = 0.4896 freq = 0.0000 freq = 0.4766 ***************************************** **************************************** Analysis of Marker 481: rs481 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.216504 pvalue = 0.641717 df = 1 ***************************************** RCHI test RCHI statistic value = 0.604034 pvalue = 0.437043 df = 1 ***************************************** RW test RW statistic value = 1.203951 pvalue = 0.272533 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.9038 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207 allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.0962 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9125 freq = 0.8896 freq = 0.0000 freq = 0.8953 allele 2 : freq = 0.0875 freq = 0.1104 freq = 0.0000 freq = 0.1047 ***************************************** **************************************** Analysis of Marker 482: rs482 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.506111 pvalue = 0.476827 df = 1 ***************************************** RCHI test RCHI statistic value = 0.503391 pvalue = 0.478014 df = 1 ***************************************** RW test RW statistic value = 3.674295 pvalue = 0.0552576 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4767 sd = 0.0539 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 allele 2 : freq = 0.5233 sd = 0.0539 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4688 freq = 0.4333 freq = 0.0000 freq = 0.4422 allele 2 : freq = 0.5312 freq = 0.5667 freq = 0.0000 freq = 0.5578 ***************************************** **************************************** Analysis of Marker 483: rs483 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.116459 pvalue = 0.290682 df = 1 ***************************************** RCHI test RCHI statistic value = 1.286853 pvalue = 0.256629 df = 1 ***************************************** RW test RW statistic value = 2.131190 pvalue = 0.144329 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1667 sd = 0.0403 freq = 0.1500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8333 sd = 0.0403 freq = 0.8500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1688 freq = 0.1292 freq = 0.0000 freq = 0.1391 allele 2 : freq = 0.8313 freq = 0.8708 freq = 0.0000 freq = 0.8609 ***************************************** **************************************** Analysis of Marker 484: rs484 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.597124 pvalue = 0.206311 df = 1 ***************************************** RCHI test RCHI statistic value = 2.340243 pvalue = 0.12607 df = 1 ***************************************** RW test RW statistic value = 0.024190 pvalue = 0.876403 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1200 sd = 0.0351 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.8800 sd = 0.0351 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1125 freq = 0.1667 freq = 0.0000 freq = 0.1531 allele 2 : freq = 0.8875 freq = 0.8333 freq = 0.0000 freq = 0.8469 ***************************************** **************************************** Analysis of Marker 485: rs485 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.002234 pvalue = 0.962305 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 1.406719 pvalue = 0.235602 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2750 sd = 0.0482 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310 allele 2 : freq = 0.7250 sd = 0.0482 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2625 freq = 0.2625 freq = 0.0000 freq = 0.2625 allele 2 : freq = 0.7375 freq = 0.7375 freq = 0.0000 freq = 0.7375 ***************************************** **************************************** Analysis of Marker 486: rs486 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.012724 pvalue = 0.910189 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 The p-value might not be exact because of the small number of allele 2 in cases ***************************************** RW test RW statistic value = 2.332156 pvalue = 0.126726 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9550 sd = 0.0224 freq = 0.9654 sd = 0.0139 freq = 0.0000 sd = 0.0000 freq = 0.9650 sd = 0.0130 allele 2 : freq = 0.0450 sd = 0.0224 freq = 0.0346 sd = 0.0139 freq = 0.0000 sd = 0.0000 freq = 0.0350 sd = 0.0130 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9625 freq = 0.9625 freq = 0.0000 freq = 0.9625 allele 2 : freq = 0.0375 freq = 0.0375 freq = 0.0000 freq = 0.0375 ***************************************** **************************************** Analysis of Marker 487: rs487 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.078347 pvalue = 0.779551 df = 1 ***************************************** RCHI test RCHI statistic value = 0.007765 pvalue = 0.929784 df = 1 ***************************************** RW test RW statistic value = 0.010385 pvalue = 0.918832 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6833 sd = 0.0502 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 allele 2 : freq = 0.3167 sd = 0.0502 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.6917 freq = 0.0000 freq = 0.6906 allele 2 : freq = 0.3125 freq = 0.3083 freq = 0.0000 freq = 0.3094 ***************************************** **************************************** Analysis of Marker 488: rs488 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.820346 pvalue = 0.365079 df = 1 ***************************************** RCHI test RCHI statistic value = 0.778927 pvalue = 0.37747 df = 1 ***************************************** RW test RW statistic value = 0.545781 pvalue = 0.460047 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1183 sd = 0.0349 freq = 0.1558 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.8817 sd = 0.0349 freq = 0.8442 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1187 freq = 0.1500 freq = 0.0000 freq = 0.1422 allele 2 : freq = 0.8812 freq = 0.8500 freq = 0.0000 freq = 0.8578 ***************************************** **************************************** Analysis of Marker 489: rs489 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.195433 pvalue = 0.658433 df = 1 ***************************************** RCHI test RCHI statistic value = 1.034944 pvalue = 0.309 df = 1 ***************************************** RW test RW statistic value = 0.341757 pvalue = 0.558817 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6687 freq = 0.7167 freq = 0.0000 freq = 0.7047 allele 2 : freq = 0.3312 freq = 0.2833 freq = 0.0000 freq = 0.2953 ***************************************** **************************************** Analysis of Marker 490: rs490 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.042672 pvalue = 0.836344 df = 1 ***************************************** RCHI test RCHI statistic value = 0.584519 pvalue = 0.444546 df = 1 ***************************************** RW test RW statistic value = 0.992904 pvalue = 0.319034 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3875 freq = 0.3500 freq = 0.0000 freq = 0.3594 allele 2 : freq = 0.6125 freq = 0.6500 freq = 0.0000 freq = 0.6406 ***************************************** **************************************** Analysis of Marker 491: rs491 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.770341 pvalue = 0.380112 df = 1 ***************************************** RCHI test RCHI statistic value = 0.593985 pvalue = 0.440882 df = 1 ***************************************** RW test RW statistic value = 0.468392 pvalue = 0.493728 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2233 sd = 0.0450 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 allele 2 : freq = 0.7767 sd = 0.0450 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2125 freq = 0.2458 freq = 0.0000 freq = 0.2375 allele 2 : freq = 0.7875 freq = 0.7542 freq = 0.0000 freq = 0.7625 ***************************************** **************************************** Analysis of Marker 492: rs492 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.287282 pvalue = 0.591967 df = 1 ***************************************** RCHI test RCHI statistic value = 1.122473 pvalue = 0.289387 df = 1 ***************************************** RW test RW statistic value = 0.530200 pvalue = 0.466523 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6183 sd = 0.0525 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.3817 sd = 0.0525 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5938 freq = 0.6458 freq = 0.0000 freq = 0.6328 allele 2 : freq = 0.4062 freq = 0.3542 freq = 0.0000 freq = 0.3672 ***************************************** **************************************** Analysis of Marker 493: rs493 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.072435 pvalue = 0.300396 df = 1 ***************************************** RCHI test RCHI statistic value = 2.051022 pvalue = 0.152104 df = 1 ***************************************** RW test RW statistic value = 0.409888 pvalue = 0.522026 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5700 sd = 0.0535 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.4300 sd = 0.0535 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5563 freq = 0.6271 freq = 0.0000 freq = 0.6094 allele 2 : freq = 0.4437 freq = 0.3729 freq = 0.0000 freq = 0.3906 ***************************************** **************************************** Analysis of Marker 494: rs494 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.118371 pvalue = 0.730808 df = 1 ***************************************** RCHI test RCHI statistic value = 0.529218 pvalue = 0.466936 df = 1 ***************************************** RW test RW statistic value = 0.499820 pvalue = 0.479579 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3812 freq = 0.3458 freq = 0.0000 freq = 0.3547 allele 2 : freq = 0.6188 freq = 0.6542 freq = 0.0000 freq = 0.6453 ***************************************** **************************************** Analysis of Marker 495: rs495 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.845034 pvalue = 0.0916566 df = 1 ***************************************** RCHI test RCHI statistic value = 0.602433 pvalue = 0.437651 df = 1 ***************************************** RW test RW statistic value = 0.504387 pvalue = 0.477579 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8150 sd = 0.0419 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 allele 2 : freq = 0.1850 sd = 0.0419 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 freq = 0.8271 freq = 0.0000 freq = 0.8203 allele 2 : freq = 0.2000 freq = 0.1729 freq = 0.0000 freq = 0.1797 ***************************************** **************************************** Analysis of Marker 496: rs496 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.135418 pvalue = 0.712879 df = 1 ***************************************** RCHI test RCHI statistic value = 0.284714 pvalue = 0.593628 df = 1 ***************************************** RW test RW statistic value = 1.223090 pvalue = 0.268755 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7350 sd = 0.0477 freq = 0.7712 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 allele 2 : freq = 0.2650 sd = 0.0477 freq = 0.2288 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7500 freq = 0.7729 freq = 0.0000 freq = 0.7672 allele 2 : freq = 0.2500 freq = 0.2271 freq = 0.0000 freq = 0.2328 ***************************************** **************************************** Analysis of Marker 497: rs497 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.378116 pvalue = 0.123046 df = 1 ***************************************** RCHI test RCHI statistic value = 2.757031 pvalue = 0.0968278 df = 1 ***************************************** RW test RW statistic value = 0.228774 pvalue = 0.632434 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5850 sd = 0.0532 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 allele 2 : freq = 0.4150 sd = 0.0532 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5563 freq = 0.6375 freq = 0.0000 freq = 0.6172 allele 2 : freq = 0.4437 freq = 0.3625 freq = 0.0000 freq = 0.3828 ***************************************** **************************************** Analysis of Marker 498: rs498 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.021657 pvalue = 0.883004 df = 1 ***************************************** RCHI test RCHI statistic value = 0.061902 pvalue = 0.803514 df = 1 ***************************************** RW test RW statistic value = 0.745112 pvalue = 0.388028 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5017 sd = 0.0540 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 allele 2 : freq = 0.4983 sd = 0.0540 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5062 freq = 0.4938 freq = 0.0000 freq = 0.4969 allele 2 : freq = 0.4938 freq = 0.5062 freq = 0.0000 freq = 0.5031 ***************************************** **************************************** Analysis of Marker 499: rs499 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.191296 pvalue = 0.275068 df = 1 ***************************************** RCHI test RCHI statistic value = 1.895571 pvalue = 0.168575 df = 1 ***************************************** RW test RW statistic value = 0.018626 pvalue = 0.891444 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2700 sd = 0.0480 freq = 0.2962 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 allele 2 : freq = 0.7300 sd = 0.0480 freq = 0.7038 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 freq = 0.3125 freq = 0.0000 freq = 0.2969 allele 2 : freq = 0.7500 freq = 0.6875 freq = 0.0000 freq = 0.7031 ***************************************** **************************************** Analysis of Marker 500: rs500 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.029562 pvalue = 0.154265 df = 1 ***************************************** RCHI test RCHI statistic value = 1.118104 pvalue = 0.290327 df = 1 ***************************************** RW test RW statistic value = 3.977751 pvalue = 0.0461051 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2583 sd = 0.0473 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 allele 2 : freq = 0.7417 sd = 0.0473 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2687 freq = 0.3187 freq = 0.0000 freq = 0.3063 allele 2 : freq = 0.7312 freq = 0.6813 freq = 0.0000 freq = 0.6937 ***************************************** **************************************** Analysis of Marker 501: rs501 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.309031 pvalue = 0.25257 df = 1 ***************************************** RCHI test RCHI statistic value = 1.711590 pvalue = 0.190779 df = 1 ***************************************** RW test RW statistic value = 5.103207 pvalue = 0.0238816 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6483 sd = 0.0516 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 allele 2 : freq = 0.3517 sd = 0.0516 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6375 freq = 0.5729 freq = 0.0000 freq = 0.5891 allele 2 : freq = 0.3625 freq = 0.4271 freq = 0.0000 freq = 0.4109 ***************************************** **************************************** Analysis of Marker 502: rs502 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.639075 pvalue = 0.104264 df = 1 ***************************************** RCHI test RCHI statistic value = 3.482000 pvalue = 0.0620397 df = 1 ***************************************** RW test RW statistic value = 3.523560 pvalue = 0.0605023 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4233 sd = 0.0534 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.5767 sd = 0.0534 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4188 freq = 0.5125 freq = 0.0000 freq = 0.4891 allele 2 : freq = 0.5813 freq = 0.4875 freq = 0.0000 freq = 0.5109 ***************************************** **************************************** Analysis of Marker 503: rs503 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.101791 pvalue = 0.749691 df = 1 ***************************************** RCHI test RCHI statistic value = 0.021811 pvalue = 0.882591 df = 1 ***************************************** RW test RW statistic value = 0.016933 pvalue = 0.896465 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7783 sd = 0.0449 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 allele 2 : freq = 0.2217 sd = 0.0449 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.7625 freq = 0.0000 freq = 0.7609 allele 2 : freq = 0.2437 freq = 0.2375 freq = 0.0000 freq = 0.2391 ***************************************** **************************************** Analysis of Marker 504: rs504 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.012724 pvalue = 0.910189 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 The p-value might not be exact because of the small number of allele 1 in cases ***************************************** RW test RW statistic value = 0.611827 pvalue = 0.434101 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0383 sd = 0.0207 freq = 0.0346 sd = 0.0139 freq = 0.0000 sd = 0.0000 freq = 0.0350 sd = 0.0130 allele 2 : freq = 0.9617 sd = 0.0207 freq = 0.9654 sd = 0.0139 freq = 0.0000 sd = 0.0000 freq = 0.9650 sd = 0.0130 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0375 freq = 0.0375 freq = 0.0000 freq = 0.0375 allele 2 : freq = 0.9625 freq = 0.9625 freq = 0.0000 freq = 0.9625 ***************************************** **************************************** Analysis of Marker 505: rs505 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 8.432396 pvalue = 0.00368594 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 10.794479 pvalue = 0.00101803 df = 1 ***************************************** RW test RW statistic value = 3.851124 pvalue = 0.0497127 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4900 sd = 0.0540 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.5100 sd = 0.0540 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4813 freq = 0.6438 freq = 0.0000 freq = 0.6031 allele 2 : freq = 0.5188 freq = 0.3563 freq = 0.0000 freq = 0.3969 ***************************************** **************************************** Analysis of Marker 506: rs506 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.158649 pvalue = 0.141769 df = 1 ***************************************** RCHI test RCHI statistic value = 1.472002 pvalue = 0.22503 df = 1 ***************************************** RW test RW statistic value = 0.439577 pvalue = 0.507326 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7783 sd = 0.0449 freq = 0.7288 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 allele 2 : freq = 0.2217 sd = 0.0449 freq = 0.2712 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7875 freq = 0.7333 freq = 0.0000 freq = 0.7469 allele 2 : freq = 0.2125 freq = 0.2667 freq = 0.0000 freq = 0.2531 ***************************************** **************************************** Analysis of Marker 507: rs507 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.232641 pvalue = 0.629572 df = 1 ***************************************** RCHI test RCHI statistic value = 0.023283 pvalue = 0.878723 df = 1 ***************************************** RW test RW statistic value = 0.885757 pvalue = 0.34663 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2317 sd = 0.0456 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 allele 2 : freq = 0.7683 sd = 0.0456 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2313 freq = 0.2250 freq = 0.0000 freq = 0.2266 allele 2 : freq = 0.7688 freq = 0.7750 freq = 0.0000 freq = 0.7734 ***************************************** **************************************** Analysis of Marker 508: rs508 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.032592 pvalue = 0.856734 df = 1 ***************************************** RCHI test RCHI statistic value = 0.006884 pvalue = 0.933874 df = 1 ***************************************** RW test RW statistic value = 0.018790 pvalue = 0.89097 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5467 sd = 0.0538 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 allele 2 : freq = 0.4533 sd = 0.0538 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5375 freq = 0.5417 freq = 0.0000 freq = 0.5406 allele 2 : freq = 0.4625 freq = 0.4583 freq = 0.0000 freq = 0.4594 ***************************************** **************************************** Analysis of Marker 509: rs509 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.812637 pvalue = 0.367342 df = 1 ***************************************** RCHI test RCHI statistic value = 0.081331 pvalue = 0.775502 df = 1 ***************************************** RW test RW statistic value = 0.179811 pvalue = 0.671536 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7967 sd = 0.0435 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 allele 2 : freq = 0.2033 sd = 0.0435 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7875 freq = 0.7750 freq = 0.0000 freq = 0.7781 allele 2 : freq = 0.2125 freq = 0.2250 freq = 0.0000 freq = 0.2219 ***************************************** **************************************** Analysis of Marker 510: rs510 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.984171 pvalue = 0.321171 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.395936 pvalue = 0.529195 df = 1 The p-value might not be exact because of the small number of allele 1 in cases ***************************************** RW test RW statistic value = 2.431558 pvalue = 0.118915 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0550 sd = 0.0246 freq = 0.0712 sd = 0.0195 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186 allele 2 : freq = 0.9450 sd = 0.0246 freq = 0.9288 sd = 0.0195 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0500 freq = 0.0667 freq = 0.0000 freq = 0.0625 allele 2 : freq = 0.9500 freq = 0.9333 freq = 0.0000 freq = 0.9375 ***************************************** **************************************** Analysis of Marker 511: rs511 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.014577 pvalue = 0.903902 df = 1 ***************************************** RCHI test RCHI statistic value = 0.064676 pvalue = 0.799253 df = 1 ***************************************** RW test RW statistic value = 0.101964 pvalue = 0.749486 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2167 sd = 0.0445 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 allele 2 : freq = 0.7833 sd = 0.0445 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2000 freq = 0.1896 freq = 0.0000 freq = 0.1922 allele 2 : freq = 0.8000 freq = 0.8104 freq = 0.0000 freq = 0.8078 ***************************************** **************************************** Analysis of Marker 512: rs512 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.483938 pvalue = 0.486644 df = 1 ***************************************** RCHI test RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1 ***************************************** RW test RW statistic value = 0.153753 pvalue = 0.694974 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1983 sd = 0.0431 freq = 0.1558 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 allele 2 : freq = 0.8017 sd = 0.0431 freq = 0.8442 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1792 freq = 0.0000 freq = 0.1812 allele 2 : freq = 0.8125 freq = 0.8208 freq = 0.0000 freq = 0.8187 ***************************************** **************************************** Analysis of Marker 513: rs513 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.027681 pvalue = 0.86786 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.490652 pvalue = 0.483636 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4667 sd = 0.0539 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 allele 2 : freq = 0.5333 sd = 0.0539 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.4500 freq = 0.0000 freq = 0.4500 allele 2 : freq = 0.5500 freq = 0.5500 freq = 0.0000 freq = 0.5500 ***************************************** **************************************** Analysis of Marker 514: rs514 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.739698 pvalue = 0.053134 df = 1 ***************************************** RCHI test RCHI statistic value = 4.155589 pvalue = 0.0414973 df = 1 ***************************************** RW test RW statistic value = 1.006985 pvalue = 0.315626 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4917 sd = 0.0540 freq = 0.5577 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 allele 2 : freq = 0.5083 sd = 0.0540 freq = 0.4423 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4688 freq = 0.5708 freq = 0.0000 freq = 0.5453 allele 2 : freq = 0.5312 freq = 0.4292 freq = 0.0000 freq = 0.4547 ***************************************** **************************************** Analysis of Marker 515: rs515 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.650098 pvalue = 0.420078 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.081320 pvalue = 0.775517 df = 1 The p-value might not be exact because of the small number of allele 2 in cases ***************************************** RW test RW statistic value = 0.024662 pvalue = 0.875212 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9667 sd = 0.0194 freq = 0.9481 sd = 0.0169 freq = 0.0000 sd = 0.0000 freq = 0.9500 sd = 0.0154 allele 2 : freq = 0.0333 sd = 0.0194 freq = 0.0519 sd = 0.0169 freq = 0.0000 sd = 0.0000 freq = 0.0500 sd = 0.0154 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9688 freq = 0.9625 freq = 0.0000 freq = 0.9641 allele 2 : freq = 0.0312 freq = 0.0375 freq = 0.0000 freq = 0.0359 ***************************************** **************************************** Analysis of Marker 516: rs516 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.372719 pvalue = 0.123472 df = 1 ***************************************** RCHI test RCHI statistic value = 1.151907 pvalue = 0.28315 df = 1 ***************************************** RW test RW statistic value = 1.446398 pvalue = 0.229107 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2167 sd = 0.0445 freq = 0.2846 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 allele 2 : freq = 0.7833 sd = 0.0445 freq = 0.7154 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2062 freq = 0.2542 freq = 0.0000 freq = 0.2422 allele 2 : freq = 0.7937 freq = 0.7458 freq = 0.0000 freq = 0.7578 ***************************************** **************************************** Analysis of Marker 517: rs517 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.316755 pvalue = 0.573564 df = 1 ***************************************** RCHI test RCHI statistic value = 0.507058 pvalue = 0.476415 df = 1 ***************************************** RW test RW statistic value = 0.004519 pvalue = 0.946403 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8017 sd = 0.0431 freq = 0.7923 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.1983 sd = 0.0431 freq = 0.2077 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.7771 freq = 0.0000 freq = 0.7844 allele 2 : freq = 0.1938 freq = 0.2229 freq = 0.0000 freq = 0.2156 ***************************************** **************************************** Analysis of Marker 518: rs518 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.051726 pvalue = 0.820086 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 2.320923 pvalue = 0.127644 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0967 sd = 0.0319 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 allele 2 : freq = 0.9033 sd = 0.0319 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1062 freq = 0.1062 freq = 0.0000 freq = 0.1062 allele 2 : freq = 0.8938 freq = 0.8938 freq = 0.0000 freq = 0.8938 ***************************************** **************************************** Analysis of Marker 519: rs519 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.274654 pvalue = 0.600227 df = 1 ***************************************** RCHI test RCHI statistic value = 0.369763 pvalue = 0.543134 df = 1 ***************************************** RW test RW statistic value = 0.252313 pvalue = 0.615451 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6583 sd = 0.0512 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 allele 2 : freq = 0.3417 sd = 0.0512 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6687 freq = 0.6396 freq = 0.0000 freq = 0.6469 allele 2 : freq = 0.3312 freq = 0.3604 freq = 0.0000 freq = 0.3531 ***************************************** **************************************** Analysis of Marker 520: rs520 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.224659 pvalue = 0.635513 df = 1 ***************************************** RCHI test RCHI statistic value = 0.551084 pvalue = 0.457875 df = 1 ***************************************** RW test RW statistic value = 0.052881 pvalue = 0.818124 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2850 sd = 0.0488 freq = 0.2731 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316 allele 2 : freq = 0.7150 sd = 0.0488 freq = 0.7269 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2875 freq = 0.2542 freq = 0.0000 freq = 0.2625 allele 2 : freq = 0.7125 freq = 0.7458 freq = 0.0000 freq = 0.7375 ***************************************** **************************************** Analysis of Marker 521: rs521 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.077220 pvalue = 0.781101 df = 1 ***************************************** RCHI test RCHI statistic value = 0.047482 pvalue = 0.827504 df = 1 ***************************************** RW test RW statistic value = 0.383408 pvalue = 0.535785 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3300 sd = 0.0508 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 allele 2 : freq = 0.6700 sd = 0.0508 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.3146 freq = 0.0000 freq = 0.3172 allele 2 : freq = 0.6750 freq = 0.6854 freq = 0.0000 freq = 0.6828 ***************************************** **************************************** Analysis of Marker 522: rs522 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.060073 pvalue = 0.80638 df = 1 ***************************************** RCHI test RCHI statistic value = 1.179090 pvalue = 0.277541 df = 1 ***************************************** RW test RW statistic value = 0.329552 pvalue = 0.565923 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1033 sd = 0.0329 freq = 0.1038 sd = 0.0232 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202 allele 2 : freq = 0.8967 sd = 0.0329 freq = 0.8962 sd = 0.0232 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0938 freq = 0.1250 freq = 0.0000 freq = 0.1172 allele 2 : freq = 0.9062 freq = 0.8750 freq = 0.0000 freq = 0.8828 ***************************************** **************************************** Analysis of Marker 523: rs523 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.047047 pvalue = 0.828284 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.973768 pvalue = 0.323742 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2683 sd = 0.0479 freq = 0.2442 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 allele 2 : freq = 0.7317 sd = 0.0479 freq = 0.7558 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2562 freq = 0.2562 freq = 0.0000 freq = 0.2562 allele 2 : freq = 0.7438 freq = 0.7438 freq = 0.0000 freq = 0.7438 ***************************************** **************************************** Analysis of Marker 524: rs524 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.097131 pvalue = 0.7553 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002178 pvalue = 0.962781 df = 1 ***************************************** RW test RW statistic value = 0.040178 pvalue = 0.841134 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2900 sd = 0.0490 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 allele 2 : freq = 0.7100 sd = 0.0490 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2875 freq = 0.2896 freq = 0.0000 freq = 0.2891 allele 2 : freq = 0.7125 freq = 0.7104 freq = 0.0000 freq = 0.7109 ***************************************** **************************************** Analysis of Marker 525: rs525 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.058021 pvalue = 0.0803395 df = 1 ***************************************** RCHI test RCHI statistic value = 2.033267 pvalue = 0.15389 df = 1 ***************************************** RW test RW statistic value = 0.666953 pvalue = 0.414116 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2117 sd = 0.0441 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7883 sd = 0.0441 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.2500 freq = 0.0000 freq = 0.2344 allele 2 : freq = 0.8125 freq = 0.7500 freq = 0.0000 freq = 0.7656 ***************************************** **************************************** Analysis of Marker 526: rs526 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.863775 pvalue = 0.352684 df = 1 ***************************************** RCHI test RCHI statistic value = 0.850035 pvalue = 0.356542 df = 1 ***************************************** RW test RW statistic value = 0.479367 pvalue = 0.488709 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4650 sd = 0.0539 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 allele 2 : freq = 0.5350 sd = 0.0539 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4625 freq = 0.4167 freq = 0.0000 freq = 0.4281 allele 2 : freq = 0.5375 freq = 0.5833 freq = 0.0000 freq = 0.5719 ***************************************** **************************************** Analysis of Marker 527: rs527 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.820364 pvalue = 0.365074 df = 1 ***************************************** RCHI test RCHI statistic value = 0.269912 pvalue = 0.603391 df = 1 ***************************************** RW test RW statistic value = 0.029469 pvalue = 0.863702 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6983 sd = 0.0496 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 allele 2 : freq = 0.3017 sd = 0.0496 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.6625 freq = 0.0000 freq = 0.6687 allele 2 : freq = 0.3125 freq = 0.3375 freq = 0.0000 freq = 0.3312 ***************************************** **************************************** Analysis of Marker 528: rs528 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.164046 pvalue = 0.280628 df = 1 ***************************************** RCHI test RCHI statistic value = 4.242175 pvalue = 0.0394316 df = 1 ***************************************** RW test RW statistic value = 7.801450 pvalue = 0.00522043 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3900 sd = 0.0527 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 allele 2 : freq = 0.6100 sd = 0.0527 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3937 freq = 0.2938 freq = 0.0000 freq = 0.3187 allele 2 : freq = 0.6062 freq = 0.7063 freq = 0.0000 freq = 0.6813 ***************************************** **************************************** Analysis of Marker 529: rs529 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.957250 pvalue = 0.327881 df = 1 ***************************************** RCHI test RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1 ***************************************** RW test RW statistic value = 0.803283 pvalue = 0.370114 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3467 sd = 0.0514 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 allele 2 : freq = 0.6533 sd = 0.0514 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3500 freq = 0.3396 freq = 0.0000 freq = 0.3422 allele 2 : freq = 0.6500 freq = 0.6604 freq = 0.0000 freq = 0.6578 ***************************************** **************************************** Analysis of Marker 530: rs530 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.180061 pvalue = 0.277344 df = 1 ***************************************** RCHI test RCHI statistic value = 2.004615 pvalue = 0.156821 df = 1 ***************************************** RW test RW statistic value = 2.958217 pvalue = 0.0854421 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5125 freq = 0.5833 freq = 0.0000 freq = 0.5656 allele 2 : freq = 0.4875 freq = 0.4167 freq = 0.0000 freq = 0.4344 ***************************************** **************************************** Analysis of Marker 531: rs531 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.552487 pvalue = 0.457303 df = 1 ***************************************** RCHI test RCHI statistic value = 2.229778 pvalue = 0.135373 df = 1 ***************************************** RW test RW statistic value = 0.667806 pvalue = 0.413818 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2533 sd = 0.0470 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 allele 2 : freq = 0.7467 sd = 0.0470 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2562 freq = 0.3229 freq = 0.0000 freq = 0.3063 allele 2 : freq = 0.7438 freq = 0.6771 freq = 0.0000 freq = 0.6937 ***************************************** **************************************** Analysis of Marker 532: rs532 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.953974 pvalue = 0.32871 df = 1 ***************************************** RCHI test RCHI statistic value = 0.021486 pvalue = 0.883462 df = 1 ***************************************** RW test RW statistic value = 2.064600 pvalue = 0.150755 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1938 freq = 0.0000 freq = 0.1922 allele 2 : freq = 0.8125 freq = 0.8063 freq = 0.0000 freq = 0.8078 ***************************************** **************************************** Analysis of Marker 533: rs533 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.355257 pvalue = 0.124861 df = 1 ***************************************** RCHI test RCHI statistic value = 3.545929 pvalue = 0.0596917 df = 1 ***************************************** RW test RW statistic value = 2.188817 pvalue = 0.139016 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6150 sd = 0.0526 freq = 0.5519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 allele 2 : freq = 0.3850 sd = 0.0526 freq = 0.4481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6250 freq = 0.5312 freq = 0.0000 freq = 0.5547 allele 2 : freq = 0.3750 freq = 0.4688 freq = 0.0000 freq = 0.4453 ***************************************** **************************************** Analysis of Marker 534: rs534 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.018814 pvalue = 0.890902 df = 1 ***************************************** RCHI test RCHI statistic value = 0.027567 pvalue = 0.86813 df = 1 ***************************************** RW test RW statistic value = 1.295888 pvalue = 0.254966 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4667 sd = 0.0539 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 allele 2 : freq = 0.5333 sd = 0.0539 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 freq = 0.4667 freq = 0.0000 freq = 0.4688 allele 2 : freq = 0.5250 freq = 0.5333 freq = 0.0000 freq = 0.5312 ***************************************** **************************************** Analysis of Marker 535: rs535 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.011260 pvalue = 0.915493 df = 1 ***************************************** RCHI test RCHI statistic value = 0.055390 pvalue = 0.813936 df = 1 ***************************************** RW test RW statistic value = 0.296324 pvalue = 0.586196 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1450 sd = 0.0380 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.8550 sd = 0.0380 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1437 freq = 0.1521 freq = 0.0000 freq = 0.1500 allele 2 : freq = 0.8562 freq = 0.8479 freq = 0.0000 freq = 0.8500 ***************************************** **************************************** Analysis of Marker 536: rs536 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.653553 pvalue = 0.418845 df = 1 ***************************************** RCHI test RCHI statistic value = 0.689949 pvalue = 0.406182 df = 1 ***************************************** RW test RW statistic value = 0.551533 pvalue = 0.457692 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2617 sd = 0.0475 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 allele 2 : freq = 0.7383 sd = 0.0475 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2625 freq = 0.2271 freq = 0.0000 freq = 0.2359 allele 2 : freq = 0.7375 freq = 0.7729 freq = 0.0000 freq = 0.7641 ***************************************** **************************************** Analysis of Marker 537: rs537 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.191992 pvalue = 0.661264 df = 1 ***************************************** RCHI test RCHI statistic value = 0.250110 pvalue = 0.616998 df = 1 ***************************************** RW test RW statistic value = 0.002458 pvalue = 0.960462 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2133 sd = 0.0442 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 allele 2 : freq = 0.7867 sd = 0.0442 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2062 freq = 0.2271 freq = 0.0000 freq = 0.2219 allele 2 : freq = 0.7937 freq = 0.7729 freq = 0.0000 freq = 0.7781 ***************************************** **************************************** Analysis of Marker 538: rs538 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.536791 pvalue = 0.463766 df = 1 ***************************************** RCHI test RCHI statistic value = 1.076849 pvalue = 0.299404 df = 1 ***************************************** RW test RW statistic value = 0.009217 pvalue = 0.923515 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5442 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4558 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5062 freq = 0.5583 freq = 0.0000 freq = 0.5453 allele 2 : freq = 0.4938 freq = 0.4417 freq = 0.0000 freq = 0.4547 ***************************************** **************************************** Analysis of Marker 539: rs539 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.896624 pvalue = 0.343688 df = 1 ***************************************** RCHI test RCHI statistic value = 0.165570 pvalue = 0.684079 df = 1 ***************************************** RW test RW statistic value = 0.734648 pvalue = 0.391381 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7417 sd = 0.0473 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2583 sd = 0.0473 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7500 freq = 0.7667 freq = 0.0000 freq = 0.7625 allele 2 : freq = 0.2500 freq = 0.2333 freq = 0.0000 freq = 0.2375 ***************************************** **************************************** Analysis of Marker 540: rs540 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.065498 pvalue = 0.798007 df = 1 ***************************************** RCHI test RCHI statistic value = 0.016481 pvalue = 0.89785 df = 1 ***************************************** RW test RW statistic value = 0.719741 pvalue = 0.396229 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6300 sd = 0.0521 freq = 0.6404 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.3700 sd = 0.0521 freq = 0.3596 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6375 freq = 0.6312 freq = 0.0000 freq = 0.6328 allele 2 : freq = 0.3625 freq = 0.3688 freq = 0.0000 freq = 0.3672 ***************************************** **************************************** Analysis of Marker 541: rs541 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.352093 pvalue = 0.244913 df = 1 ***************************************** RCHI test RCHI statistic value = 0.514724 pvalue = 0.473101 df = 1 ***************************************** RW test RW statistic value = 0.343014 pvalue = 0.558095 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6467 sd = 0.0516 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 allele 2 : freq = 0.3533 sd = 0.0516 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 freq = 0.6146 freq = 0.0000 freq = 0.6234 allele 2 : freq = 0.3500 freq = 0.3854 freq = 0.0000 freq = 0.3766 ***************************************** **************************************** Analysis of Marker 542: rs542 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.013277 pvalue = 0.908267 df = 1 ***************************************** RCHI test RCHI statistic value = 0.084129 pvalue = 0.771777 df = 1 ***************************************** RW test RW statistic value = 1.586588 pvalue = 0.207814 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5062 freq = 0.4917 freq = 0.0000 freq = 0.4953 allele 2 : freq = 0.4938 freq = 0.5083 freq = 0.0000 freq = 0.5047 ***************************************** **************************************** Analysis of Marker 543: rs543 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.085399 pvalue = 0.77011 df = 1 ***************************************** RCHI test RCHI statistic value = 0.526459 pvalue = 0.468099 df = 1 ***************************************** RW test RW statistic value = 0.229912 pvalue = 0.631589 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1617 sd = 0.0398 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 allele 2 : freq = 0.8383 sd = 0.0398 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1625 freq = 0.1896 freq = 0.0000 freq = 0.1828 allele 2 : freq = 0.8375 freq = 0.8104 freq = 0.0000 freq = 0.8172 ***************************************** **************************************** Analysis of Marker 544: rs544 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.236650 pvalue = 0.134773 df = 1 ***************************************** RCHI test RCHI statistic value = 2.420181 pvalue = 0.119781 df = 1 ***************************************** RW test RW statistic value = 1.968901 pvalue = 0.160565 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3583 sd = 0.0518 freq = 0.4346 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 allele 2 : freq = 0.6417 sd = 0.0518 freq = 0.5654 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3563 freq = 0.4333 freq = 0.0000 freq = 0.4141 allele 2 : freq = 0.6438 freq = 0.5667 freq = 0.0000 freq = 0.5859 ***************************************** **************************************** Analysis of Marker 545: rs545 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000001 pvalue = 0.999228 df = 1 ***************************************** RCHI test RCHI statistic value = 0.015527 pvalue = 0.900835 df = 1 ***************************************** RW test RW statistic value = 0.286489 pvalue = 0.592479 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.5423 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.4577 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5375 freq = 0.5437 freq = 0.0000 freq = 0.5422 allele 2 : freq = 0.4625 freq = 0.4562 freq = 0.0000 freq = 0.4578 ***************************************** **************************************** Analysis of Marker 546: rs546 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.156904 pvalue = 0.14193 df = 1 ***************************************** RCHI test RCHI statistic value = 1.395893 pvalue = 0.237412 df = 1 ***************************************** RW test RW statistic value = 1.017068 pvalue = 0.313216 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1833 sd = 0.0418 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 allele 2 : freq = 0.8167 sd = 0.0418 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.2250 freq = 0.0000 freq = 0.2125 allele 2 : freq = 0.8250 freq = 0.7750 freq = 0.0000 freq = 0.7875 ***************************************** **************************************** Analysis of Marker 547: rs547 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.037221 pvalue = 0.847016 df = 1 ***************************************** RCHI test RCHI statistic value = 0.006873 pvalue = 0.933927 df = 1 ***************************************** RW test RW statistic value = 0.893171 pvalue = 0.34462 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 sd = 0.0539 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 allele 2 : freq = 0.4750 sd = 0.0539 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.5208 freq = 0.0000 freq = 0.5219 allele 2 : freq = 0.4750 freq = 0.4792 freq = 0.0000 freq = 0.4781 ***************************************** **************************************** Analysis of Marker 548: rs548 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.129896 pvalue = 0.71854 df = 1 ***************************************** RCHI test RCHI statistic value = 0.313031 pvalue = 0.575826 df = 1 ***************************************** RW test RW statistic value = 0.678158 pvalue = 0.410222 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.8042 freq = 0.0000 freq = 0.7984 allele 2 : freq = 0.2188 freq = 0.1958 freq = 0.0000 freq = 0.2016 ***************************************** **************************************** Analysis of Marker 549: rs549 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000237 pvalue = 0.987725 df = 1 ***************************************** RCHI test RCHI statistic value = 0.041393 pvalue = 0.838782 df = 1 ***************************************** RW test RW statistic value = 0.734648 pvalue = 0.391381 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7683 sd = 0.0456 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2317 sd = 0.0456 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7875 freq = 0.7792 freq = 0.0000 freq = 0.7812 allele 2 : freq = 0.2125 freq = 0.2208 freq = 0.0000 freq = 0.2188 ***************************************** **************************************** Analysis of Marker 550: rs550 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.462130 pvalue = 0.226591 df = 1 ***************************************** RCHI test RCHI statistic value = 1.210532 pvalue = 0.271227 df = 1 ***************************************** RW test RW statistic value = 4.064317 pvalue = 0.0437984 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7500 sd = 0.0468 freq = 0.7923 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 allele 2 : freq = 0.2500 sd = 0.0468 freq = 0.2077 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7375 freq = 0.7833 freq = 0.0000 freq = 0.7719 allele 2 : freq = 0.2625 freq = 0.2167 freq = 0.0000 freq = 0.2281 ***************************************** **************************************** Analysis of Marker 551: rs551 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.469111 pvalue = 0.493396 df = 1 ***************************************** RCHI test RCHI statistic value = 0.266625 pvalue = 0.605605 df = 1 ***************************************** RW test RW statistic value = 0.365916 pvalue = 0.545239 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 sd = 0.0451 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 allele 2 : freq = 0.2250 sd = 0.0451 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7396 freq = 0.0000 freq = 0.7453 allele 2 : freq = 0.2375 freq = 0.2604 freq = 0.0000 freq = 0.2547 ***************************************** **************************************** Analysis of Marker 552: rs552 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.865190 pvalue = 0.090515 df = 1 ***************************************** RCHI test RCHI statistic value = 2.130537 pvalue = 0.14439 df = 1 ***************************************** RW test RW statistic value = 0.085439 pvalue = 0.770057 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7217 sd = 0.0484 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 allele 2 : freq = 0.2783 sd = 0.0484 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7438 freq = 0.6750 freq = 0.0000 freq = 0.6922 allele 2 : freq = 0.2562 freq = 0.3250 freq = 0.0000 freq = 0.3078 ***************************************** **************************************** Analysis of Marker 553: rs553 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.906849 pvalue = 0.167314 df = 1 ***************************************** RCHI test RCHI statistic value = 2.434755 pvalue = 0.118672 df = 1 ***************************************** RW test RW statistic value = 2.031842 pvalue = 0.154034 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7533 sd = 0.0466 freq = 0.6981 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 allele 2 : freq = 0.2467 sd = 0.0466 freq = 0.3019 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.6917 freq = 0.0000 freq = 0.7094 allele 2 : freq = 0.2375 freq = 0.3083 freq = 0.0000 freq = 0.2906 ***************************************** **************************************** Analysis of Marker 554: rs554 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.015743 pvalue = 0.900151 df = 1 ***************************************** RCHI test RCHI statistic value = 0.148328 pvalue = 0.700139 df = 1 ***************************************** RW test RW statistic value = 0.004998 pvalue = 0.943638 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3683 sd = 0.0521 freq = 0.3731 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 allele 2 : freq = 0.6317 sd = 0.0521 freq = 0.6269 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.3937 freq = 0.0000 freq = 0.3891 allele 2 : freq = 0.6250 freq = 0.6062 freq = 0.0000 freq = 0.6109 ***************************************** **************************************** Analysis of Marker 555: rs555 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.128953 pvalue = 0.71952 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003795 pvalue = 0.95088 df = 1 ***************************************** RW test RW statistic value = 0.324817 pvalue = 0.568727 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8633 sd = 0.0371 freq = 0.8692 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.8700 sd = 0.0238 allele 2 : freq = 0.1367 sd = 0.0371 freq = 0.1308 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.1300 sd = 0.0238 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8562 freq = 0.8583 freq = 0.0000 freq = 0.8578 allele 2 : freq = 0.1437 freq = 0.1417 freq = 0.0000 freq = 0.1422 ***************************************** **************************************** Analysis of Marker 556: rs556 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.459436 pvalue = 0.497887 df = 1 ***************************************** RCHI test RCHI statistic value = 0.178484 pvalue = 0.672679 df = 1 ***************************************** RW test RW statistic value = 0.106094 pvalue = 0.744636 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7200 sd = 0.0485 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 allele 2 : freq = 0.2800 sd = 0.0485 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7063 freq = 0.7250 freq = 0.0000 freq = 0.7203 allele 2 : freq = 0.2938 freq = 0.2750 freq = 0.0000 freq = 0.2797 ***************************************** **************************************** Analysis of Marker 557: rs557 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.247495 pvalue = 0.0715327 df = 1 ***************************************** RCHI test RCHI statistic value = 3.239542 pvalue = 0.0718807 df = 1 ***************************************** RW test RW statistic value = 0.389941 pvalue = 0.53233 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2383 sd = 0.0460 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 allele 2 : freq = 0.7617 sd = 0.0460 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.3208 freq = 0.0000 freq = 0.3000 allele 2 : freq = 0.7625 freq = 0.6792 freq = 0.0000 freq = 0.7000 ***************************************** **************************************** Analysis of Marker 558: rs558 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.774907 pvalue = 0.378703 df = 1 ***************************************** RCHI test RCHI statistic value = 0.877320 pvalue = 0.348937 df = 1 ***************************************** RW test RW statistic value = 1.143080 pvalue = 0.285003 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5717 sd = 0.0534 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 allele 2 : freq = 0.4283 sd = 0.0534 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5813 freq = 0.6271 freq = 0.0000 freq = 0.6156 allele 2 : freq = 0.4188 freq = 0.3729 freq = 0.0000 freq = 0.3844 ***************************************** **************************************** Analysis of Marker 559: rs559 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.756849 pvalue = 0.185018 df = 1 ***************************************** RCHI test RCHI statistic value = 2.288668 pvalue = 0.130322 df = 1 ***************************************** RW test RW statistic value = 0.054417 pvalue = 0.815549 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2567 sd = 0.0472 freq = 0.1981 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 allele 2 : freq = 0.7433 sd = 0.0472 freq = 0.8019 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2562 freq = 0.1938 freq = 0.0000 freq = 0.2094 allele 2 : freq = 0.7438 freq = 0.8063 freq = 0.0000 freq = 0.7906 ***************************************** **************************************** Analysis of Marker 560: rs560 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.275311 pvalue = 0.258773 df = 1 ***************************************** RCHI test RCHI statistic value = 1.532036 pvalue = 0.215807 df = 1 ***************************************** RW test RW statistic value = 2.277075 pvalue = 0.131299 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6533 sd = 0.0514 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 allele 2 : freq = 0.3467 sd = 0.0514 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6625 freq = 0.6021 freq = 0.0000 freq = 0.6172 allele 2 : freq = 0.3375 freq = 0.3979 freq = 0.0000 freq = 0.3828 ***************************************** **************************************** Analysis of Marker 561: rs561 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.567488 pvalue = 0.451259 df = 1 ***************************************** RCHI test RCHI statistic value = 0.278875 pvalue = 0.597439 df = 1 ***************************************** RW test RW statistic value = 2.251871 pvalue = 0.133453 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8417 sd = 0.0394 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.1583 sd = 0.0394 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8167 freq = 0.0000 freq = 0.8219 allele 2 : freq = 0.1625 freq = 0.1833 freq = 0.0000 freq = 0.1781 ***************************************** **************************************** Analysis of Marker 562: rs562 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.154883 pvalue = 0.693912 df = 1 ***************************************** RCHI test RCHI statistic value = 0.112145 pvalue = 0.737715 df = 1 ***************************************** RW test RW statistic value = 0.517302 pvalue = 0.471995 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8150 sd = 0.0419 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 allele 2 : freq = 0.1850 sd = 0.0419 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8125 freq = 0.8000 freq = 0.0000 freq = 0.8031 allele 2 : freq = 0.1875 freq = 0.2000 freq = 0.0000 freq = 0.1969 ***************************************** **************************************** Analysis of Marker 563: rs563 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.041434 pvalue = 0.307488 df = 1 ***************************************** RCHI test RCHI statistic value = 0.431328 pvalue = 0.511338 df = 1 ***************************************** RW test RW statistic value = 0.263091 pvalue = 0.608005 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1050 sd = 0.0331 freq = 0.1423 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8950 sd = 0.0331 freq = 0.8577 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1062 freq = 0.1292 freq = 0.0000 freq = 0.1234 allele 2 : freq = 0.8938 freq = 0.8708 freq = 0.0000 freq = 0.8766 ***************************************** **************************************** Analysis of Marker 564: rs564 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.947658 pvalue = 0.330316 df = 1 ***************************************** RCHI test RCHI statistic value = 1.901084 pvalue = 0.167957 df = 1 ***************************************** RW test RW statistic value = 6.233031 pvalue = 0.0125389 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1833 sd = 0.0418 freq = 0.1519 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.8167 sd = 0.0418 freq = 0.8481 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1938 freq = 0.1417 freq = 0.0000 freq = 0.1547 allele 2 : freq = 0.8063 freq = 0.8583 freq = 0.0000 freq = 0.8453 ***************************************** **************************************** Analysis of Marker 565: rs565 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.759901 pvalue = 0.383359 df = 1 ***************************************** RCHI test RCHI statistic value = 0.565058 pvalue = 0.45223 df = 1 ***************************************** RW test RW statistic value = 0.042842 pvalue = 0.836024 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9000 freq = 0.8750 freq = 0.0000 freq = 0.8812 allele 2 : freq = 0.1000 freq = 0.1250 freq = 0.0000 freq = 0.1187 ***************************************** **************************************** Analysis of Marker 566: rs566 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.918916 pvalue = 0.33776 df = 1 ***************************************** RCHI test RCHI statistic value = 1.346475 pvalue = 0.245895 df = 1 ***************************************** RW test RW statistic value = 0.744218 pvalue = 0.388313 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8200 sd = 0.0415 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1800 sd = 0.0415 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.8667 freq = 0.0000 freq = 0.8562 allele 2 : freq = 0.1750 freq = 0.1333 freq = 0.0000 freq = 0.1437 ***************************************** **************************************** Analysis of Marker 567: rs567 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.404207 pvalue = 0.524925 df = 1 ***************************************** RCHI test RCHI statistic value = 0.700907 pvalue = 0.402479 df = 1 ***************************************** RW test RW statistic value = 1.183910 pvalue = 0.276561 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8100 sd = 0.0424 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 allele 2 : freq = 0.1900 sd = 0.0424 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8187 freq = 0.8500 freq = 0.0000 freq = 0.8422 allele 2 : freq = 0.1812 freq = 0.1500 freq = 0.0000 freq = 0.1578 ***************************************** **************************************** Analysis of Marker 568: rs568 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.899765 pvalue = 0.168105 df = 1 ***************************************** RCHI test RCHI statistic value = 1.869546 pvalue = 0.171527 df = 1 ***************************************** RW test RW statistic value = 4.217234 pvalue = 0.0400153 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5517 sd = 0.0537 freq = 0.4885 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.4483 sd = 0.0537 freq = 0.5115 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5563 freq = 0.4875 freq = 0.0000 freq = 0.5047 allele 2 : freq = 0.4437 freq = 0.5125 freq = 0.0000 freq = 0.4953 ***************************************** **************************************** Analysis of Marker 569: rs569 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.017902 pvalue = 0.893561 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001774 pvalue = 0.966402 df = 1 ***************************************** RW test RW statistic value = 0.564855 pvalue = 0.452311 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.5885 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.4115 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5813 freq = 0.5792 freq = 0.0000 freq = 0.5797 allele 2 : freq = 0.4188 freq = 0.4208 freq = 0.0000 freq = 0.4203 ***************************************** **************************************** Analysis of Marker 570: rs570 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.635900 pvalue = 0.104473 df = 1 ***************************************** RCHI test RCHI statistic value = 1.302353 pvalue = 0.253784 df = 1 ***************************************** RW test RW statistic value = 0.092759 pvalue = 0.760698 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3967 sd = 0.0528 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 allele 2 : freq = 0.6033 sd = 0.0528 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4062 freq = 0.3521 freq = 0.0000 freq = 0.3656 allele 2 : freq = 0.5938 freq = 0.6479 freq = 0.0000 freq = 0.6344 ***************************************** **************************************** Analysis of Marker 571: rs571 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.503332 pvalue = 0.113606 df = 1 ***************************************** RCHI test RCHI statistic value = 1.265446 pvalue = 0.260623 df = 1 ***************************************** RW test RW statistic value = 0.718208 pvalue = 0.396732 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7767 sd = 0.0450 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 allele 2 : freq = 0.2233 sd = 0.0450 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7104 freq = 0.0000 freq = 0.7234 allele 2 : freq = 0.2375 freq = 0.2896 freq = 0.0000 freq = 0.2766 ***************************************** **************************************** Analysis of Marker 572: rs572 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.529549 pvalue = 0.466796 df = 1 ***************************************** RCHI test RCHI statistic value = 1.098066 pvalue = 0.294691 df = 1 ***************************************** RW test RW statistic value = 0.897976 pvalue = 0.343325 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1917 sd = 0.0425 freq = 0.1654 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.8083 sd = 0.0425 freq = 0.8346 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1479 freq = 0.0000 freq = 0.1578 allele 2 : freq = 0.8125 freq = 0.8521 freq = 0.0000 freq = 0.8422 ***************************************** **************************************** Analysis of Marker 573: rs573 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.053207 pvalue = 0.817573 df = 1 ***************************************** RCHI test RCHI statistic value = 0.015677 pvalue = 0.90036 df = 1 ***************************************** RW test RW statistic value = 1.341847 pvalue = 0.246708 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5350 sd = 0.0539 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 allele 2 : freq = 0.4650 sd = 0.0539 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5437 freq = 0.5375 freq = 0.0000 freq = 0.5391 allele 2 : freq = 0.4562 freq = 0.4625 freq = 0.0000 freq = 0.4609 ***************************************** **************************************** Analysis of Marker 574: rs574 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.207416 pvalue = 0.6488 df = 1 ***************************************** RCHI test RCHI statistic value = 0.569032 pvalue = 0.450644 df = 1 ***************************************** RW test RW statistic value = 0.234890 pvalue = 0.627921 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.4500 freq = 0.0000 freq = 0.4406 allele 2 : freq = 0.5875 freq = 0.5500 freq = 0.0000 freq = 0.5594 ***************************************** **************************************** Analysis of Marker 575: rs575 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.129706 pvalue = 0.718737 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002908 pvalue = 0.956996 df = 1 ***************************************** RW test RW statistic value = 0.002857 pvalue = 0.957371 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8417 sd = 0.0394 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 allele 2 : freq = 0.1583 sd = 0.0394 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8396 freq = 0.0000 freq = 0.8391 allele 2 : freq = 0.1625 freq = 0.1604 freq = 0.0000 freq = 0.1609 ***************************************** **************************************** Analysis of Marker 576: rs576 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.878117 pvalue = 0.348718 df = 1 ***************************************** RCHI test RCHI statistic value = 0.833781 pvalue = 0.361181 df = 1 ***************************************** RW test RW statistic value = 2.957594 pvalue = 0.0854751 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6667 sd = 0.0509 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321 allele 2 : freq = 0.3333 sd = 0.0509 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 freq = 0.7167 freq = 0.0000 freq = 0.7063 allele 2 : freq = 0.3250 freq = 0.2833 freq = 0.0000 freq = 0.2938 ***************************************** **************************************** Analysis of Marker 577: rs577 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.258445 pvalue = 0.611191 df = 1 ***************************************** RCHI test RCHI statistic value = 0.950061 pvalue = 0.329704 df = 1 ***************************************** RW test RW statistic value = 0.530200 pvalue = 0.466523 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6083 sd = 0.0527 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.3917 sd = 0.0527 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5938 freq = 0.6417 freq = 0.0000 freq = 0.6297 allele 2 : freq = 0.4062 freq = 0.3583 freq = 0.0000 freq = 0.3703 ***************************************** **************************************** Analysis of Marker 578: rs578 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.779111 pvalue = 0.377413 df = 1 ***************************************** RCHI test RCHI statistic value = 1.492136 pvalue = 0.221885 df = 1 ***************************************** RW test RW statistic value = 0.564855 pvalue = 0.452311 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3800 sd = 0.0524 freq = 0.4115 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 allele 2 : freq = 0.6200 sd = 0.0524 freq = 0.5885 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3812 freq = 0.4417 freq = 0.0000 freq = 0.4266 allele 2 : freq = 0.6188 freq = 0.5583 freq = 0.0000 freq = 0.5734 ***************************************** **************************************** Analysis of Marker 579: rs579 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.007574 pvalue = 0.930648 df = 1 ***************************************** RCHI test RCHI statistic value = 0.211298 pvalue = 0.645752 df = 1 ***************************************** RW test RW statistic value = 0.183219 pvalue = 0.668621 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5687 freq = 0.5917 freq = 0.0000 freq = 0.5859 allele 2 : freq = 0.4313 freq = 0.4083 freq = 0.0000 freq = 0.4141 ***************************************** **************************************** Analysis of Marker 580: rs580 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.279996 pvalue = 0.596704 df = 1 ***************************************** RCHI test RCHI statistic value = 0.284022 pvalue = 0.594077 df = 1 ***************************************** RW test RW statistic value = 5.307935 pvalue = 0.0212285 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3117 sd = 0.0500 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 allele 2 : freq = 0.6883 sd = 0.0500 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3000 freq = 0.3250 freq = 0.0000 freq = 0.3187 allele 2 : freq = 0.7000 freq = 0.6750 freq = 0.0000 freq = 0.6813 ***************************************** **************************************** Analysis of Marker 581: rs581 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.413451 pvalue = 0.120297 df = 1 ***************************************** RCHI test RCHI statistic value = 2.054446 pvalue = 0.151762 df = 1 ***************************************** RW test RW statistic value = 5.272829 pvalue = 0.0216608 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5950 sd = 0.0530 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 allele 2 : freq = 0.4050 sd = 0.0530 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.6562 freq = 0.0000 freq = 0.6391 allele 2 : freq = 0.4125 freq = 0.3438 freq = 0.0000 freq = 0.3609 ***************************************** **************************************** Analysis of Marker 582: rs582 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.386093 pvalue = 0.53436 df = 1 ***************************************** RCHI test RCHI statistic value = 0.149992 pvalue = 0.698543 df = 1 ***************************************** RW test RW statistic value = 0.003235 pvalue = 0.954645 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6017 sd = 0.0529 freq = 0.6365 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340 allele 2 : freq = 0.3983 sd = 0.0529 freq = 0.3635 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6062 freq = 0.6250 freq = 0.0000 freq = 0.6203 allele 2 : freq = 0.3937 freq = 0.3750 freq = 0.0000 freq = 0.3797 ***************************************** **************************************** Analysis of Marker 583: rs583 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.124515 pvalue = 0.724188 df = 1 ***************************************** RCHI test RCHI statistic value = 0.286424 pvalue = 0.592521 df = 1 ***************************************** RW test RW statistic value = 0.000217 pvalue = 0.988242 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6950 sd = 0.0497 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.3050 sd = 0.0497 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 freq = 0.7000 freq = 0.0000 freq = 0.6937 allele 2 : freq = 0.3250 freq = 0.3000 freq = 0.0000 freq = 0.3063 ***************************************** **************************************** Analysis of Marker 584: rs584 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.231961 pvalue = 0.630073 df = 1 ***************************************** RCHI test RCHI statistic value = 0.228272 pvalue = 0.632808 df = 1 ***************************************** RW test RW statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.3462 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.6538 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3688 freq = 0.3458 freq = 0.0000 freq = 0.3516 allele 2 : freq = 0.6312 freq = 0.6542 freq = 0.0000 freq = 0.6484 ***************************************** **************************************** Analysis of Marker 585: rs585 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.386180 pvalue = 0.122412 df = 1 ***************************************** RCHI test RCHI statistic value = 1.676519 pvalue = 0.195388 df = 1 ***************************************** RW test RW statistic value = 0.756767 pvalue = 0.384342 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5700 sd = 0.0535 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339 allele 2 : freq = 0.4300 sd = 0.0535 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.6375 freq = 0.0000 freq = 0.6219 allele 2 : freq = 0.4250 freq = 0.3625 freq = 0.0000 freq = 0.3781 ***************************************** **************************************** Analysis of Marker 586: rs586 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.870077 pvalue = 0.350934 df = 1 ***************************************** RCHI test RCHI statistic value = 1.563187 pvalue = 0.211199 df = 1 ***************************************** RW test RW statistic value = 0.279620 pvalue = 0.596951 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8050 sd = 0.0428 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 allele 2 : freq = 0.1950 sd = 0.0428 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.7542 freq = 0.0000 freq = 0.7672 allele 2 : freq = 0.1938 freq = 0.2458 freq = 0.0000 freq = 0.2328 ***************************************** **************************************** Analysis of Marker 587: rs587 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.403729 pvalue = 0.52517 df = 1 ***************************************** RCHI test RCHI statistic value = 0.777114 pvalue = 0.378025 df = 1 ***************************************** RW test RW statistic value = 1.151624 pvalue = 0.28321 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2783 sd = 0.0484 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316 allele 2 : freq = 0.7217 sd = 0.0484 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2938 freq = 0.2542 freq = 0.0000 freq = 0.2641 allele 2 : freq = 0.7063 freq = 0.7458 freq = 0.0000 freq = 0.7359 ***************************************** **************************************** Analysis of Marker 588: rs588 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.033735 pvalue = 0.854273 df = 1 ***************************************** RCHI test RCHI statistic value = 0.317845 pvalue = 0.572906 df = 1 ***************************************** RW test RW statistic value = 0.524811 pvalue = 0.468797 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8783 sd = 0.0353 freq = 0.8692 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 allele 2 : freq = 0.1217 sd = 0.0353 freq = 0.1308 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8750 freq = 0.8562 freq = 0.0000 freq = 0.8609 allele 2 : freq = 0.1250 freq = 0.1437 freq = 0.0000 freq = 0.1391 ***************************************** **************************************** Analysis of Marker 589: rs589 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.711910 pvalue = 0.39881 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.404622 pvalue = 0.524712 df = 1 The p-value might not be exact because of the small number of allele 2 in cases ***************************************** RW test RW statistic value = 0.923189 pvalue = 0.336639 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9550 sd = 0.0224 freq = 0.9404 sd = 0.0180 freq = 0.0000 sd = 0.0000 freq = 0.9450 sd = 0.0161 allele 2 : freq = 0.0450 sd = 0.0224 freq = 0.0596 sd = 0.0180 freq = 0.0000 sd = 0.0000 freq = 0.0550 sd = 0.0161 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9625 freq = 0.9479 freq = 0.0000 freq = 0.9516 allele 2 : freq = 0.0375 freq = 0.0521 freq = 0.0000 freq = 0.0484 ***************************************** **************************************** Analysis of Marker 590: rs590 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.145439 pvalue = 0.702932 df = 1 ***************************************** RCHI test RCHI statistic value = 0.027471 pvalue = 0.868359 df = 1 ***************************************** RW test RW statistic value = 0.270680 pvalue = 0.602876 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4583 sd = 0.0538 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.5417 sd = 0.0538 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4688 freq = 0.4604 freq = 0.0000 freq = 0.4625 allele 2 : freq = 0.5312 freq = 0.5396 freq = 0.0000 freq = 0.5375 ***************************************** **************************************** Analysis of Marker 591: rs591 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.522136 pvalue = 0.469932 df = 1 ***************************************** RCHI test RCHI statistic value = 0.027869 pvalue = 0.867416 df = 1 ***************************************** RW test RW statistic value = 0.128556 pvalue = 0.719934 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6133 sd = 0.0526 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 allele 2 : freq = 0.3867 sd = 0.0526 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.5917 freq = 0.0000 freq = 0.5938 allele 2 : freq = 0.4000 freq = 0.4083 freq = 0.0000 freq = 0.4062 ***************************************** **************************************** Analysis of Marker 592: rs592 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.054863 pvalue = 0.814807 df = 1 ***************************************** RCHI test RCHI statistic value = 0.269890 pvalue = 0.603405 df = 1 ***************************************** RW test RW statistic value = 0.442453 pvalue = 0.505941 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9000 sd = 0.0324 freq = 0.8885 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 allele 2 : freq = 0.1000 sd = 0.0324 freq = 0.1115 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.8708 freq = 0.0000 freq = 0.8750 allele 2 : freq = 0.1125 freq = 0.1292 freq = 0.0000 freq = 0.1250 ***************************************** **************************************** Analysis of Marker 593: rs593 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.025694 pvalue = 0.872649 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002320 pvalue = 0.961582 df = 1 ***************************************** RW test RW statistic value = 0.559587 pvalue = 0.454427 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7417 sd = 0.0473 freq = 0.7654 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.2583 sd = 0.0473 freq = 0.2346 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7604 freq = 0.0000 freq = 0.7609 allele 2 : freq = 0.2375 freq = 0.2396 freq = 0.0000 freq = 0.2391 ***************************************** **************************************** Analysis of Marker 594: rs594 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.069021 pvalue = 0.301167 df = 1 ***************************************** RCHI test RCHI statistic value = 0.633879 pvalue = 0.425936 df = 1 ***************************************** RW test RW statistic value = 5.131702 pvalue = 0.0234927 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7188 freq = 0.6813 freq = 0.0000 freq = 0.6906 allele 2 : freq = 0.2812 freq = 0.3187 freq = 0.0000 freq = 0.3094 ***************************************** **************************************** Analysis of Marker 595: rs595 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.646905 pvalue = 0.421222 df = 1 ***************************************** RCHI test RCHI statistic value = 0.386889 pvalue = 0.533939 df = 1 ***************************************** RW test RW statistic value = 1.588972 pvalue = 0.207473 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4200 sd = 0.0533 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.5800 sd = 0.0533 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4437 freq = 0.4750 freq = 0.0000 freq = 0.4672 allele 2 : freq = 0.5563 freq = 0.5250 freq = 0.0000 freq = 0.5328 ***************************************** **************************************** Analysis of Marker 596: rs596 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.097922 pvalue = 0.754337 df = 1 ***************************************** RCHI test RCHI statistic value = 0.015550 pvalue = 0.90076 df = 1 ***************************************** RW test RW statistic value = 0.950934 pvalue = 0.329482 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5350 sd = 0.0539 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 allele 2 : freq = 0.4650 sd = 0.0539 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5188 freq = 0.5125 freq = 0.0000 freq = 0.5141 allele 2 : freq = 0.4813 freq = 0.4875 freq = 0.0000 freq = 0.4859 ***************************************** **************************************** Analysis of Marker 597: rs597 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.299914 pvalue = 0.583936 df = 1 ***************************************** RCHI test RCHI statistic value = 0.372258 pvalue = 0.541776 df = 1 ***************************************** RW test RW statistic value = 0.365783 pvalue = 0.545312 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 sd = 0.0506 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 allele 2 : freq = 0.6750 sd = 0.0506 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.3542 freq = 0.0000 freq = 0.3469 allele 2 : freq = 0.6750 freq = 0.6458 freq = 0.0000 freq = 0.6531 ***************************************** **************************************** Analysis of Marker 598: rs598 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.026654 pvalue = 0.870312 df = 1 ***************************************** RCHI test RCHI statistic value = 0.251137 pvalue = 0.616276 df = 1 ***************************************** RW test RW statistic value = 0.385576 pvalue = 0.534634 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1150 sd = 0.0345 freq = 0.1327 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 allele 2 : freq = 0.8850 sd = 0.0345 freq = 0.8673 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1250 freq = 0.1417 freq = 0.0000 freq = 0.1375 allele 2 : freq = 0.8750 freq = 0.8583 freq = 0.0000 freq = 0.8625 ***************************************** **************************************** Analysis of Marker 599: rs599 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.554408 pvalue = 0.456522 df = 1 ***************************************** RCHI test RCHI statistic value = 0.254296 pvalue = 0.614066 df = 1 ***************************************** RW test RW statistic value = 2.199161 pvalue = 0.138086 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.7771 freq = 0.0000 freq = 0.7719 allele 2 : freq = 0.2437 freq = 0.2229 freq = 0.0000 freq = 0.2281 ***************************************** **************************************** Analysis of Marker 600: rs600 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.216549 pvalue = 0.641682 df = 1 ***************************************** RCHI test RCHI statistic value = 0.317306 pvalue = 0.573231 df = 1 ***************************************** RW test RW statistic value = 2.217147 pvalue = 0.136485 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7417 sd = 0.0473 freq = 0.7250 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 allele 2 : freq = 0.2583 sd = 0.0473 freq = 0.2750 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7500 freq = 0.7250 freq = 0.0000 freq = 0.7312 allele 2 : freq = 0.2500 freq = 0.2750 freq = 0.0000 freq = 0.2687 ***************************************** **************************************** Analysis of Marker 601: rs601 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.361945 pvalue = 0.0667192 df = 1 ***************************************** RCHI test RCHI statistic value = 1.823796 pvalue = 0.176862 df = 1 ***************************************** RW test RW statistic value = 0.280789 pvalue = 0.596184 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4783 sd = 0.0540 freq = 0.4173 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 allele 2 : freq = 0.5217 sd = 0.0540 freq = 0.5827 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4875 freq = 0.4208 freq = 0.0000 freq = 0.4375 allele 2 : freq = 0.5125 freq = 0.5792 freq = 0.0000 freq = 0.5625 ***************************************** **************************************** Analysis of Marker 602: rs602 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 6.110609 pvalue = 0.0134373 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 4.079976 pvalue = 0.0433943 df = 1 ***************************************** RW test RW statistic value = 3.873119 pvalue = 0.0490653 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2817 sd = 0.0486 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 allele 2 : freq = 0.7183 sd = 0.0486 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2875 freq = 0.2062 freq = 0.0000 freq = 0.2266 allele 2 : freq = 0.7125 freq = 0.7937 freq = 0.0000 freq = 0.7734 ***************************************** **************************************** Analysis of Marker 603: rs603 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.103172 pvalue = 0.748056 df = 1 ***************************************** RCHI test RCHI statistic value = 0.042919 pvalue = 0.835878 df = 1 ***************************************** RW test RW statistic value = 0.732159 pvalue = 0.392184 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 sd = 0.0451 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 allele 2 : freq = 0.7750 sd = 0.0451 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2188 freq = 0.2271 freq = 0.0000 freq = 0.2250 allele 2 : freq = 0.7812 freq = 0.7729 freq = 0.0000 freq = 0.7750 ***************************************** **************************************** Analysis of Marker 604: rs604 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.273839 pvalue = 0.259048 df = 1 ***************************************** RCHI test RCHI statistic value = 2.225137 pvalue = 0.135781 df = 1 ***************************************** RW test RW statistic value = 0.060734 pvalue = 0.805339 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4650 sd = 0.0539 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.5350 sd = 0.0539 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.5312 freq = 0.0000 freq = 0.5125 allele 2 : freq = 0.5437 freq = 0.4688 freq = 0.0000 freq = 0.4875 ***************************************** **************************************** Analysis of Marker 605: rs605 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.683322 pvalue = 0.194484 df = 1 ***************************************** RCHI test RCHI statistic value = 1.648706 pvalue = 0.199135 df = 1 ***************************************** RW test RW statistic value = 0.921955 pvalue = 0.336962 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8700 sd = 0.0363 freq = 0.9038 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217 allele 2 : freq = 0.1300 sd = 0.0363 freq = 0.0962 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8625 freq = 0.9021 freq = 0.0000 freq = 0.8922 allele 2 : freq = 0.1375 freq = 0.0979 freq = 0.0000 freq = 0.1078 ***************************************** **************************************** Analysis of Marker 606: rs606 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.069914 pvalue = 0.15023 df = 1 ***************************************** RCHI test RCHI statistic value = 3.306542 pvalue = 0.0690046 df = 1 ***************************************** RW test RW statistic value = 2.362432 pvalue = 0.124288 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5283 sd = 0.0539 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 allele 2 : freq = 0.4717 sd = 0.0539 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5500 freq = 0.6396 freq = 0.0000 freq = 0.6172 allele 2 : freq = 0.4500 freq = 0.3604 freq = 0.0000 freq = 0.3828 ***************************************** **************************************** Analysis of Marker 607: rs607 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000433 pvalue = 0.983393 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.193498 pvalue = 0.660021 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4633 sd = 0.0539 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 allele 2 : freq = 0.5367 sd = 0.0539 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.4562 freq = 0.0000 freq = 0.4562 allele 2 : freq = 0.5437 freq = 0.5437 freq = 0.0000 freq = 0.5437 ***************************************** **************************************** Analysis of Marker 608: rs608 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.136730 pvalue = 0.0234247 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 3.492684 pvalue = 0.0616406 df = 1 ***************************************** RW test RW statistic value = 0.189284 pvalue = 0.663513 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4683 sd = 0.0539 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 allele 2 : freq = 0.5317 sd = 0.0539 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4875 freq = 0.3958 freq = 0.0000 freq = 0.4188 allele 2 : freq = 0.5125 freq = 0.6042 freq = 0.0000 freq = 0.5813 ***************************************** **************************************** Analysis of Marker 609: rs609 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.890169 pvalue = 0.345432 df = 1 ***************************************** RCHI test RCHI statistic value = 0.996301 pvalue = 0.318207 df = 1 ***************************************** RW test RW statistic value = 0.179811 pvalue = 0.671536 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7233 sd = 0.0483 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 allele 2 : freq = 0.2767 sd = 0.0483 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7125 freq = 0.7562 freq = 0.0000 freq = 0.7453 allele 2 : freq = 0.2875 freq = 0.2437 freq = 0.0000 freq = 0.2547 ***************************************** **************************************** Analysis of Marker 610: rs610 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.871296 pvalue = 0.350597 df = 1 ***************************************** RCHI test RCHI statistic value = 0.638192 pvalue = 0.424366 df = 1 ***************************************** RW test RW statistic value = 0.293569 pvalue = 0.587942 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6033 sd = 0.0528 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 allele 2 : freq = 0.3967 sd = 0.0528 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6250 freq = 0.5854 freq = 0.0000 freq = 0.5953 allele 2 : freq = 0.3750 freq = 0.4146 freq = 0.0000 freq = 0.4047 ***************************************** **************************************** Analysis of Marker 611: rs611 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.221442 pvalue = 0.637943 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002543 pvalue = 0.959781 df = 1 ***************************************** RW test RW statistic value = 0.009995 pvalue = 0.920364 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7646 freq = 0.0000 freq = 0.7641 allele 2 : freq = 0.2375 freq = 0.2354 freq = 0.0000 freq = 0.2359 ***************************************** **************************************** Analysis of Marker 612: rs612 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 7.067292 pvalue = 0.00785038 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 7.627688 pvalue = 0.0057479 df = 1 ***************************************** RW test RW statistic value = 7.800898 pvalue = 0.00522203 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3417 sd = 0.0512 freq = 0.4346 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 allele 2 : freq = 0.6583 sd = 0.0512 freq = 0.5654 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.4625 freq = 0.0000 freq = 0.4281 allele 2 : freq = 0.6750 freq = 0.5375 freq = 0.0000 freq = 0.5719 ***************************************** **************************************** Analysis of Marker 613: rs613 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.460772 pvalue = 0.497263 df = 1 ***************************************** RCHI test RCHI statistic value = 1.140882 pvalue = 0.285466 df = 1 ***************************************** RW test RW statistic value = 0.823619 pvalue = 0.364124 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8217 sd = 0.0413 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.1783 sd = 0.0413 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.7625 freq = 0.0000 freq = 0.7734 allele 2 : freq = 0.1938 freq = 0.2375 freq = 0.0000 freq = 0.2266 ***************************************** **************************************** Analysis of Marker 614: rs614 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.640947 pvalue = 0.423368 df = 1 ***************************************** RCHI test RCHI statistic value = 1.282332 pvalue = 0.257466 df = 1 ***************************************** RW test RW statistic value = 0.248894 pvalue = 0.617855 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7950 sd = 0.0436 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 allele 2 : freq = 0.2050 sd = 0.0436 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 freq = 0.8438 freq = 0.0000 freq = 0.8328 allele 2 : freq = 0.2000 freq = 0.1562 freq = 0.0000 freq = 0.1672 ***************************************** **************************************** Analysis of Marker 615: rs615 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.061676 pvalue = 0.803866 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.107598 pvalue = 0.742896 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8200 sd = 0.0415 freq = 0.8192 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.1800 sd = 0.0415 freq = 0.1808 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8187 freq = 0.8187 freq = 0.0000 freq = 0.8187 allele 2 : freq = 0.1812 freq = 0.1812 freq = 0.0000 freq = 0.1812 ***************************************** **************************************** Analysis of Marker 616: rs616 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.553986 pvalue = 0.456694 df = 1 ***************************************** RCHI test RCHI statistic value = 1.545590 pvalue = 0.213788 df = 1 ***************************************** RW test RW statistic value = 0.042186 pvalue = 0.837265 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1667 sd = 0.0403 freq = 0.1519 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 allele 2 : freq = 0.8333 sd = 0.0403 freq = 0.8481 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.1292 freq = 0.0000 freq = 0.1406 allele 2 : freq = 0.8250 freq = 0.8708 freq = 0.0000 freq = 0.8594 ***************************************** **************************************** Analysis of Marker 617: rs617 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.102926 pvalue = 0.147018 df = 1 ***************************************** RCHI test RCHI statistic value = 3.632654 pvalue = 0.0566564 df = 1 ***************************************** RW test RW statistic value = 2.699030 pvalue = 0.100409 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.5458 freq = 0.0000 freq = 0.5219 allele 2 : freq = 0.5500 freq = 0.4542 freq = 0.0000 freq = 0.4781 ***************************************** **************************************** Analysis of Marker 618: rs618 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.659194 pvalue = 0.416845 df = 1 ***************************************** RCHI test RCHI statistic value = 0.337327 pvalue = 0.561376 df = 1 ***************************************** RW test RW statistic value = 0.568405 pvalue = 0.450894 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5533 sd = 0.0537 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 allele 2 : freq = 0.4467 sd = 0.0537 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5625 freq = 0.5333 freq = 0.0000 freq = 0.5406 allele 2 : freq = 0.4375 freq = 0.4667 freq = 0.0000 freq = 0.4594 ***************************************** **************************************** Analysis of Marker 619: rs619 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.784122 pvalue = 0.181644 df = 1 ***************************************** RCHI test RCHI statistic value = 1.053386 pvalue = 0.304729 df = 1 ***************************************** RW test RW statistic value = 0.001150 pvalue = 0.972947 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8317 sd = 0.0404 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 allele 2 : freq = 0.1683 sd = 0.0404 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8021 freq = 0.0000 freq = 0.8125 allele 2 : freq = 0.1562 freq = 0.1979 freq = 0.0000 freq = 0.1875 ***************************************** **************************************** Analysis of Marker 620: rs620 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.300589 pvalue = 0.129325 df = 1 ***************************************** RCHI test RCHI statistic value = 0.207748 pvalue = 0.648538 df = 1 ***************************************** RW test RW statistic value = 0.630586 pvalue = 0.42714 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5783 sd = 0.0533 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 allele 2 : freq = 0.4217 sd = 0.0533 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.5646 freq = 0.0000 freq = 0.5703 allele 2 : freq = 0.4125 freq = 0.4354 freq = 0.0000 freq = 0.4297 ***************************************** **************************************** Analysis of Marker 621: rs621 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.117262 pvalue = 0.732023 df = 1 ***************************************** RCHI test RCHI statistic value = 0.444872 pvalue = 0.50478 df = 1 ***************************************** RW test RW statistic value = 0.206614 pvalue = 0.649434 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5583 sd = 0.0536 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 allele 2 : freq = 0.4417 sd = 0.0536 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5625 freq = 0.5292 freq = 0.0000 freq = 0.5375 allele 2 : freq = 0.4375 freq = 0.4708 freq = 0.0000 freq = 0.4625 ***************************************** **************************************** Analysis of Marker 622: rs622 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.858202 pvalue = 0.354242 df = 1 ***************************************** RCHI test RCHI statistic value = 0.192277 pvalue = 0.661029 df = 1 ***************************************** RW test RW statistic value = 0.385576 pvalue = 0.534634 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9133 sd = 0.0304 freq = 0.8827 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 allele 2 : freq = 0.0867 sd = 0.0304 freq = 0.1173 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9062 freq = 0.8917 freq = 0.0000 freq = 0.8953 allele 2 : freq = 0.0938 freq = 0.1083 freq = 0.0000 freq = 0.1047 ***************************************** **************************************** Analysis of Marker 623: rs623 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.843838 pvalue = 0.358302 df = 1 ***************************************** RCHI test RCHI statistic value = 0.454770 pvalue = 0.500079 df = 1 ***************************************** RW test RW statistic value = 0.198604 pvalue = 0.65585 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7083 sd = 0.0491 freq = 0.7712 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.2917 sd = 0.0491 freq = 0.2288 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7188 freq = 0.7479 freq = 0.0000 freq = 0.7406 allele 2 : freq = 0.2812 freq = 0.2521 freq = 0.0000 freq = 0.2594 ***************************************** **************************************** Analysis of Marker 624: rs624 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.284936 pvalue = 0.593484 df = 1 ***************************************** RCHI test RCHI statistic value = 0.788950 pvalue = 0.374418 df = 1 ***************************************** RW test RW statistic value = 1.862482 pvalue = 0.172339 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7050 sd = 0.0493 freq = 0.6673 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 allele 2 : freq = 0.2950 sd = 0.0493 freq = 0.3327 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.6521 freq = 0.0000 freq = 0.6625 allele 2 : freq = 0.3063 freq = 0.3479 freq = 0.0000 freq = 0.3375 ***************************************** **************************************** Analysis of Marker 625: rs625 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.023802 pvalue = 0.311619 df = 1 ***************************************** RCHI test RCHI statistic value = 0.581890 pvalue = 0.445572 df = 1 ***************************************** RW test RW statistic value = 2.503742 pvalue = 0.113576 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3400 sd = 0.0512 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6600 sd = 0.0512 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3500 freq = 0.3875 freq = 0.0000 freq = 0.3781 allele 2 : freq = 0.6500 freq = 0.6125 freq = 0.0000 freq = 0.6219 ***************************************** **************************************** Analysis of Marker 626: rs626 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.062478 pvalue = 0.802622 df = 1 ***************************************** RCHI test RCHI statistic value = 0.112161 pvalue = 0.737697 df = 1 ***************************************** RW test RW statistic value = 0.306140 pvalue = 0.580059 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2750 sd = 0.0482 freq = 0.2635 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.7250 sd = 0.0482 freq = 0.7365 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2687 freq = 0.2833 freq = 0.0000 freq = 0.2797 allele 2 : freq = 0.7312 freq = 0.7167 freq = 0.0000 freq = 0.7203 ***************************************** **************************************** Analysis of Marker 627: rs627 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.064130 pvalue = 0.800084 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001989 pvalue = 0.964427 df = 1 ***************************************** RW test RW statistic value = 0.945958 pvalue = 0.33075 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3150 sd = 0.0502 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.6850 sd = 0.0502 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3000 freq = 0.2979 freq = 0.0000 freq = 0.2984 allele 2 : freq = 0.7000 freq = 0.7021 freq = 0.0000 freq = 0.7016 ***************************************** **************************************** Analysis of Marker 628: rs628 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.602546 pvalue = 0.437608 df = 1 ***************************************** RCHI test RCHI statistic value = 0.882903 pvalue = 0.347408 df = 1 ***************************************** RW test RW statistic value = 0.867545 pvalue = 0.351636 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1333 sd = 0.0367 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 allele 2 : freq = 0.8667 sd = 0.0367 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1437 freq = 0.1125 freq = 0.0000 freq = 0.1203 allele 2 : freq = 0.8562 freq = 0.8875 freq = 0.0000 freq = 0.8797 ***************************************** **************************************** Analysis of Marker 629: rs629 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.003727 pvalue = 0.951322 df = 1 ***************************************** RCHI test RCHI statistic value = 0.063427 pvalue = 0.801159 df = 1 ***************************************** RW test RW statistic value = 0.424916 pvalue = 0.514494 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.5904 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349 allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.4096 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5813 freq = 0.5938 freq = 0.0000 freq = 0.5906 allele 2 : freq = 0.4188 freq = 0.4062 freq = 0.0000 freq = 0.4094 ***************************************** **************************************** Analysis of Marker 630: rs630 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.072670 pvalue = 0.787488 df = 1 ***************************************** RCHI test RCHI statistic value = 0.199365 pvalue = 0.655234 df = 1 ***************************************** RW test RW statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2317 sd = 0.0456 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 allele 2 : freq = 0.7683 sd = 0.0456 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2313 freq = 0.2125 freq = 0.0000 freq = 0.2172 allele 2 : freq = 0.7688 freq = 0.7875 freq = 0.0000 freq = 0.7828 ***************************************** **************************************** Analysis of Marker 631: rs631 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.046571 pvalue = 0.0246747 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 4.265996 pvalue = 0.0388824 df = 1 ***************************************** RW test RW statistic value = 0.509058 pvalue = 0.475547 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 sd = 0.0432 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 allele 2 : freq = 0.2000 sd = 0.0432 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8187 freq = 0.7271 freq = 0.0000 freq = 0.7500 allele 2 : freq = 0.1812 freq = 0.2729 freq = 0.0000 freq = 0.2500 ***************************************** **************************************** Analysis of Marker 632: rs632 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.902747 pvalue = 0.342046 df = 1 ***************************************** RCHI test RCHI statistic value = 3.051875 pvalue = 0.080644 df = 1 ***************************************** RW test RW statistic value = 0.368249 pvalue = 0.54396 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6817 sd = 0.0503 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327 allele 2 : freq = 0.3183 sd = 0.0503 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6687 freq = 0.7500 freq = 0.0000 freq = 0.7297 allele 2 : freq = 0.3312 freq = 0.2500 freq = 0.0000 freq = 0.2703 ***************************************** **************************************** Analysis of Marker 633: rs633 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.283633 pvalue = 0.59433 df = 1 ***************************************** RCHI test RCHI statistic value = 0.180092 pvalue = 0.671294 df = 1 ***************************************** RW test RW statistic value = 0.000401 pvalue = 0.984018 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8950 sd = 0.0331 freq = 0.8615 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 allele 2 : freq = 0.1050 sd = 0.0331 freq = 0.1385 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8812 freq = 0.8667 freq = 0.0000 freq = 0.8703 allele 2 : freq = 0.1187 freq = 0.1333 freq = 0.0000 freq = 0.1297 ***************************************** **************************************** Analysis of Marker 634: rs634 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.656944 pvalue = 0.198016 df = 1 ***************************************** RCHI test RCHI statistic value = 1.138553 pvalue = 0.285958 df = 1 ***************************************** RW test RW statistic value = 0.892811 pvalue = 0.344717 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3267 sd = 0.0507 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 allele 2 : freq = 0.6733 sd = 0.0507 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.3771 freq = 0.0000 freq = 0.3641 allele 2 : freq = 0.6750 freq = 0.6229 freq = 0.0000 freq = 0.6359 ***************************************** **************************************** Analysis of Marker 635: rs635 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 7.926986 pvalue = 0.00487029 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 8.120998 pvalue = 0.00437555 df = 1 ***************************************** RW test RW statistic value = 2.761156 pvalue = 0.0965785 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6883 sd = 0.0500 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 allele 2 : freq = 0.3117 sd = 0.0500 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.5458 freq = 0.0000 freq = 0.5813 allele 2 : freq = 0.3125 freq = 0.4542 freq = 0.0000 freq = 0.4188 ***************************************** **************************************** Analysis of Marker 636: rs636 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.266372 pvalue = 0.605776 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001751 pvalue = 0.966622 df = 1 ***************************************** RW test RW statistic value = 3.588252 pvalue = 0.0581894 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5900 sd = 0.0531 freq = 0.5712 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 allele 2 : freq = 0.4100 sd = 0.0531 freq = 0.4288 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.5979 freq = 0.0000 freq = 0.5984 allele 2 : freq = 0.4000 freq = 0.4021 freq = 0.0000 freq = 0.4016 ***************************************** **************************************** Analysis of Marker 637: rs637 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.402967 pvalue = 0.236227 df = 1 ***************************************** RCHI test RCHI statistic value = 2.128783 pvalue = 0.144555 df = 1 ***************************************** RW test RW statistic value = 0.350808 pvalue = 0.553656 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4867 sd = 0.0540 freq = 0.4231 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.5133 sd = 0.0540 freq = 0.5769 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4875 freq = 0.4146 freq = 0.0000 freq = 0.4328 allele 2 : freq = 0.5125 freq = 0.5854 freq = 0.0000 freq = 0.5672 ***************************************** **************************************** Analysis of Marker 638: rs638 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.208182 pvalue = 0.648196 df = 1 ***************************************** RCHI test RCHI statistic value = 0.192277 pvalue = 0.661029 df = 1 ***************************************** RW test RW statistic value = 0.010710 pvalue = 0.917573 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0983 sd = 0.0322 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 allele 2 : freq = 0.9017 sd = 0.0322 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1125 freq = 0.1271 freq = 0.0000 freq = 0.1234 allele 2 : freq = 0.8875 freq = 0.8729 freq = 0.0000 freq = 0.8766 ***************************************** **************************************** Analysis of Marker 639: rs639 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.781639 pvalue = 0.0953505 df = 1 ***************************************** RCHI test RCHI statistic value = 2.051022 pvalue = 0.152104 df = 1 ***************************************** RW test RW statistic value = 0.130947 pvalue = 0.717452 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4767 sd = 0.0539 freq = 0.3962 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 allele 2 : freq = 0.5233 sd = 0.0539 freq = 0.6038 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4813 freq = 0.4104 freq = 0.0000 freq = 0.4281 allele 2 : freq = 0.5188 freq = 0.5896 freq = 0.0000 freq = 0.5719 ***************************************** **************************************** Analysis of Marker 640: rs640 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.137396 pvalue = 0.710884 df = 1 ***************************************** RCHI test RCHI statistic value = 0.288871 pvalue = 0.590945 df = 1 ***************************************** RW test RW statistic value = 0.094094 pvalue = 0.759035 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7733 sd = 0.0452 freq = 0.7462 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 allele 2 : freq = 0.2267 sd = 0.0452 freq = 0.2538 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 freq = 0.7521 freq = 0.0000 freq = 0.7578 allele 2 : freq = 0.2250 freq = 0.2479 freq = 0.0000 freq = 0.2422 ***************************************** **************************************** Analysis of Marker 641: rs641 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.974299 pvalue = 0.0461997 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 5.947033 pvalue = 0.0147421 df = 1 ***************************************** RW test RW statistic value = 0.718192 pvalue = 0.396737 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.4646 freq = 0.0000 freq = 0.4344 allele 2 : freq = 0.6562 freq = 0.5354 freq = 0.0000 freq = 0.5656 ***************************************** **************************************** Analysis of Marker 642: rs642 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.060945 pvalue = 0.805008 df = 1 ***************************************** RCHI test RCHI statistic value = 0.140193 pvalue = 0.708089 df = 1 ***************************************** RW test RW statistic value = 0.148147 pvalue = 0.700312 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.5558 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.4442 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5375 freq = 0.5563 freq = 0.0000 freq = 0.5516 allele 2 : freq = 0.4625 freq = 0.4437 freq = 0.0000 freq = 0.4484 ***************************************** **************************************** Analysis of Marker 643: rs643 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.037970 pvalue = 0.845503 df = 1 ***************************************** RCHI test RCHI statistic value = 0.027493 pvalue = 0.868307 df = 1 ***************************************** RW test RW statistic value = 0.082732 pvalue = 0.773628 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.5083 freq = 0.0000 freq = 0.5062 allele 2 : freq = 0.5000 freq = 0.4917 freq = 0.0000 freq = 0.4938 ***************************************** **************************************** Analysis of Marker 644: rs644 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.091304 pvalue = 0.762526 df = 1 ***************************************** RCHI test RCHI statistic value = 1.345228 pvalue = 0.246114 df = 1 ***************************************** RW test RW statistic value = 0.266809 pvalue = 0.60548 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2317 sd = 0.0456 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 allele 2 : freq = 0.7683 sd = 0.0456 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2188 freq = 0.2667 freq = 0.0000 freq = 0.2547 allele 2 : freq = 0.7812 freq = 0.7333 freq = 0.0000 freq = 0.7453 ***************************************** **************************************** Analysis of Marker 645: rs645 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.415914 pvalue = 0.019954 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 7.935860 pvalue = 0.00484646 df = 1 ***************************************** RW test RW statistic value = 1.778786 pvalue = 0.182298 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6367 sd = 0.0519 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 allele 2 : freq = 0.3633 sd = 0.0519 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6687 freq = 0.5292 freq = 0.0000 freq = 0.5641 allele 2 : freq = 0.3312 freq = 0.4708 freq = 0.0000 freq = 0.4359 ***************************************** **************************************** Analysis of Marker 646: rs646 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.625272 pvalue = 0.202358 df = 1 ***************************************** RCHI test RCHI statistic value = 1.166235 pvalue = 0.280176 df = 1 ***************************************** RW test RW statistic value = 0.743629 pvalue = 0.388501 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6367 sd = 0.0519 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 allele 2 : freq = 0.3633 sd = 0.0519 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6438 freq = 0.6937 freq = 0.0000 freq = 0.6813 allele 2 : freq = 0.3563 freq = 0.3063 freq = 0.0000 freq = 0.3187 ***************************************** **************************************** Analysis of Marker 647: rs647 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.846730 pvalue = 0.174164 df = 1 ***************************************** RCHI test RCHI statistic value = 0.418890 pvalue = 0.517492 df = 1 ***************************************** RW test RW statistic value = 0.003402 pvalue = 0.953491 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1800 sd = 0.0415 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.8200 sd = 0.0415 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1938 freq = 0.1708 freq = 0.0000 freq = 0.1766 allele 2 : freq = 0.8063 freq = 0.8292 freq = 0.0000 freq = 0.8234 ***************************************** **************************************** Analysis of Marker 648: rs648 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.067379 pvalue = 0.795192 df = 1 ***************************************** RCHI test RCHI statistic value = 0.171951 pvalue = 0.678384 df = 1 ***************************************** RW test RW statistic value = 0.147183 pvalue = 0.701242 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5125 freq = 0.5333 freq = 0.0000 freq = 0.5281 allele 2 : freq = 0.4875 freq = 0.4667 freq = 0.0000 freq = 0.4719 ***************************************** **************************************** Analysis of Marker 649: rs649 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.174973 pvalue = 0.278382 df = 1 ***************************************** RCHI test RCHI statistic value = 2.952292 pvalue = 0.0857559 df = 1 ***************************************** RW test RW statistic value = 0.939560 pvalue = 0.332391 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3933 sd = 0.0528 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 allele 2 : freq = 0.6067 sd = 0.0528 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3937 freq = 0.4792 freq = 0.0000 freq = 0.4578 allele 2 : freq = 0.6062 freq = 0.5208 freq = 0.0000 freq = 0.5422 ***************************************** **************************************** Analysis of Marker 650: rs650 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.082382 pvalue = 0.774095 df = 1 ***************************************** RCHI test RCHI statistic value = 0.652905 pvalue = 0.419076 df = 1 ***************************************** RW test RW statistic value = 0.568292 pvalue = 0.450939 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2617 sd = 0.0475 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7383 sd = 0.0475 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2562 freq = 0.2208 freq = 0.0000 freq = 0.2297 allele 2 : freq = 0.7438 freq = 0.7792 freq = 0.0000 freq = 0.7703 ***************************************** **************************************** Analysis of Marker 651: rs651 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.100954 pvalue = 0.750688 df = 1 ***************************************** RCHI test RCHI statistic value = 0.757165 pvalue = 0.384217 df = 1 ***************************************** RW test RW statistic value = 0.000750 pvalue = 0.978155 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5312 freq = 0.5750 freq = 0.0000 freq = 0.5641 allele 2 : freq = 0.4688 freq = 0.4250 freq = 0.0000 freq = 0.4359 ***************************************** **************************************** Analysis of Marker 652: rs652 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.062080 pvalue = 0.803238 df = 1 ***************************************** RCHI test RCHI statistic value = 0.474992 pvalue = 0.4907 df = 1 ***************************************** RW test RW statistic value = 0.085726 pvalue = 0.769683 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7688 freq = 0.7979 freq = 0.0000 freq = 0.7906 allele 2 : freq = 0.2313 freq = 0.2021 freq = 0.0000 freq = 0.2094 ***************************************** **************************************** Analysis of Marker 653: rs653 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.003518 pvalue = 0.316461 df = 1 ***************************************** RCHI test RCHI statistic value = 1.213165 pvalue = 0.270706 df = 1 ***************************************** RW test RW statistic value = 4.128990 pvalue = 0.0421545 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7683 sd = 0.0456 freq = 0.6904 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 allele 2 : freq = 0.2317 sd = 0.0456 freq = 0.3096 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7500 freq = 0.7000 freq = 0.0000 freq = 0.7125 allele 2 : freq = 0.2500 freq = 0.3000 freq = 0.0000 freq = 0.2875 ***************************************** **************************************** Analysis of Marker 654: rs654 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.088050 pvalue = 0.766671 df = 1 ***************************************** RCHI test RCHI statistic value = 0.043269 pvalue = 0.835219 df = 1 ***************************************** RW test RW statistic value = 0.848256 pvalue = 0.357046 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5383 sd = 0.0538 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 allele 2 : freq = 0.4617 sd = 0.0538 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5312 freq = 0.5417 freq = 0.0000 freq = 0.5391 allele 2 : freq = 0.4688 freq = 0.4583 freq = 0.0000 freq = 0.4609 ***************************************** **************************************** Analysis of Marker 655: rs655 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.479960 pvalue = 0.48844 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.098984 pvalue = 0.753052 df = 1 The p-value might not be exact because of the small number of allele 1 in cases ***************************************** RW test RW statistic value = 0.151972 pvalue = 0.696658 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0567 sd = 0.0250 freq = 0.0615 sd = 0.0183 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186 allele 2 : freq = 0.9433 sd = 0.0250 freq = 0.9385 sd = 0.0183 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0563 freq = 0.0646 freq = 0.0000 freq = 0.0625 allele 2 : freq = 0.9437 freq = 0.9354 freq = 0.0000 freq = 0.9375 ***************************************** **************************************** Analysis of Marker 656: rs656 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.418917 pvalue = 0.517478 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003924 pvalue = 0.950052 df = 1 ***************************************** RW test RW statistic value = 0.042842 pvalue = 0.836024 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1533 sd = 0.0389 freq = 0.1212 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 allele 2 : freq = 0.8467 sd = 0.0389 freq = 0.8788 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1500 freq = 0.1479 freq = 0.0000 freq = 0.1484 allele 2 : freq = 0.8500 freq = 0.8521 freq = 0.0000 freq = 0.8516 ***************************************** **************************************** Analysis of Marker 657: rs657 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.072679 pvalue = 0.300341 df = 1 ***************************************** RCHI test RCHI statistic value = 2.522676 pvalue = 0.11222 df = 1 ***************************************** RW test RW statistic value = 0.117145 pvalue = 0.732151 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9167 sd = 0.0299 freq = 0.8865 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212 allele 2 : freq = 0.0833 sd = 0.0299 freq = 0.1135 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9187 freq = 0.8708 freq = 0.0000 freq = 0.8828 allele 2 : freq = 0.0813 freq = 0.1292 freq = 0.0000 freq = 0.1172 ***************************************** **************************************** Analysis of Marker 658: rs658 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.221600 pvalue = 0.269047 df = 1 ***************************************** RCHI test RCHI statistic value = 0.004064 pvalue = 0.949168 df = 1 ***************************************** RW test RW statistic value = 0.454382 pvalue = 0.500261 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8450 sd = 0.0391 freq = 0.8692 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.8800 sd = 0.0230 allele 2 : freq = 0.1550 sd = 0.0391 freq = 0.1308 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.1200 sd = 0.0230 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8396 freq = 0.0000 freq = 0.8391 allele 2 : freq = 0.1625 freq = 0.1604 freq = 0.0000 freq = 0.1609 ***************************************** **************************************** Analysis of Marker 659: rs659 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.072904 pvalue = 0.787154 df = 1 ***************************************** RCHI test RCHI statistic value = 0.160070 pvalue = 0.689092 df = 1 ***************************************** RW test RW statistic value = 0.078916 pvalue = 0.778772 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2083 sd = 0.0439 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 allele 2 : freq = 0.7917 sd = 0.0439 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2000 freq = 0.1833 freq = 0.0000 freq = 0.1875 allele 2 : freq = 0.8000 freq = 0.8167 freq = 0.0000 freq = 0.8125 ***************************************** **************************************** Analysis of Marker 660: rs660 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.629719 pvalue = 0.10488 df = 1 ***************************************** RCHI test RCHI statistic value = 3.640288 pvalue = 0.0563972 df = 1 ***************************************** RW test RW statistic value = 0.866079 pvalue = 0.352043 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.2788 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.7212 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3500 freq = 0.2625 freq = 0.0000 freq = 0.2844 allele 2 : freq = 0.6500 freq = 0.7375 freq = 0.0000 freq = 0.7156 ***************************************** **************************************** Analysis of Marker 661: rs661 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.561566 pvalue = 0.45363 df = 1 ***************************************** RCHI test RCHI statistic value = 0.457801 pvalue = 0.498653 df = 1 ***************************************** RW test RW statistic value = 0.078097 pvalue = 0.779893 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.4154 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.5846 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3688 freq = 0.4021 freq = 0.0000 freq = 0.3937 allele 2 : freq = 0.6312 freq = 0.5979 freq = 0.0000 freq = 0.6062 ***************************************** **************************************** Analysis of Marker 662: rs662 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.127653 pvalue = 0.288277 df = 1 ***************************************** RCHI test RCHI statistic value = 2.139177 pvalue = 0.143579 df = 1 ***************************************** RW test RW statistic value = 0.289986 pvalue = 0.59023 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5817 sd = 0.0533 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 allele 2 : freq = 0.4183 sd = 0.0533 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.5271 freq = 0.0000 freq = 0.5453 allele 2 : freq = 0.4000 freq = 0.4729 freq = 0.0000 freq = 0.4547 ***************************************** **************************************** Analysis of Marker 663: rs663 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.055373 pvalue = 0.813965 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001717 pvalue = 0.966944 df = 1 ***************************************** RW test RW statistic value = 0.126755 pvalue = 0.72182 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5400 sd = 0.0538 freq = 0.5000 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 allele 2 : freq = 0.4600 sd = 0.0538 freq = 0.5000 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.5271 freq = 0.0000 freq = 0.5266 allele 2 : freq = 0.4750 freq = 0.4729 freq = 0.0000 freq = 0.4734 ***************************************** **************************************** Analysis of Marker 664: rs664 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.301193 pvalue = 0.129275 df = 1 ***************************************** RCHI test RCHI statistic value = 3.098062 pvalue = 0.0783855 df = 1 ***************************************** RW test RW statistic value = 3.494588 pvalue = 0.0615697 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3583 sd = 0.0518 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 allele 2 : freq = 0.6417 sd = 0.0518 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3688 freq = 0.4562 freq = 0.0000 freq = 0.4344 allele 2 : freq = 0.6312 freq = 0.5437 freq = 0.0000 freq = 0.5656 ***************************************** **************************************** Analysis of Marker 665: rs665 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.009262 pvalue = 0.923329 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001956 pvalue = 0.96472 df = 1 ***************************************** RW test RW statistic value = 0.021360 pvalue = 0.883803 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6687 freq = 0.6667 freq = 0.0000 freq = 0.6672 allele 2 : freq = 0.3312 freq = 0.3333 freq = 0.0000 freq = 0.3328 ***************************************** **************************************** Analysis of Marker 666: rs666 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.383920 pvalue = 0.535513 df = 1 ***************************************** RCHI test RCHI statistic value = 0.029990 pvalue = 0.862512 df = 1 ***************************************** RW test RW statistic value = 0.013097 pvalue = 0.908887 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6100 sd = 0.0527 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 allele 2 : freq = 0.3900 sd = 0.0527 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6125 freq = 0.6208 freq = 0.0000 freq = 0.6188 allele 2 : freq = 0.3875 freq = 0.3792 freq = 0.0000 freq = 0.3812 ***************************************** **************************************** Analysis of Marker 667: rs667 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.261434 pvalue = 0.609137 df = 1 ***************************************** RCHI test RCHI statistic value = 0.029990 pvalue = 0.862512 df = 1 ***************************************** RW test RW statistic value = 0.452057 pvalue = 0.50136 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6200 sd = 0.0524 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 allele 2 : freq = 0.3800 sd = 0.0524 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6188 freq = 0.6271 freq = 0.0000 freq = 0.6250 allele 2 : freq = 0.3812 freq = 0.3729 freq = 0.0000 freq = 0.3750 ***************************************** **************************************** Analysis of Marker 668: rs668 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.777304 pvalue = 0.377967 df = 1 ***************************************** RCHI test RCHI statistic value = 1.309252 pvalue = 0.25253 df = 1 ***************************************** RW test RW statistic value = 0.345885 pvalue = 0.556452 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4183 sd = 0.0533 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.5817 sd = 0.0533 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 freq = 0.3688 freq = 0.0000 freq = 0.3828 allele 2 : freq = 0.5750 freq = 0.6312 freq = 0.0000 freq = 0.6172 ***************************************** **************************************** Analysis of Marker 669: rs669 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 7.283962 pvalue = 0.00695729 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 6.288114 pvalue = 0.012155 df = 1 ***************************************** RW test RW statistic value = 4.623934 pvalue = 0.0315288 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2033 sd = 0.0435 freq = 0.1288 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.7967 sd = 0.0435 freq = 0.8712 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2188 freq = 0.1313 freq = 0.0000 freq = 0.1531 allele 2 : freq = 0.7812 freq = 0.8688 freq = 0.0000 freq = 0.8469 ***************************************** **************************************** Analysis of Marker 670: rs670 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.567990 pvalue = 0.0589036 df = 1 ***************************************** RCHI test RCHI statistic value = 4.756081 pvalue = 0.0291949 df = 1 ***************************************** RW test RW statistic value = 0.798416 pvalue = 0.371567 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0950 sd = 0.0317 freq = 0.0558 sd = 0.0174 freq = 0.0000 sd = 0.0000 freq = 0.0600 sd = 0.0168 allele 2 : freq = 0.9050 sd = 0.0317 freq = 0.9442 sd = 0.0174 freq = 0.0000 sd = 0.0000 freq = 0.9400 sd = 0.0168 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0938 freq = 0.0417 freq = 0.0000 freq = 0.0547 allele 2 : freq = 0.9062 freq = 0.9583 freq = 0.0000 freq = 0.9453 ***************************************** **************************************** Analysis of Marker 671: rs671 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.885934 pvalue = 0.346582 df = 1 ***************************************** RCHI test RCHI statistic value = 0.156051 pvalue = 0.692818 df = 1 ***************************************** RW test RW statistic value = 0.659621 pvalue = 0.416694 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5933 sd = 0.0531 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 allele 2 : freq = 0.4067 sd = 0.0531 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6188 freq = 0.6375 freq = 0.0000 freq = 0.6328 allele 2 : freq = 0.3812 freq = 0.3625 freq = 0.0000 freq = 0.3672 ***************************************** **************************************** Analysis of Marker 672: rs672 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.482975 pvalue = 0.487078 df = 1 ***************************************** RCHI test RCHI statistic value = 0.938573 pvalue = 0.332645 df = 1 ***************************************** RW test RW statistic value = 0.069929 pvalue = 0.79144 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.4173 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.5827 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3875 freq = 0.4354 freq = 0.0000 freq = 0.4234 allele 2 : freq = 0.6125 freq = 0.5646 freq = 0.0000 freq = 0.5766 ***************************************** **************************************** Analysis of Marker 673: rs673 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.250755 pvalue = 0.263408 df = 1 ***************************************** RCHI test RCHI statistic value = 0.741638 pvalue = 0.389137 df = 1 ***************************************** RW test RW statistic value = 0.099964 pvalue = 0.751873 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.2538 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.7462 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2938 freq = 0.2562 freq = 0.0000 freq = 0.2656 allele 2 : freq = 0.7063 freq = 0.7438 freq = 0.0000 freq = 0.7344 ***************************************** **************************************** Analysis of Marker 674: rs674 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.131535 pvalue = 0.716846 df = 1 ***************************************** RCHI test RCHI statistic value = 0.113551 pvalue = 0.736137 df = 1 ***************************************** RW test RW statistic value = 0.409888 pvalue = 0.522026 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5667 sd = 0.0535 freq = 0.5846 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.4333 sd = 0.0535 freq = 0.4154 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.5917 freq = 0.0000 freq = 0.5875 allele 2 : freq = 0.4250 freq = 0.4083 freq = 0.0000 freq = 0.4125 ***************************************** **************************************** Analysis of Marker 675: rs675 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.182281 pvalue = 0.66942 df = 1 ***************************************** RCHI test RCHI statistic value = 0.117968 pvalue = 0.731249 df = 1 ***************************************** RW test RW statistic value = 0.389605 pvalue = 0.532507 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8200 sd = 0.0415 freq = 0.8615 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 allele 2 : freq = 0.1800 sd = 0.0415 freq = 0.1385 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8313 freq = 0.8438 freq = 0.0000 freq = 0.8406 allele 2 : freq = 0.1688 freq = 0.1562 freq = 0.0000 freq = 0.1594 ***************************************** **************************************** Analysis of Marker 676: rs676 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.116459 pvalue = 0.290682 df = 1 ***************************************** RCHI test RCHI statistic value = 1.286853 pvalue = 0.256629 df = 1 ***************************************** RW test RW statistic value = 0.014011 pvalue = 0.905777 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1500 sd = 0.0386 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8500 sd = 0.0386 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1688 freq = 0.1292 freq = 0.0000 freq = 0.1391 allele 2 : freq = 0.8313 freq = 0.8708 freq = 0.0000 freq = 0.8609 ***************************************** **************************************** Analysis of Marker 677: rs677 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.441113 pvalue = 0.0635928 df = 1 ***************************************** RCHI test RCHI statistic value = 1.955797 pvalue = 0.161964 df = 1 ***************************************** RW test RW statistic value = 3.468454 pvalue = 0.0625497 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3333 sd = 0.0509 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6667 sd = 0.0509 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3125 freq = 0.3812 freq = 0.0000 freq = 0.3641 allele 2 : freq = 0.6875 freq = 0.6188 freq = 0.0000 freq = 0.6359 ***************************************** **************************************** Analysis of Marker 678: rs678 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 9.589246 pvalue = 0.0019572 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 9.314497 pvalue = 0.00227348 df = 1 ***************************************** RW test RW statistic value = 5.468119 pvalue = 0.0193665 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 sd = 0.0451 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 allele 2 : freq = 0.7750 sd = 0.0451 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2062 freq = 0.3500 freq = 0.0000 freq = 0.3141 allele 2 : freq = 0.7937 freq = 0.6500 freq = 0.0000 freq = 0.6859 ***************************************** **************************************** Analysis of Marker 679: rs679 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.358969 pvalue = 0.54908 df = 1 ***************************************** RCHI test RCHI statistic value = 0.019160 pvalue = 0.889908 df = 1 ***************************************** RW test RW statistic value = 0.318198 pvalue = 0.572692 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7500 freq = 0.7438 freq = 0.0000 freq = 0.7453 allele 2 : freq = 0.2500 freq = 0.2562 freq = 0.0000 freq = 0.2547 ***************************************** **************************************** Analysis of Marker 680: rs680 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.150469 pvalue = 0.698088 df = 1 ***************************************** RCHI test RCHI statistic value = 1.417707 pvalue = 0.233781 df = 1 ***************************************** RW test RW statistic value = 0.429953 pvalue = 0.512012 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7700 sd = 0.0455 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 allele 2 : freq = 0.2300 sd = 0.0455 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 freq = 0.8250 freq = 0.0000 freq = 0.8125 allele 2 : freq = 0.2250 freq = 0.1750 freq = 0.0000 freq = 0.1875 ***************************************** **************************************** Analysis of Marker 681: rs681 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.079865 pvalue = 0.298728 df = 1 ***************************************** RCHI test RCHI statistic value = 0.668624 pvalue = 0.413532 df = 1 ***************************************** RW test RW statistic value = 0.109048 pvalue = 0.74123 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6583 sd = 0.0512 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 allele 2 : freq = 0.3417 sd = 0.0512 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6625 freq = 0.7000 freq = 0.0000 freq = 0.6906 allele 2 : freq = 0.3375 freq = 0.3000 freq = 0.0000 freq = 0.3094 ***************************************** **************************************** Analysis of Marker 682: rs682 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.261661 pvalue = 0.608981 df = 1 ***************************************** RCHI test RCHI statistic value = 0.757165 pvalue = 0.384217 df = 1 ***************************************** RW test RW statistic value = 0.414080 pvalue = 0.519906 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4933 sd = 0.0540 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.5067 sd = 0.0540 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4813 freq = 0.5250 freq = 0.0000 freq = 0.5141 allele 2 : freq = 0.5188 freq = 0.4750 freq = 0.0000 freq = 0.4859 ***************************************** **************************************** Analysis of Marker 683: rs683 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.016310 pvalue = 0.898379 df = 1 ***************************************** RCHI test RCHI statistic value = 0.341400 pvalue = 0.559022 df = 1 ***************************************** RW test RW statistic value = 0.037274 pvalue = 0.846909 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4437 freq = 0.4729 freq = 0.0000 freq = 0.4656 allele 2 : freq = 0.5563 freq = 0.5271 freq = 0.0000 freq = 0.5344 ***************************************** **************************************** Analysis of Marker 684: rs684 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.064575 pvalue = 0.799405 df = 1 ***************************************** RCHI test RCHI statistic value = 0.194671 pvalue = 0.659057 df = 1 ***************************************** RW test RW statistic value = 1.276561 pvalue = 0.258539 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8233 sd = 0.0412 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.1767 sd = 0.0412 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.8417 freq = 0.0000 freq = 0.8375 allele 2 : freq = 0.1750 freq = 0.1583 freq = 0.0000 freq = 0.1625 ***************************************** **************************************** Analysis of Marker 685: rs685 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.002263 pvalue = 0.962055 df = 1 ***************************************** RCHI test RCHI statistic value = 0.074292 pvalue = 0.785188 df = 1 ***************************************** RW test RW statistic value = 0.065114 pvalue = 0.798589 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2850 sd = 0.0488 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 allele 2 : freq = 0.7150 sd = 0.0488 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2875 freq = 0.2750 freq = 0.0000 freq = 0.2781 allele 2 : freq = 0.7125 freq = 0.7250 freq = 0.0000 freq = 0.7219 ***************************************** **************************************** Analysis of Marker 686: rs686 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.126398 pvalue = 0.722197 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 1.862482 pvalue = 0.172339 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3050 sd = 0.0497 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 allele 2 : freq = 0.6950 sd = 0.0497 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3000 freq = 0.3000 freq = 0.0000 freq = 0.3000 allele 2 : freq = 0.7000 freq = 0.7000 freq = 0.0000 freq = 0.7000 ***************************************** **************************************** Analysis of Marker 687: rs687 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.009061 pvalue = 0.315128 df = 1 ***************************************** RCHI test RCHI statistic value = 2.053262 pvalue = 0.15188 df = 1 ***************************************** RW test RW statistic value = 0.099632 pvalue = 0.752272 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1383 sd = 0.0373 freq = 0.1346 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8617 sd = 0.0373 freq = 0.8654 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1625 freq = 0.1125 freq = 0.0000 freq = 0.1250 allele 2 : freq = 0.8375 freq = 0.8875 freq = 0.0000 freq = 0.8750 ***************************************** **************************************** Analysis of Marker 688: rs688 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.806753 pvalue = 0.369082 df = 1 ***************************************** RCHI test RCHI statistic value = 0.830993 pvalue = 0.361986 df = 1 ***************************************** RW test RW statistic value = 0.609029 pvalue = 0.435153 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4767 sd = 0.0539 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 allele 2 : freq = 0.5233 sd = 0.0539 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4688 freq = 0.5146 freq = 0.0000 freq = 0.5031 allele 2 : freq = 0.5312 freq = 0.4854 freq = 0.0000 freq = 0.4969 ***************************************** **************************************** Analysis of Marker 689: rs689 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.094825 pvalue = 0.295405 df = 1 ***************************************** RCHI test RCHI statistic value = 1.030394 pvalue = 0.310066 df = 1 ***************************************** RW test RW statistic value = 3.808155 pvalue = 0.0510036 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6700 sd = 0.0508 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.3300 sd = 0.0508 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6813 freq = 0.7271 freq = 0.0000 freq = 0.7156 allele 2 : freq = 0.3187 freq = 0.2729 freq = 0.0000 freq = 0.2844 ***************************************** **************************************** Analysis of Marker 690: rs690 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.039548 pvalue = 0.842367 df = 1 ***************************************** RCHI test RCHI statistic value = 0.455949 pvalue = 0.499523 df = 1 ***************************************** RW test RW statistic value = 0.000778 pvalue = 0.97775 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4183 sd = 0.0533 freq = 0.4096 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 allele 2 : freq = 0.5817 sd = 0.0533 freq = 0.5904 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4062 freq = 0.4396 freq = 0.0000 freq = 0.4313 allele 2 : freq = 0.5938 freq = 0.5604 freq = 0.0000 freq = 0.5687 ***************************************** **************************************** Analysis of Marker 691: rs691 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.018578 pvalue = 0.891584 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003924 pvalue = 0.950052 df = 1 ***************************************** RW test RW statistic value = 0.096394 pvalue = 0.756201 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1192 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8808 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1187 freq = 0.1167 freq = 0.0000 freq = 0.1172 allele 2 : freq = 0.8812 freq = 0.8833 freq = 0.0000 freq = 0.8828 ***************************************** **************************************** Analysis of Marker 692: rs692 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.683933 pvalue = 0.101365 df = 1 ***************************************** RCHI test RCHI statistic value = 2.535042 pvalue = 0.111344 df = 1 ***************************************** RW test RW statistic value = 0.051756 pvalue = 0.820036 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6800 sd = 0.0504 freq = 0.6288 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340 allele 2 : freq = 0.3200 sd = 0.0504 freq = 0.3712 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7000 freq = 0.6229 freq = 0.0000 freq = 0.6422 allele 2 : freq = 0.3000 freq = 0.3771 freq = 0.0000 freq = 0.3578 ***************************************** **************************************** Analysis of Marker 693: rs693 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.515076 pvalue = 0.218366 df = 1 ***************************************** RCHI test RCHI statistic value = 0.892899 pvalue = 0.344693 df = 1 ***************************************** RW test RW statistic value = 0.037358 pvalue = 0.846737 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3300 sd = 0.0508 freq = 0.3115 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 allele 2 : freq = 0.6700 sd = 0.0508 freq = 0.6885 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3563 freq = 0.3125 freq = 0.0000 freq = 0.3234 allele 2 : freq = 0.6438 freq = 0.6875 freq = 0.0000 freq = 0.6766 ***************************************** **************************************** Analysis of Marker 694: rs694 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.193904 pvalue = 0.274543 df = 1 ***************************************** RCHI test RCHI statistic value = 1.822243 pvalue = 0.177047 df = 1 ***************************************** RW test RW statistic value = 0.240729 pvalue = 0.62368 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7100 sd = 0.0490 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 allele 2 : freq = 0.2900 sd = 0.0490 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7312 freq = 0.6687 freq = 0.0000 freq = 0.6844 allele 2 : freq = 0.2687 freq = 0.3312 freq = 0.0000 freq = 0.3156 ***************************************** **************************************** Analysis of Marker 695: rs695 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.584777 pvalue = 0.107896 df = 1 ***************************************** RCHI test RCHI statistic value = 2.145068 pvalue = 0.143029 df = 1 ***************************************** RW test RW statistic value = 0.000765 pvalue = 0.977938 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3850 sd = 0.0526 freq = 0.4269 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 allele 2 : freq = 0.6150 sd = 0.0526 freq = 0.5731 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.4354 freq = 0.0000 freq = 0.4172 allele 2 : freq = 0.6375 freq = 0.5646 freq = 0.0000 freq = 0.5828 ***************************************** **************************************** Analysis of Marker 696: rs696 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.325073 pvalue = 0.568575 df = 1 ***************************************** RCHI test RCHI statistic value = 0.008516 pvalue = 0.926475 df = 1 ***************************************** RW test RW statistic value = 0.182226 pvalue = 0.669467 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3267 sd = 0.0507 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 allele 2 : freq = 0.6733 sd = 0.0507 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3125 freq = 0.3167 freq = 0.0000 freq = 0.3156 allele 2 : freq = 0.6875 freq = 0.6833 freq = 0.0000 freq = 0.6844 ***************************************** **************************************** Analysis of Marker 697: rs697 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.082591 pvalue = 0.773816 df = 1 ***************************************** RCHI test RCHI statistic value = 0.139113 pvalue = 0.709165 df = 1 ***************************************** RW test RW statistic value = 0.126755 pvalue = 0.72182 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4833 sd = 0.0540 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 allele 2 : freq = 0.5167 sd = 0.0540 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.4813 freq = 0.0000 freq = 0.4859 allele 2 : freq = 0.5000 freq = 0.5188 freq = 0.0000 freq = 0.5141 ***************************************** **************************************** Analysis of Marker 698: rs698 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.003853 pvalue = 0.950505 df = 1 ***************************************** RCHI test RCHI statistic value = 0.042919 pvalue = 0.835878 df = 1 ***************************************** RW test RW statistic value = 0.885912 pvalue = 0.346588 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7950 sd = 0.0436 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 allele 2 : freq = 0.2050 sd = 0.0436 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7937 freq = 0.7854 freq = 0.0000 freq = 0.7875 allele 2 : freq = 0.2062 freq = 0.2146 freq = 0.0000 freq = 0.2125 ***************************************** **************************************** Analysis of Marker 699: rs699 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.773972 pvalue = 0.378991 df = 1 ***************************************** RCHI test RCHI statistic value = 0.625900 pvalue = 0.428863 df = 1 ***************************************** RW test RW statistic value = 0.586076 pvalue = 0.443941 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8300 sd = 0.0406 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 allele 2 : freq = 0.1700 sd = 0.0406 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8125 freq = 0.8417 freq = 0.0000 freq = 0.8344 allele 2 : freq = 0.1875 freq = 0.1583 freq = 0.0000 freq = 0.1656 ***************************************** **************************************** Analysis of Marker 700: rs700 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.046110 pvalue = 0.829975 df = 1 ***************************************** RCHI test RCHI statistic value = 0.275415 pvalue = 0.599722 df = 1 ***************************************** RW test RW statistic value = 0.501366 pvalue = 0.478901 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3583 sd = 0.0518 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335 allele 2 : freq = 0.6417 sd = 0.0518 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3625 freq = 0.0000 freq = 0.3563 allele 2 : freq = 0.6625 freq = 0.6375 freq = 0.0000 freq = 0.6438 ***************************************** **************************************** Analysis of Marker 701: rs701 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.343641 pvalue = 0.246393 df = 1 ***************************************** RCHI test RCHI statistic value = 2.263162 pvalue = 0.132483 df = 1 ***************************************** RW test RW statistic value = 1.757073 pvalue = 0.18499 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4700 sd = 0.0539 freq = 0.4058 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.5300 sd = 0.0539 freq = 0.5942 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 freq = 0.4000 freq = 0.0000 freq = 0.4188 allele 2 : freq = 0.5250 freq = 0.6000 freq = 0.0000 freq = 0.5813 ***************************************** **************************************** Analysis of Marker 702: rs702 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.344033 pvalue = 0.246324 df = 1 ***************************************** RCHI test RCHI statistic value = 2.909432 pvalue = 0.0880629 df = 1 ***************************************** RW test RW statistic value = 0.510957 pvalue = 0.474725 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4300 sd = 0.0535 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 allele 2 : freq = 0.5700 sd = 0.0535 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4188 freq = 0.5042 freq = 0.0000 freq = 0.4828 allele 2 : freq = 0.5813 freq = 0.4958 freq = 0.0000 freq = 0.5172 ***************************************** **************************************** Analysis of Marker 703: rs703 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.084500 pvalue = 0.297693 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** RCHI test RCHI statistic value = 0.616388 pvalue = 0.432393 df = 1 The p-value might not be exact because of the small number of allele 1 in cases ***************************************** RW test RW statistic value = 1.608464 pvalue = 0.204708 df = 1 The p-value might not be exact because of the small number of type 1 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0300 sd = 0.0184 freq = 0.0577 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.0600 sd = 0.0168 allele 2 : freq = 0.9700 sd = 0.0184 freq = 0.9423 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.9400 sd = 0.0168 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0375 freq = 0.0563 freq = 0.0000 freq = 0.0516 allele 2 : freq = 0.9625 freq = 0.9437 freq = 0.0000 freq = 0.9484 ***************************************** **************************************** Analysis of Marker 704: rs704 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.777159 pvalue = 0.378011 df = 1 ***************************************** RCHI test RCHI statistic value = 0.869817 pvalue = 0.351006 df = 1 ***************************************** RW test RW statistic value = 0.001938 pvalue = 0.964886 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6867 sd = 0.0501 freq = 0.6788 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 allele 2 : freq = 0.3133 sd = 0.0501 freq = 0.3212 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7125 freq = 0.6687 freq = 0.0000 freq = 0.6797 allele 2 : freq = 0.2875 freq = 0.3312 freq = 0.0000 freq = 0.3203 ***************************************** **************************************** Analysis of Marker 705: rs705 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.093294 pvalue = 0.295743 df = 1 ***************************************** RCHI test RCHI statistic value = 1.666466 pvalue = 0.196733 df = 1 ***************************************** RW test RW statistic value = 2.503835 pvalue = 0.113569 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4217 sd = 0.0533 freq = 0.4481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.5783 sd = 0.0533 freq = 0.5519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.4771 freq = 0.0000 freq = 0.4609 allele 2 : freq = 0.5875 freq = 0.5229 freq = 0.0000 freq = 0.5391 ***************************************** **************************************** Analysis of Marker 706: rs706 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.149105 pvalue = 0.0416565 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 4.680014 pvalue = 0.0305155 df = 1 ***************************************** RW test RW statistic value = 3.810254 pvalue = 0.0509397 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.4833 freq = 0.0000 freq = 0.4562 allele 2 : freq = 0.6250 freq = 0.5167 freq = 0.0000 freq = 0.5437 ***************************************** **************************************** Analysis of Marker 707: rs707 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.016829 pvalue = 0.896782 df = 1 ***************************************** RCHI test RCHI statistic value = 0.286424 pvalue = 0.592521 df = 1 ***************************************** RW test RW statistic value = 0.281442 pvalue = 0.595758 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7000 sd = 0.0495 freq = 0.6981 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.3000 sd = 0.0495 freq = 0.3019 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.7125 freq = 0.0000 freq = 0.7063 allele 2 : freq = 0.3125 freq = 0.2875 freq = 0.0000 freq = 0.2938 ***************************************** **************************************** Analysis of Marker 708: rs708 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.328663 pvalue = 0.127011 df = 1 ***************************************** RCHI test RCHI statistic value = 2.098021 pvalue = 0.14749 df = 1 ***************************************** RW test RW statistic value = 7.121219 pvalue = 0.00761769 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2633 sd = 0.0476 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 allele 2 : freq = 0.7367 sd = 0.0476 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2750 freq = 0.3438 freq = 0.0000 freq = 0.3266 allele 2 : freq = 0.7250 freq = 0.6562 freq = 0.0000 freq = 0.6734 ***************************************** **************************************** Analysis of Marker 709: rs709 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.537602 pvalue = 0.463428 df = 1 ***************************************** RCHI test RCHI statistic value = 0.124628 pvalue = 0.724068 df = 1 ***************************************** RW test RW statistic value = 0.024190 pvalue = 0.876403 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1250 sd = 0.0357 freq = 0.1365 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.8750 sd = 0.0357 freq = 0.8635 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1187 freq = 0.1313 freq = 0.0000 freq = 0.1281 allele 2 : freq = 0.8812 freq = 0.8688 freq = 0.0000 freq = 0.8719 ***************************************** **************************************** Analysis of Marker 710: rs710 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.899779 pvalue = 0.342841 df = 1 ***************************************** RCHI test RCHI statistic value = 0.557120 pvalue = 0.455423 df = 1 ***************************************** RW test RW statistic value = 0.609944 pvalue = 0.434809 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4467 sd = 0.0537 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.5533 sd = 0.0537 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.4750 freq = 0.0000 freq = 0.4656 allele 2 : freq = 0.5625 freq = 0.5250 freq = 0.0000 freq = 0.5344 ***************************************** **************************************** Analysis of Marker 711: rs711 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.340534 pvalue = 0.559521 df = 1 ***************************************** RCHI test RCHI statistic value = 1.303661 pvalue = 0.253546 df = 1 ***************************************** RW test RW statistic value = 1.581463 pvalue = 0.20855 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5983 sd = 0.0530 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 allele 2 : freq = 0.4017 sd = 0.0530 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.6438 freq = 0.0000 freq = 0.6297 allele 2 : freq = 0.4125 freq = 0.3563 freq = 0.0000 freq = 0.3703 ***************************************** **************************************** Analysis of Marker 712: rs712 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 6.279555 pvalue = 0.0122139 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 4.259951 pvalue = 0.039021 df = 1 ***************************************** RW test RW statistic value = 2.386686 pvalue = 0.122373 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4850 sd = 0.0540 freq = 0.5865 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.5150 sd = 0.0540 freq = 0.4135 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4813 freq = 0.5833 freq = 0.0000 freq = 0.5578 allele 2 : freq = 0.5188 freq = 0.4167 freq = 0.0000 freq = 0.4422 ***************************************** **************************************** Analysis of Marker 713: rs713 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.317025 pvalue = 0.251127 df = 1 ***************************************** RCHI test RCHI statistic value = 3.029568 pvalue = 0.0817598 df = 1 ***************************************** RW test RW statistic value = 0.744218 pvalue = 0.388313 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8350 sd = 0.0401 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1650 sd = 0.0401 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.8875 freq = 0.0000 freq = 0.8719 allele 2 : freq = 0.1750 freq = 0.1125 freq = 0.0000 freq = 0.1281 ***************************************** **************************************** Analysis of Marker 714: rs714 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.078308 pvalue = 0.779604 df = 1 ***************************************** RCHI test RCHI statistic value = 0.007071 pvalue = 0.932984 df = 1 ***************************************** RW test RW statistic value = 0.049411 pvalue = 0.824092 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5967 sd = 0.0530 freq = 0.5827 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 allele 2 : freq = 0.4033 sd = 0.0530 freq = 0.4173 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.5958 freq = 0.0000 freq = 0.5969 allele 2 : freq = 0.4000 freq = 0.4042 freq = 0.0000 freq = 0.4031 ***************************************** **************************************** Analysis of Marker 715: rs715 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.860079 pvalue = 0.353717 df = 1 ***************************************** RCHI test RCHI statistic value = 0.293685 pvalue = 0.587869 df = 1 ***************************************** RW test RW statistic value = 1.011062 pvalue = 0.314648 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4083 sd = 0.0531 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.5917 sd = 0.0531 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4000 freq = 0.4271 freq = 0.0000 freq = 0.4203 allele 2 : freq = 0.6000 freq = 0.5729 freq = 0.0000 freq = 0.5797 ***************************************** **************************************** Analysis of Marker 716: rs716 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.906676 pvalue = 0.167333 df = 1 ***************************************** RCHI test RCHI statistic value = 3.705277 pvalue = 0.0542407 df = 1 ***************************************** RW test RW statistic value = 4.187601 pvalue = 0.0407207 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5150 sd = 0.0540 freq = 0.5885 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 allele 2 : freq = 0.4850 sd = 0.0540 freq = 0.4115 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.6208 freq = 0.0000 freq = 0.5969 allele 2 : freq = 0.4750 freq = 0.3792 freq = 0.0000 freq = 0.4031 ***************************************** **************************************** Analysis of Marker 717: rs717 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.202762 pvalue = 0.073514 df = 1 ***************************************** RCHI test RCHI statistic value = 1.865447 pvalue = 0.171997 df = 1 ***************************************** RW test RW statistic value = 0.068666 pvalue = 0.793289 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4083 sd = 0.0531 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 allele 2 : freq = 0.5917 sd = 0.0531 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4062 freq = 0.3417 freq = 0.0000 freq = 0.3578 allele 2 : freq = 0.5938 freq = 0.6583 freq = 0.0000 freq = 0.6422 ***************************************** **************************************** Analysis of Marker 718: rs718 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.138355 pvalue = 0.709921 df = 1 ***************************************** RCHI test RCHI statistic value = 0.484731 pvalue = 0.486287 df = 1 ***************************************** RW test RW statistic value = 0.450206 pvalue = 0.502237 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8433 sd = 0.0393 freq = 0.8635 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1567 sd = 0.0393 freq = 0.1365 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8688 freq = 0.0000 freq = 0.8625 allele 2 : freq = 0.1562 freq = 0.1313 freq = 0.0000 freq = 0.1375 ***************************************** **************************************** Analysis of Marker 719: rs719 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.263614 pvalue = 0.607648 df = 1 ***************************************** RCHI test RCHI statistic value = 0.386270 pvalue = 0.534267 df = 1 ***************************************** RW test RW statistic value = 0.042172 pvalue = 0.837292 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4813 freq = 0.5125 freq = 0.0000 freq = 0.5047 allele 2 : freq = 0.5188 freq = 0.4875 freq = 0.0000 freq = 0.4953 ***************************************** **************************************** Analysis of Marker 720: rs720 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.042899 pvalue = 0.835916 df = 1 ***************************************** RCHI test RCHI statistic value = 0.162750 pvalue = 0.686637 df = 1 ***************************************** RW test RW statistic value = 0.359817 pvalue = 0.548608 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2167 sd = 0.0445 freq = 0.2096 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 allele 2 : freq = 0.7833 sd = 0.0445 freq = 0.7904 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2188 freq = 0.2021 freq = 0.0000 freq = 0.2062 allele 2 : freq = 0.7812 freq = 0.7979 freq = 0.0000 freq = 0.7937 ***************************************** **************************************** Analysis of Marker 721: rs721 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.044494 pvalue = 0.832936 df = 1 ***************************************** RCHI test RCHI statistic value = 0.837580 pvalue = 0.36009 df = 1 ***************************************** RW test RW statistic value = 0.067185 pvalue = 0.795481 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6517 sd = 0.0515 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 allele 2 : freq = 0.3483 sd = 0.0515 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 freq = 0.6062 freq = 0.0000 freq = 0.6172 allele 2 : freq = 0.3500 freq = 0.3937 freq = 0.0000 freq = 0.3828 ***************************************** **************************************** Analysis of Marker 722: rs722 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.083269 pvalue = 0.297967 df = 1 ***************************************** RCHI test RCHI statistic value = 0.337700 pvalue = 0.56116 df = 1 ***************************************** RW test RW statistic value = 0.347815 pvalue = 0.555353 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4217 sd = 0.0533 freq = 0.4712 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 allele 2 : freq = 0.5783 sd = 0.0533 freq = 0.5288 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4188 freq = 0.4479 freq = 0.0000 freq = 0.4406 allele 2 : freq = 0.5813 freq = 0.5521 freq = 0.0000 freq = 0.5594 ***************************************** **************************************** Analysis of Marker 723: rs723 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.107503 pvalue = 0.0779323 df = 1 ***************************************** RCHI test RCHI statistic value = 4.100046 pvalue = 0.042882 df = 1 ***************************************** RW test RW statistic value = 0.718208 pvalue = 0.396732 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2283 sd = 0.0453 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326 allele 2 : freq = 0.7717 sd = 0.0453 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.3375 freq = 0.0000 freq = 0.3141 allele 2 : freq = 0.7562 freq = 0.6625 freq = 0.0000 freq = 0.6859 ***************************************** **************************************** Analysis of Marker 724: rs724 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.387265 pvalue = 0.53374 df = 1 ***************************************** RCHI test RCHI statistic value = 0.451461 pvalue = 0.501642 df = 1 ***************************************** RW test RW statistic value = 0.638796 pvalue = 0.424147 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2800 sd = 0.0485 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327 allele 2 : freq = 0.7200 sd = 0.0485 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2875 freq = 0.3187 freq = 0.0000 freq = 0.3109 allele 2 : freq = 0.7125 freq = 0.6813 freq = 0.0000 freq = 0.6891 ***************************************** **************************************** Analysis of Marker 725: rs725 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.608226 pvalue = 0.435456 df = 1 ***************************************** RCHI test RCHI statistic value = 0.427337 pvalue = 0.513299 df = 1 ***************************************** RW test RW statistic value = 1.261578 pvalue = 0.261353 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6900 sd = 0.0500 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 allele 2 : freq = 0.3100 sd = 0.0500 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.6562 freq = 0.0000 freq = 0.6641 allele 2 : freq = 0.3125 freq = 0.3438 freq = 0.0000 freq = 0.3359 ***************************************** **************************************** Analysis of Marker 726: rs726 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.130740 pvalue = 0.717666 df = 1 ***************************************** RCHI test RCHI statistic value = 0.035256 pvalue = 0.85106 df = 1 ***************************************** RW test RW statistic value = 2.858281 pvalue = 0.0909046 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6983 sd = 0.0496 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 allele 2 : freq = 0.3017 sd = 0.0496 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7125 freq = 0.7042 freq = 0.0000 freq = 0.7063 allele 2 : freq = 0.2875 freq = 0.2958 freq = 0.0000 freq = 0.2938 ***************************************** **************************************** Analysis of Marker 727: rs727 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.667214 pvalue = 0.414025 df = 1 ***************************************** RCHI test RCHI statistic value = 0.379219 pvalue = 0.538022 df = 1 ***************************************** RW test RW statistic value = 0.415175 pvalue = 0.519354 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1700 sd = 0.0406 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 allele 2 : freq = 0.8300 sd = 0.0406 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.2000 freq = 0.0000 freq = 0.1938 allele 2 : freq = 0.8250 freq = 0.8000 freq = 0.0000 freq = 0.8063 ***************************************** **************************************** Analysis of Marker 728: rs728 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.386293 pvalue = 0.239032 df = 1 ***************************************** RCHI test RCHI statistic value = 0.173410 pvalue = 0.677099 df = 1 ***************************************** RW test RW statistic value = 1.211686 pvalue = 0.270999 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.4308 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.5692 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3875 freq = 0.4083 freq = 0.0000 freq = 0.4031 allele 2 : freq = 0.6125 freq = 0.5917 freq = 0.0000 freq = 0.5969 ***************************************** **************************************** Analysis of Marker 729: rs729 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.306741 pvalue = 0.579687 df = 1 ***************************************** RCHI test RCHI statistic value = 0.498513 pvalue = 0.480154 df = 1 ***************************************** RW test RW statistic value = 0.063876 pvalue = 0.800471 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8667 sd = 0.0367 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 allele 2 : freq = 0.1333 sd = 0.0367 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8688 freq = 0.8438 freq = 0.0000 freq = 0.8500 allele 2 : freq = 0.1313 freq = 0.1562 freq = 0.0000 freq = 0.1500 ***************************************** **************************************** Analysis of Marker 730: rs730 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.771258 pvalue = 0.0521404 df = 1 ***************************************** RCHI test RCHI statistic value = 3.884570 pvalue = 0.0487318 df = 1 ***************************************** RW test RW statistic value = 2.369415 pvalue = 0.123733 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2600 sd = 0.0474 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327 allele 2 : freq = 0.7400 sd = 0.0474 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.3292 freq = 0.0000 freq = 0.3063 allele 2 : freq = 0.7625 freq = 0.6708 freq = 0.0000 freq = 0.6937 ***************************************** **************************************** Analysis of Marker 731: rs731 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.658782 pvalue = 0.41699 df = 1 ***************************************** RCHI test RCHI statistic value = 0.393992 pvalue = 0.530208 df = 1 ***************************************** RW test RW statistic value = 0.422316 pvalue = 0.515784 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6100 sd = 0.0527 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 allele 2 : freq = 0.3900 sd = 0.0527 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6062 freq = 0.5750 freq = 0.0000 freq = 0.5828 allele 2 : freq = 0.3937 freq = 0.4250 freq = 0.0000 freq = 0.4172 ***************************************** **************************************** Analysis of Marker 732: rs732 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.753348 pvalue = 0.385418 df = 1 ***************************************** RCHI test RCHI statistic value = 0.541699 pvalue = 0.461729 df = 1 ***************************************** RW test RW statistic value = 0.222856 pvalue = 0.636872 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6667 sd = 0.0509 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 allele 2 : freq = 0.3333 sd = 0.0509 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6813 freq = 0.6458 freq = 0.0000 freq = 0.6547 allele 2 : freq = 0.3187 freq = 0.3542 freq = 0.0000 freq = 0.3453 ***************************************** **************************************** Analysis of Marker 733: rs733 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.524176 pvalue = 0.469066 df = 1 ***************************************** RCHI test RCHI statistic value = 1.066607 pvalue = 0.301713 df = 1 ***************************************** RW test RW statistic value = 0.007278 pvalue = 0.932013 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340 allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3875 freq = 0.3375 freq = 0.0000 freq = 0.3500 allele 2 : freq = 0.6125 freq = 0.6625 freq = 0.0000 freq = 0.6500 ***************************************** **************************************** Analysis of Marker 734: rs734 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.002881 pvalue = 0.957191 df = 1 ***************************************** RCHI test RCHI statistic value = 0.297817 pvalue = 0.585254 df = 1 ***************************************** RW test RW statistic value = 0.241849 pvalue = 0.622874 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2067 sd = 0.0437 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 allele 2 : freq = 0.7933 sd = 0.0437 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2313 freq = 0.2542 freq = 0.0000 freq = 0.2484 allele 2 : freq = 0.7688 freq = 0.7458 freq = 0.0000 freq = 0.7516 ***************************************** **************************************** Analysis of Marker 735: rs735 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.658119 pvalue = 0.197857 df = 1 ***************************************** RCHI test RCHI statistic value = 1.381579 pvalue = 0.239832 df = 1 ***************************************** RW test RW statistic value = 0.089254 pvalue = 0.765128 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 sd = 0.0506 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 allele 2 : freq = 0.3250 sd = 0.0506 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 freq = 0.7042 freq = 0.0000 freq = 0.6906 allele 2 : freq = 0.3500 freq = 0.2958 freq = 0.0000 freq = 0.3094 ***************************************** **************************************** Analysis of Marker 736: rs736 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.735483 pvalue = 0.0532683 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** RCHI test RCHI statistic value = 2.201480 pvalue = 0.137878 df = 1 The p-value might not be exact because of the small number of allele 2 in cases ***************************************** RW test RW statistic value = 1.833450 pvalue = 0.175721 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9550 sd = 0.0224 freq = 0.9058 sd = 0.0222 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207 allele 2 : freq = 0.0450 sd = 0.0224 freq = 0.0942 sd = 0.0222 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9563 freq = 0.9125 freq = 0.0000 freq = 0.9234 allele 2 : freq = 0.0437 freq = 0.0875 freq = 0.0000 freq = 0.0766 ***************************************** **************************************** Analysis of Marker 737: rs737 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.150927 pvalue = 0.697651 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002461 pvalue = 0.960432 df = 1 ***************************************** RW test RW statistic value = 0.107488 pvalue = 0.743022 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2417 sd = 0.0462 freq = 0.2288 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 allele 2 : freq = 0.7583 sd = 0.0462 freq = 0.7712 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.2417 freq = 0.0000 freq = 0.2422 allele 2 : freq = 0.7562 freq = 0.7583 freq = 0.0000 freq = 0.7578 ***************************************** **************************************** Analysis of Marker 738: rs738 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.239406 pvalue = 0.624636 df = 1 ***************************************** RCHI test RCHI statistic value = 0.009281 pvalue = 0.923252 df = 1 ***************************************** RW test RW statistic value = 1.541208 pvalue = 0.214438 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7517 sd = 0.0467 freq = 0.7442 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.2483 sd = 0.0467 freq = 0.2558 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7312 freq = 0.7354 freq = 0.0000 freq = 0.7344 allele 2 : freq = 0.2687 freq = 0.2646 freq = 0.0000 freq = 0.2656 ***************************************** **************************************** Analysis of Marker 739: rs739 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.035947 pvalue = 0.849625 df = 1 ***************************************** RCHI test RCHI statistic value = 0.009694 pvalue = 0.92157 df = 1 ***************************************** RW test RW statistic value = 1.568729 pvalue = 0.210392 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7833 sd = 0.0445 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 allele 2 : freq = 0.2167 sd = 0.0445 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7854 freq = 0.0000 freq = 0.7844 allele 2 : freq = 0.2188 freq = 0.2146 freq = 0.0000 freq = 0.2156 ***************************************** **************************************** Analysis of Marker 740: rs740 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.604097 pvalue = 0.205324 df = 1 ***************************************** RCHI test RCHI statistic value = 2.261241 pvalue = 0.132648 df = 1 ***************************************** RW test RW statistic value = 0.332940 pvalue = 0.563933 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 freq = 0.7354 freq = 0.0000 freq = 0.7516 allele 2 : freq = 0.2000 freq = 0.2646 freq = 0.0000 freq = 0.2484 ***************************************** **************************************** Analysis of Marker 741: rs741 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.529674 pvalue = 0.0602796 df = 1 ***************************************** RCHI test RCHI statistic value = 5.403195 pvalue = 0.0200999 df = 1 ***************************************** RW test RW statistic value = 2.575035 pvalue = 0.108562 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5283 sd = 0.0539 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 allele 2 : freq = 0.4717 sd = 0.0539 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5375 freq = 0.4208 freq = 0.0000 freq = 0.4500 allele 2 : freq = 0.4625 freq = 0.5792 freq = 0.0000 freq = 0.5500 ***************************************** **************************************** Analysis of Marker 742: rs742 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.057215 pvalue = 0.810953 df = 1 ***************************************** RCHI test RCHI statistic value = 0.045102 pvalue = 0.831817 df = 1 ***************************************** RW test RW statistic value = 0.015954 pvalue = 0.899487 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3983 sd = 0.0529 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 allele 2 : freq = 0.6017 sd = 0.0529 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4000 freq = 0.3896 freq = 0.0000 freq = 0.3922 allele 2 : freq = 0.6000 freq = 0.6104 freq = 0.0000 freq = 0.6078 ***************************************** **************************************** Analysis of Marker 743: rs743 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.298788 pvalue = 0.584643 df = 1 ***************************************** RCHI test RCHI statistic value = 0.507562 pvalue = 0.476196 df = 1 ***************************************** RW test RW statistic value = 3.240523 pvalue = 0.0718377 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4083 sd = 0.0531 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 allele 2 : freq = 0.5917 sd = 0.0531 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4062 freq = 0.4417 freq = 0.0000 freq = 0.4328 allele 2 : freq = 0.5938 freq = 0.5583 freq = 0.0000 freq = 0.5672 ***************************************** **************************************** Analysis of Marker 744: rs744 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.017620 pvalue = 0.894398 df = 1 ***************************************** RCHI test RCHI statistic value = 0.001746 pvalue = 0.966667 df = 1 ***************************************** RW test RW statistic value = 0.403425 pvalue = 0.525326 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4467 sd = 0.0537 freq = 0.4558 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.5533 sd = 0.0537 freq = 0.5442 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4437 freq = 0.4458 freq = 0.0000 freq = 0.4453 allele 2 : freq = 0.5563 freq = 0.5542 freq = 0.0000 freq = 0.5547 ***************************************** **************************************** Analysis of Marker 745: rs745 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.191229 pvalue = 0.275082 df = 1 ***************************************** RCHI test RCHI statistic value = 1.330570 pvalue = 0.248704 df = 1 ***************************************** RW test RW statistic value = 0.112497 pvalue = 0.737319 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6867 sd = 0.0501 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.3133 sd = 0.0501 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6813 freq = 0.7333 freq = 0.0000 freq = 0.7203 allele 2 : freq = 0.3187 freq = 0.2667 freq = 0.0000 freq = 0.2797 ***************************************** **************************************** Analysis of Marker 746: rs746 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.349078 pvalue = 0.554636 df = 1 ***************************************** RCHI test RCHI statistic value = 1.871230 pvalue = 0.171334 df = 1 ***************************************** RW test RW statistic value = 0.006754 pvalue = 0.934503 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5062 freq = 0.5750 freq = 0.0000 freq = 0.5578 allele 2 : freq = 0.4938 freq = 0.4250 freq = 0.0000 freq = 0.4422 ***************************************** **************************************** Analysis of Marker 747: rs747 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.005619 pvalue = 0.940249 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003193 pvalue = 0.954936 df = 1 ***************************************** RW test RW statistic value = 0.906831 pvalue = 0.340957 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8350 sd = 0.0401 freq = 0.8365 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 allele 2 : freq = 0.1650 sd = 0.0401 freq = 0.1635 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8396 freq = 0.0000 freq = 0.8391 allele 2 : freq = 0.1625 freq = 0.1604 freq = 0.0000 freq = 0.1609 ***************************************** **************************************** Analysis of Marker 748: rs748 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.750680 pvalue = 0.386261 df = 1 ***************************************** RCHI test RCHI statistic value = 0.799376 pvalue = 0.37128 df = 1 ***************************************** RW test RW statistic value = 0.000198 pvalue = 0.988776 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4383 sd = 0.0536 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 allele 2 : freq = 0.5617 sd = 0.0536 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4188 freq = 0.3750 freq = 0.0000 freq = 0.3859 allele 2 : freq = 0.5813 freq = 0.6250 freq = 0.0000 freq = 0.6141 ***************************************** **************************************** Analysis of Marker 749: rs749 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.024915 pvalue = 0.87458 df = 1 ***************************************** RCHI test RCHI statistic value = 0.027537 pvalue = 0.868202 df = 1 ***************************************** RW test RW statistic value = 0.018790 pvalue = 0.89097 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4688 freq = 0.4771 freq = 0.0000 freq = 0.4750 allele 2 : freq = 0.5312 freq = 0.5229 freq = 0.0000 freq = 0.5250 ***************************************** **************************************** Analysis of Marker 750: rs750 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.017099 pvalue = 0.0823907 df = 1 ***************************************** RCHI test RCHI statistic value = 1.310977 pvalue = 0.252218 df = 1 ***************************************** RW test RW statistic value = 0.073026 pvalue = 0.786981 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1117 sd = 0.0340 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 allele 2 : freq = 0.8883 sd = 0.0340 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1125 freq = 0.1562 freq = 0.0000 freq = 0.1453 allele 2 : freq = 0.8875 freq = 0.8438 freq = 0.0000 freq = 0.8547 ***************************************** **************************************** Analysis of Marker 751: rs751 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.556124 pvalue = 0.455826 df = 1 ***************************************** RCHI test RCHI statistic value = 0.109305 pvalue = 0.740937 df = 1 ***************************************** RW test RW statistic value = 0.515342 pvalue = 0.472835 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2833 sd = 0.0487 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310 allele 2 : freq = 0.7167 sd = 0.0487 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2938 freq = 0.2792 freq = 0.0000 freq = 0.2828 allele 2 : freq = 0.7063 freq = 0.7208 freq = 0.0000 freq = 0.7172 ***************************************** **************************************** Analysis of Marker 752: rs752 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.536034 pvalue = 0.464081 df = 1 ***************************************** RCHI test RCHI statistic value = 0.785443 pvalue = 0.375481 df = 1 ***************************************** RW test RW statistic value = 2.482962 pvalue = 0.115085 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4450 sd = 0.0537 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 allele 2 : freq = 0.5550 sd = 0.0537 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4313 freq = 0.3875 freq = 0.0000 freq = 0.3984 allele 2 : freq = 0.5687 freq = 0.6125 freq = 0.0000 freq = 0.6016 ***************************************** **************************************** Analysis of Marker 753: rs753 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.032450 pvalue = 0.857044 df = 1 ***************************************** RCHI test RCHI statistic value = 0.205980 pvalue = 0.649937 df = 1 ***************************************** RW test RW statistic value = 2.721118 pvalue = 0.0990286 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2617 sd = 0.0475 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 allele 2 : freq = 0.7383 sd = 0.0475 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2313 freq = 0.2500 freq = 0.0000 freq = 0.2453 allele 2 : freq = 0.7688 freq = 0.7500 freq = 0.0000 freq = 0.7547 ***************************************** **************************************** Analysis of Marker 754: rs754 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.405712 pvalue = 0.120893 df = 1 ***************************************** RCHI test RCHI statistic value = 1.088648 pvalue = 0.296771 df = 1 ***************************************** RW test RW statistic value = 0.554539 pvalue = 0.456469 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4950 sd = 0.0540 freq = 0.5731 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 allele 2 : freq = 0.5050 sd = 0.0540 freq = 0.4269 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4875 freq = 0.5396 freq = 0.0000 freq = 0.5266 allele 2 : freq = 0.5125 freq = 0.4604 freq = 0.0000 freq = 0.4734 ***************************************** **************************************** Analysis of Marker 755: rs755 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.500347 pvalue = 0.220618 df = 1 ***************************************** RCHI test RCHI statistic value = 0.852740 pvalue = 0.355778 df = 1 ***************************************** RW test RW statistic value = 0.001731 pvalue = 0.966811 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5367 sd = 0.0539 freq = 0.5904 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349 allele 2 : freq = 0.4633 sd = 0.0539 freq = 0.4096 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.5708 freq = 0.0000 freq = 0.5594 allele 2 : freq = 0.4750 freq = 0.4292 freq = 0.0000 freq = 0.4406 ***************************************** **************************************** Analysis of Marker 756: rs756 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.657564 pvalue = 0.417421 df = 1 ***************************************** RCHI test RCHI statistic value = 0.774516 pvalue = 0.378824 df = 1 ***************************************** RW test RW statistic value = 2.761156 pvalue = 0.0965785 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6267 sd = 0.0522 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 allele 2 : freq = 0.3733 sd = 0.0522 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6062 freq = 0.5625 freq = 0.0000 freq = 0.5734 allele 2 : freq = 0.3937 freq = 0.4375 freq = 0.0000 freq = 0.4266 ***************************************** **************************************** Analysis of Marker 757: rs757 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.356775 pvalue = 0.244097 df = 1 ***************************************** RCHI test RCHI statistic value = 1.649967 pvalue = 0.198963 df = 1 ***************************************** RW test RW statistic value = 6.277558 pvalue = 0.0122276 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4583 sd = 0.0538 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.5417 sd = 0.0538 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.5146 freq = 0.0000 freq = 0.4984 allele 2 : freq = 0.5500 freq = 0.4854 freq = 0.0000 freq = 0.5016 ***************************************** **************************************** Analysis of Marker 758: rs758 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.054166 pvalue = 0.815967 df = 1 ***************************************** RCHI test RCHI statistic value = 0.046860 pvalue = 0.82862 df = 1 ***************************************** RW test RW statistic value = 0.010028 pvalue = 0.920235 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3283 sd = 0.0507 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 allele 2 : freq = 0.6717 sd = 0.0507 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3271 freq = 0.0000 freq = 0.3297 allele 2 : freq = 0.6625 freq = 0.6729 freq = 0.0000 freq = 0.6703 ***************************************** **************************************** Analysis of Marker 759: rs759 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.643565 pvalue = 0.422423 df = 1 ***************************************** RCHI test RCHI statistic value = 0.445910 pvalue = 0.504283 df = 1 ***************************************** RW test RW statistic value = 0.109539 pvalue = 0.74067 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.4308 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.5692 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 freq = 0.4417 freq = 0.0000 freq = 0.4500 allele 2 : freq = 0.5250 freq = 0.5583 freq = 0.0000 freq = 0.5500 ***************************************** **************************************** Analysis of Marker 760: rs760 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.095596 pvalue = 0.75718 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003366 pvalue = 0.953734 df = 1 ***************************************** RW test RW statistic value = 0.450206 pvalue = 0.502237 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1417 sd = 0.0377 freq = 0.1635 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 allele 2 : freq = 0.8583 sd = 0.0377 freq = 0.8365 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1375 freq = 0.1396 freq = 0.0000 freq = 0.1391 allele 2 : freq = 0.8625 freq = 0.8604 freq = 0.0000 freq = 0.8609 ***************************************** **************************************** Analysis of Marker 761: rs761 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.181757 pvalue = 0.669867 df = 1 ***************************************** RCHI test RCHI statistic value = 0.042135 pvalue = 0.837362 df = 1 ***************************************** RW test RW statistic value = 0.807636 pvalue = 0.36882 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2000 sd = 0.0432 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 allele 2 : freq = 0.8000 sd = 0.0432 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1958 freq = 0.0000 freq = 0.1938 allele 2 : freq = 0.8125 freq = 0.8042 freq = 0.0000 freq = 0.8063 ***************************************** **************************************** Analysis of Marker 762: rs762 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.140082 pvalue = 0.708199 df = 1 ***************************************** RCHI test RCHI statistic value = 1.171495 pvalue = 0.279094 df = 1 ***************************************** RW test RW statistic value = 0.066304 pvalue = 0.796796 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6583 sd = 0.0512 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 allele 2 : freq = 0.3417 sd = 0.0512 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6438 freq = 0.6958 freq = 0.0000 freq = 0.6828 allele 2 : freq = 0.3563 freq = 0.3042 freq = 0.0000 freq = 0.3172 ***************************************** **************************************** Analysis of Marker 763: rs763 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.315494 pvalue = 0.574328 df = 1 ***************************************** RCHI test RCHI statistic value = 0.386842 pvalue = 0.533964 df = 1 ***************************************** RW test RW statistic value = 0.006248 pvalue = 0.936999 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7300 sd = 0.0480 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 allele 2 : freq = 0.2700 sd = 0.0480 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7312 freq = 0.7583 freq = 0.0000 freq = 0.7516 allele 2 : freq = 0.2687 freq = 0.2417 freq = 0.0000 freq = 0.2484 ***************************************** **************************************** Analysis of Marker 764: rs764 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.431557 pvalue = 0.511226 df = 1 ***************************************** RCHI test RCHI statistic value = 0.765042 pvalue = 0.381755 df = 1 ***************************************** RW test RW statistic value = 0.007517 pvalue = 0.930908 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6683 sd = 0.0509 freq = 0.6423 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335 allele 2 : freq = 0.3317 sd = 0.0509 freq = 0.3577 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6813 freq = 0.6396 freq = 0.0000 freq = 0.6500 allele 2 : freq = 0.3187 freq = 0.3604 freq = 0.0000 freq = 0.3500 ***************************************** **************************************** Analysis of Marker 765: rs765 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.123442 pvalue = 0.72533 df = 1 ***************************************** RCHI test RCHI statistic value = 0.607253 pvalue = 0.435824 df = 1 ***************************************** RW test RW statistic value = 1.602685 pvalue = 0.205523 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1333 sd = 0.0367 freq = 0.0962 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 allele 2 : freq = 0.8667 sd = 0.0367 freq = 0.9038 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1187 freq = 0.0938 freq = 0.0000 freq = 0.1000 allele 2 : freq = 0.8812 freq = 0.9062 freq = 0.0000 freq = 0.9000 ***************************************** **************************************** Analysis of Marker 766: rs766 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.025777 pvalue = 0.872447 df = 1 ***************************************** RCHI test RCHI statistic value = 0.042923 pvalue = 0.83587 df = 1 ***************************************** RW test RW statistic value = 1.988671 pvalue = 0.15848 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 sd = 0.0539 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.5250 sd = 0.0539 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4813 freq = 0.4708 freq = 0.0000 freq = 0.4734 allele 2 : freq = 0.5188 freq = 0.5292 freq = 0.0000 freq = 0.5266 ***************************************** **************************************** Analysis of Marker 767: rs767 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.707209 pvalue = 0.191348 df = 1 ***************************************** RCHI test RCHI statistic value = 2.409481 pvalue = 0.120602 df = 1 ***************************************** RW test RW statistic value = 4.612856 pvalue = 0.0317331 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2833 sd = 0.0487 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 allele 2 : freq = 0.7167 sd = 0.0487 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2812 freq = 0.2146 freq = 0.0000 freq = 0.2313 allele 2 : freq = 0.7188 freq = 0.7854 freq = 0.0000 freq = 0.7688 ***************************************** **************************************** Analysis of Marker 768: rs768 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000217 pvalue = 0.988249 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002044 pvalue = 0.963942 df = 1 ***************************************** RW test RW statistic value = 0.139459 pvalue = 0.70882 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3017 sd = 0.0496 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 allele 2 : freq = 0.6983 sd = 0.0496 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3000 freq = 0.2979 freq = 0.0000 freq = 0.2984 allele 2 : freq = 0.7000 freq = 0.7021 freq = 0.0000 freq = 0.7016 ***************************************** **************************************** Analysis of Marker 769: rs769 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.447075 pvalue = 0.503727 df = 1 ***************************************** RCHI test RCHI statistic value = 0.528296 pvalue = 0.467324 df = 1 ***************************************** RW test RW statistic value = 0.230714 pvalue = 0.630995 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6833 sd = 0.0502 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 allele 2 : freq = 0.3167 sd = 0.0502 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6813 freq = 0.7146 freq = 0.0000 freq = 0.7063 allele 2 : freq = 0.3187 freq = 0.2854 freq = 0.0000 freq = 0.2938 ***************************************** **************************************** Analysis of Marker 770: rs770 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.333290 pvalue = 0.563728 df = 1 ***************************************** RCHI test RCHI statistic value = 0.247832 pvalue = 0.618606 df = 1 ***************************************** RW test RW statistic value = 0.380502 pvalue = 0.537335 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5633 sd = 0.0536 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353 allele 2 : freq = 0.4367 sd = 0.0536 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5500 freq = 0.5250 freq = 0.0000 freq = 0.5312 allele 2 : freq = 0.4500 freq = 0.4750 freq = 0.0000 freq = 0.4688 ***************************************** **************************************** Analysis of Marker 771: rs771 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.302631 pvalue = 0.582238 df = 1 ***************************************** RCHI test RCHI statistic value = 0.297817 pvalue = 0.585254 df = 1 ***************************************** RW test RW statistic value = 0.544159 pvalue = 0.460714 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.7792 freq = 0.0000 freq = 0.7734 allele 2 : freq = 0.2437 freq = 0.2208 freq = 0.0000 freq = 0.2266 ***************************************** **************************************** Analysis of Marker 772: rs772 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.004086 pvalue = 0.949035 df = 1 ***************************************** RCHI test RCHI statistic value = 0.288740 pvalue = 0.591029 df = 1 ***************************************** RW test RW statistic value = 0.076281 pvalue = 0.782402 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1733 sd = 0.0409 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8267 sd = 0.0409 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1500 freq = 0.1688 freq = 0.0000 freq = 0.1641 allele 2 : freq = 0.8500 freq = 0.8313 freq = 0.0000 freq = 0.8359 ***************************************** **************************************** Analysis of Marker 773: rs773 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.485482 pvalue = 0.019175 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 3.729815 pvalue = 0.0534493 df = 1 ***************************************** RW test RW statistic value = 2.978603 pvalue = 0.0843721 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7617 sd = 0.0460 freq = 0.6500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 allele 2 : freq = 0.2383 sd = 0.0460 freq = 0.3500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.6708 freq = 0.0000 freq = 0.6937 allele 2 : freq = 0.2375 freq = 0.3292 freq = 0.0000 freq = 0.3063 ***************************************** **************************************** Analysis of Marker 774: rs774 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.668886 pvalue = 0.196408 df = 1 ***************************************** RCHI test RCHI statistic value = 2.209988 pvalue = 0.13712 df = 1 ***************************************** RW test RW statistic value = 0.165648 pvalue = 0.684009 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4183 sd = 0.0533 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 allele 2 : freq = 0.5817 sd = 0.0533 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.3646 freq = 0.0000 freq = 0.3828 allele 2 : freq = 0.5625 freq = 0.6354 freq = 0.0000 freq = 0.6172 ***************************************** **************************************** Analysis of Marker 775: rs775 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.564539 pvalue = 0.211002 df = 1 ***************************************** RCHI test RCHI statistic value = 2.369430 pvalue = 0.123732 df = 1 ***************************************** RW test RW statistic value = 2.858824 pvalue = 0.0908739 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4967 sd = 0.0540 freq = 0.5577 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 allele 2 : freq = 0.5033 sd = 0.0540 freq = 0.4423 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.5771 freq = 0.0000 freq = 0.5578 allele 2 : freq = 0.5000 freq = 0.4229 freq = 0.0000 freq = 0.4422 ***************************************** **************************************** Analysis of Marker 776: rs776 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.715778 pvalue = 0.0993605 df = 1 ***************************************** RCHI test RCHI statistic value = 2.860604 pvalue = 0.0907734 df = 1 ***************************************** RW test RW statistic value = 3.470181 pvalue = 0.0624845 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0800 sd = 0.0293 freq = 0.1327 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 allele 2 : freq = 0.9200 sd = 0.0293 freq = 0.8673 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0813 freq = 0.1375 freq = 0.0000 freq = 0.1234 allele 2 : freq = 0.9187 freq = 0.8625 freq = 0.0000 freq = 0.8766 ***************************************** **************************************** Analysis of Marker 777: rs777 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.118593 pvalue = 0.730565 df = 1 ***************************************** RCHI test RCHI statistic value = 0.070143 pvalue = 0.791128 df = 1 ***************************************** RW test RW statistic value = 0.172786 pvalue = 0.677647 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0983 sd = 0.0322 freq = 0.1096 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221 allele 2 : freq = 0.9017 sd = 0.0322 freq = 0.8904 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0938 freq = 0.0854 freq = 0.0000 freq = 0.0875 allele 2 : freq = 0.9062 freq = 0.9146 freq = 0.0000 freq = 0.9125 ***************************************** **************************************** Analysis of Marker 778: rs778 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.242746 pvalue = 0.264942 df = 1 ***************************************** RCHI test RCHI statistic value = 0.861068 pvalue = 0.35344 df = 1 ***************************************** RW test RW statistic value = 0.094010 pvalue = 0.75914 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7633 sd = 0.0459 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316 allele 2 : freq = 0.2367 sd = 0.0459 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7688 freq = 0.7271 freq = 0.0000 freq = 0.7375 allele 2 : freq = 0.2313 freq = 0.2729 freq = 0.0000 freq = 0.2625 ***************************************** **************************************** Analysis of Marker 779: rs779 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.722578 pvalue = 0.3953 df = 1 ***************************************** RCHI test RCHI statistic value = 0.369763 pvalue = 0.543134 df = 1 ***************************************** RW test RW statistic value = 2.059699 pvalue = 0.15124 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6083 sd = 0.0527 freq = 0.6615 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 allele 2 : freq = 0.3917 sd = 0.0527 freq = 0.3385 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6125 freq = 0.6417 freq = 0.0000 freq = 0.6344 allele 2 : freq = 0.3875 freq = 0.3583 freq = 0.0000 freq = 0.3656 ***************************************** **************************************** Analysis of Marker 780: rs780 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.704490 pvalue = 0.401279 df = 1 ***************************************** RCHI test RCHI statistic value = 0.627469 pvalue = 0.428285 df = 1 ***************************************** RW test RW statistic value = 0.954822 pvalue = 0.328495 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8433 sd = 0.0393 freq = 0.7962 sd = 0.0306 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.1567 sd = 0.0393 freq = 0.2038 sd = 0.0306 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8063 freq = 0.0000 freq = 0.8141 allele 2 : freq = 0.1625 freq = 0.1938 freq = 0.0000 freq = 0.1859 ***************************************** **************************************** Analysis of Marker 781: rs781 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.241727 pvalue = 0.622961 df = 1 ***************************************** RCHI test RCHI statistic value = 0.728717 pvalue = 0.393299 df = 1 ***************************************** RW test RW statistic value = 0.472699 pvalue = 0.491748 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1533 sd = 0.0389 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275 allele 2 : freq = 0.8467 sd = 0.0389 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.2083 freq = 0.0000 freq = 0.2000 allele 2 : freq = 0.8250 freq = 0.7917 freq = 0.0000 freq = 0.8000 ***************************************** **************************************** Analysis of Marker 782: rs782 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.150629 pvalue = 0.697935 df = 1 ***************************************** RCHI test RCHI statistic value = 0.516159 pvalue = 0.472485 df = 1 ***************************************** RW test RW statistic value = 0.048590 pvalue = 0.825534 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7875 freq = 0.8167 freq = 0.0000 freq = 0.8094 allele 2 : freq = 0.2125 freq = 0.1833 freq = 0.0000 freq = 0.1906 ***************************************** **************************************** Analysis of Marker 783: rs783 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000047 pvalue = 0.994537 df = 1 ***************************************** RCHI test RCHI statistic value = 0.776980 pvalue = 0.378066 df = 1 ***************************************** RW test RW statistic value = 0.001731 pvalue = 0.966811 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4567 sd = 0.0538 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349 allele 2 : freq = 0.5433 sd = 0.0538 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.4813 freq = 0.0000 freq = 0.4703 allele 2 : freq = 0.5625 freq = 0.5188 freq = 0.0000 freq = 0.5297 ***************************************** **************************************** Analysis of Marker 784: rs784 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.294186 pvalue = 0.587551 df = 1 ***************************************** RCHI test RCHI statistic value = 0.207748 pvalue = 0.648538 df = 1 ***************************************** RW test RW statistic value = 0.431888 pvalue = 0.511064 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5188 freq = 0.4958 freq = 0.0000 freq = 0.5016 allele 2 : freq = 0.4813 freq = 0.5042 freq = 0.0000 freq = 0.4984 ***************************************** **************************************** Analysis of Marker 785: rs785 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.857699 pvalue = 0.0155091 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 6.237683 pvalue = 0.012506 df = 1 ***************************************** RW test RW statistic value = 4.951513 pvalue = 0.0260678 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2267 sd = 0.0452 freq = 0.3346 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.7733 sd = 0.0452 freq = 0.6654 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 freq = 0.3417 freq = 0.0000 freq = 0.3125 allele 2 : freq = 0.7750 freq = 0.6583 freq = 0.0000 freq = 0.6875 ***************************************** **************************************** Analysis of Marker 786: rs786 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.283081 pvalue = 0.257327 df = 1 ***************************************** RCHI test RCHI statistic value = 0.258703 pvalue = 0.611012 df = 1 ***************************************** RW test RW statistic value = 0.983202 pvalue = 0.32141 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8400 sd = 0.0396 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.1600 sd = 0.0396 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8167 freq = 0.0000 freq = 0.8219 allele 2 : freq = 0.1625 freq = 0.1833 freq = 0.0000 freq = 0.1781 ***************************************** **************************************** Analysis of Marker 787: rs787 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.027711 pvalue = 0.154453 df = 1 ***************************************** RCHI test RCHI statistic value = 1.249745 pvalue = 0.263601 df = 1 ***************************************** RW test RW statistic value = 2.603798 pvalue = 0.106608 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0967 sd = 0.0319 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.9033 sd = 0.0319 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1000 freq = 0.1396 freq = 0.0000 freq = 0.1297 allele 2 : freq = 0.9000 freq = 0.8604 freq = 0.0000 freq = 0.8703 ***************************************** **************************************** Analysis of Marker 788: rs788 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.151376 pvalue = 0.283261 df = 1 ***************************************** RCHI test RCHI statistic value = 0.553792 pvalue = 0.456772 df = 1 ***************************************** RW test RW statistic value = 0.001431 pvalue = 0.969824 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1558 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8442 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1187 freq = 0.1458 freq = 0.0000 freq = 0.1391 allele 2 : freq = 0.8812 freq = 0.8542 freq = 0.0000 freq = 0.8609 ***************************************** **************************************** Analysis of Marker 789: rs789 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.181490 pvalue = 0.670096 df = 1 ***************************************** RCHI test RCHI statistic value = 0.077879 pvalue = 0.780193 df = 1 ***************************************** RW test RW statistic value = 0.122778 pvalue = 0.72604 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1433 sd = 0.0378 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 allele 2 : freq = 0.8567 sd = 0.0378 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1500 freq = 0.1604 freq = 0.0000 freq = 0.1578 allele 2 : freq = 0.8500 freq = 0.8396 freq = 0.0000 freq = 0.8422 ***************************************** **************************************** Analysis of Marker 790: rs790 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.464273 pvalue = 0.495634 df = 1 ***************************************** RCHI test RCHI statistic value = 0.386842 pvalue = 0.533964 df = 1 ***************************************** RW test RW statistic value = 0.056230 pvalue = 0.812557 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2617 sd = 0.0475 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.7383 sd = 0.0475 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2750 freq = 0.2479 freq = 0.0000 freq = 0.2547 allele 2 : freq = 0.7250 freq = 0.7521 freq = 0.0000 freq = 0.7453 ***************************************** **************************************** Analysis of Marker 791: rs791 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.006761 pvalue = 0.934466 df = 1 ***************************************** RCHI test RCHI statistic value = 0.048164 pvalue = 0.82629 df = 1 ***************************************** RW test RW statistic value = 0.121155 pvalue = 0.727785 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3550 sd = 0.0517 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 allele 2 : freq = 0.6450 sd = 0.0517 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.3542 freq = 0.0000 freq = 0.3516 allele 2 : freq = 0.6562 freq = 0.6458 freq = 0.0000 freq = 0.6484 ***************************************** **************************************** Analysis of Marker 792: rs792 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.020865 pvalue = 0.885146 df = 1 ***************************************** RCHI test RCHI statistic value = 0.124628 pvalue = 0.724068 df = 1 ***************************************** RW test RW statistic value = 0.122461 pvalue = 0.726381 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8667 sd = 0.0367 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 allele 2 : freq = 0.1333 sd = 0.0367 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8562 freq = 0.8438 freq = 0.0000 freq = 0.8469 allele 2 : freq = 0.1437 freq = 0.1562 freq = 0.0000 freq = 0.1531 ***************************************** **************************************** Analysis of Marker 793: rs793 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.995050 pvalue = 0.318511 df = 1 ***************************************** RCHI test RCHI statistic value = 0.452569 pvalue = 0.501118 df = 1 ***************************************** RW test RW statistic value = 2.378084 pvalue = 0.123048 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6433 sd = 0.0517 freq = 0.5769 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348 allele 2 : freq = 0.3567 sd = 0.0517 freq = 0.4231 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6312 freq = 0.5979 freq = 0.0000 freq = 0.6062 allele 2 : freq = 0.3688 freq = 0.4021 freq = 0.0000 freq = 0.3937 ***************************************** **************************************** Analysis of Marker 794: rs794 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.070593 pvalue = 0.300811 df = 1 ***************************************** RCHI test RCHI statistic value = 1.155485 pvalue = 0.282404 df = 1 ***************************************** RW test RW statistic value = 2.303093 pvalue = 0.129117 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1883 sd = 0.0422 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 allele 2 : freq = 0.8117 sd = 0.0422 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2000 freq = 0.2458 freq = 0.0000 freq = 0.2344 allele 2 : freq = 0.8000 freq = 0.7542 freq = 0.0000 freq = 0.7656 ***************************************** **************************************** Analysis of Marker 795: rs795 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.194257 pvalue = 0.138526 df = 1 ***************************************** RCHI test RCHI statistic value = 2.225805 pvalue = 0.135722 df = 1 ***************************************** RW test RW statistic value = 2.028082 pvalue = 0.154415 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4800 sd = 0.0540 freq = 0.5115 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 allele 2 : freq = 0.5200 sd = 0.0540 freq = 0.4885 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.5250 freq = 0.0000 freq = 0.5062 allele 2 : freq = 0.5500 freq = 0.4750 freq = 0.0000 freq = 0.4938 ***************************************** **************************************** Analysis of Marker 796: rs796 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.550019 pvalue = 0.45831 df = 1 ***************************************** RCHI test RCHI statistic value = 0.152642 pvalue = 0.696023 df = 1 ***************************************** RW test RW statistic value = 0.517302 pvalue = 0.471995 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8550 sd = 0.0380 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 allele 2 : freq = 0.1450 sd = 0.0380 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8625 freq = 0.8479 freq = 0.0000 freq = 0.8516 allele 2 : freq = 0.1375 freq = 0.1521 freq = 0.0000 freq = 0.1484 ***************************************** **************************************** Analysis of Marker 797: rs797 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.096277 pvalue = 0.295085 df = 1 ***************************************** RCHI test RCHI statistic value = 1.606359 pvalue = 0.205004 df = 1 ***************************************** RW test RW statistic value = 0.003849 pvalue = 0.950529 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2300 sd = 0.0455 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 allele 2 : freq = 0.7700 sd = 0.0455 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2313 freq = 0.2875 freq = 0.0000 freq = 0.2734 allele 2 : freq = 0.7688 freq = 0.7125 freq = 0.0000 freq = 0.7266 ***************************************** **************************************** Analysis of Marker 798: rs798 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.970571 pvalue = 0.0847919 df = 1 ***************************************** RCHI test RCHI statistic value = 2.186381 pvalue = 0.139236 df = 1 ***************************************** RW test RW statistic value = 1.132938 pvalue = 0.287149 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8650 sd = 0.0369 freq = 0.8019 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.1350 sd = 0.0369 freq = 0.1981 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8688 freq = 0.8104 freq = 0.0000 freq = 0.8250 allele 2 : freq = 0.1313 freq = 0.1896 freq = 0.0000 freq = 0.1750 ***************************************** **************************************** Analysis of Marker 799: rs799 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.570259 pvalue = 0.10889 df = 1 ***************************************** RCHI test RCHI statistic value = 1.733467 pvalue = 0.187969 df = 1 ***************************************** RW test RW statistic value = 1.906525 pvalue = 0.16735 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7817 sd = 0.0446 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256 allele 2 : freq = 0.2183 sd = 0.0446 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7937 freq = 0.8417 freq = 0.0000 freq = 0.8297 allele 2 : freq = 0.2062 freq = 0.1583 freq = 0.0000 freq = 0.1703 ***************************************** **************************************** Analysis of Marker 800: rs800 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.167509 pvalue = 0.682335 df = 1 ***************************************** RCHI test RCHI statistic value = 0.358916 pvalue = 0.549109 df = 1 ***************************************** RW test RW statistic value = 0.124955 pvalue = 0.723721 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6217 sd = 0.0524 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.3783 sd = 0.0524 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6375 freq = 0.6083 freq = 0.0000 freq = 0.6156 allele 2 : freq = 0.3625 freq = 0.3917 freq = 0.0000 freq = 0.3844 ***************************************** **************************************** Analysis of Marker 801: rs801 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.530169 pvalue = 0.466536 df = 1 ***************************************** RCHI test RCHI statistic value = 0.136649 pvalue = 0.711636 df = 1 ***************************************** RW test RW statistic value = 0.059676 pvalue = 0.807008 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7617 sd = 0.0460 freq = 0.8038 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.2383 sd = 0.0460 freq = 0.1962 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7812 freq = 0.7958 freq = 0.0000 freq = 0.7922 allele 2 : freq = 0.2188 freq = 0.2042 freq = 0.0000 freq = 0.2078 ***************************************** **************************************** Analysis of Marker 802: rs802 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.082507 pvalue = 0.298137 df = 1 ***************************************** RCHI test RCHI statistic value = 0.615256 pvalue = 0.432816 df = 1 ***************************************** RW test RW statistic value = 0.002092 pvalue = 0.96352 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7667 sd = 0.0457 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.2333 sd = 0.0457 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7271 freq = 0.0000 freq = 0.7359 allele 2 : freq = 0.2375 freq = 0.2729 freq = 0.0000 freq = 0.2641 ***************************************** **************************************** Analysis of Marker 803: rs803 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.319071 pvalue = 0.127796 df = 1 ***************************************** RCHI test RCHI statistic value = 1.775137 pvalue = 0.182748 df = 1 ***************************************** RW test RW statistic value = 0.966665 pvalue = 0.325513 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6267 sd = 0.0522 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 allele 2 : freq = 0.3733 sd = 0.0522 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6188 freq = 0.6813 freq = 0.0000 freq = 0.6656 allele 2 : freq = 0.3812 freq = 0.3187 freq = 0.0000 freq = 0.3344 ***************************************** **************************************** Analysis of Marker 804: rs804 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.046314 pvalue = 0.306358 df = 1 ***************************************** RCHI test RCHI statistic value = 0.879061 pvalue = 0.348459 df = 1 ***************************************** RW test RW statistic value = 1.117157 pvalue = 0.290531 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8717 sd = 0.0361 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 allele 2 : freq = 0.1283 sd = 0.0361 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8625 freq = 0.8271 freq = 0.0000 freq = 0.8359 allele 2 : freq = 0.1375 freq = 0.1729 freq = 0.0000 freq = 0.1641 ***************************************** **************************************** Analysis of Marker 805: rs805 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.056637 pvalue = 0.151544 df = 1 ***************************************** RCHI test RCHI statistic value = 4.874893 pvalue = 0.0272501 df = 1 ***************************************** RW test RW statistic value = 2.320923 pvalue = 0.127644 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0917 sd = 0.0312 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 allele 2 : freq = 0.9083 sd = 0.0312 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0875 freq = 0.1583 freq = 0.0000 freq = 0.1406 allele 2 : freq = 0.9125 freq = 0.8417 freq = 0.0000 freq = 0.8594 ***************************************** **************************************** Analysis of Marker 806: rs806 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.849584 pvalue = 0.35667 df = 1 ***************************************** RCHI test RCHI statistic value = 0.279526 pvalue = 0.597012 df = 1 ***************************************** RW test RW statistic value = 0.000848 pvalue = 0.976772 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2950 sd = 0.0493 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 allele 2 : freq = 0.7050 sd = 0.0493 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2875 freq = 0.3125 freq = 0.0000 freq = 0.3063 allele 2 : freq = 0.7125 freq = 0.6875 freq = 0.0000 freq = 0.6937 ***************************************** **************************************** Analysis of Marker 807: rs807 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.734323 pvalue = 0.0533053 df = 1 ***************************************** RCHI test RCHI statistic value = 2.076126 pvalue = 0.149619 df = 1 ***************************************** RW test RW statistic value = 0.268433 pvalue = 0.604385 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5533 sd = 0.0537 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.4467 sd = 0.0537 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5188 freq = 0.5896 freq = 0.0000 freq = 0.5719 allele 2 : freq = 0.4813 freq = 0.4104 freq = 0.0000 freq = 0.4281 ***************************************** **************************************** Analysis of Marker 808: rs808 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.254715 pvalue = 0.262654 df = 1 ***************************************** RCHI test RCHI statistic value = 0.685638 pvalue = 0.407652 df = 1 ***************************************** RW test RW statistic value = 0.797091 pvalue = 0.371964 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6167 sd = 0.0525 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 allele 2 : freq = 0.3833 sd = 0.0525 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6062 freq = 0.6458 freq = 0.0000 freq = 0.6359 allele 2 : freq = 0.3937 freq = 0.3542 freq = 0.0000 freq = 0.3641 ***************************************** **************************************** Analysis of Marker 809: rs809 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.007888 pvalue = 0.92923 df = 1 ***************************************** RCHI test RCHI statistic value = 0.074318 pvalue = 0.78515 df = 1 ***************************************** RW test RW statistic value = 1.371260 pvalue = 0.241595 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.1646 freq = 0.0000 freq = 0.1672 allele 2 : freq = 0.8250 freq = 0.8354 freq = 0.0000 freq = 0.8328 ***************************************** **************************************** Analysis of Marker 810: rs810 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.811301 pvalue = 0.0509079 df = 1 ***************************************** RCHI test RCHI statistic value = 4.765072 pvalue = 0.0290428 df = 1 ***************************************** RW test RW statistic value = 0.812880 pvalue = 0.36727 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8333 sd = 0.0403 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 allele 2 : freq = 0.1667 sd = 0.0403 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.7458 freq = 0.0000 freq = 0.7688 allele 2 : freq = 0.1625 freq = 0.2542 freq = 0.0000 freq = 0.2313 ***************************************** **************************************** Analysis of Marker 811: rs811 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.074935 pvalue = 0.784282 df = 1 ***************************************** RCHI test RCHI statistic value = 0.256780 pvalue = 0.612341 df = 1 ***************************************** RW test RW statistic value = 0.020597 pvalue = 0.885882 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0950 sd = 0.0317 freq = 0.0923 sd = 0.0220 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202 allele 2 : freq = 0.9050 sd = 0.0317 freq = 0.9077 sd = 0.0220 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0938 freq = 0.0792 freq = 0.0000 freq = 0.0828 allele 2 : freq = 0.9062 freq = 0.9208 freq = 0.0000 freq = 0.9172 ***************************************** **************************************** Analysis of Marker 812: rs812 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001119 pvalue = 0.973318 df = 1 ***************************************** RCHI test RCHI statistic value = 0.195642 pvalue = 0.658262 df = 1 ***************************************** RW test RW statistic value = 0.048060 pvalue = 0.826475 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6617 sd = 0.0511 freq = 0.6615 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 allele 2 : freq = 0.3383 sd = 0.0511 freq = 0.3385 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6687 freq = 0.6479 freq = 0.0000 freq = 0.6531 allele 2 : freq = 0.3312 freq = 0.3521 freq = 0.0000 freq = 0.3469 ***************************************** **************************************** Analysis of Marker 813: rs813 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.030383 pvalue = 0.861623 df = 1 ***************************************** RCHI test RCHI statistic value = 0.220424 pvalue = 0.638717 df = 1 ***************************************** RW test RW statistic value = 0.350839 pvalue = 0.553638 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6233 sd = 0.0523 freq = 0.6269 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 allele 2 : freq = 0.3767 sd = 0.0523 freq = 0.3731 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6188 freq = 0.6417 freq = 0.0000 freq = 0.6359 allele 2 : freq = 0.3812 freq = 0.3583 freq = 0.0000 freq = 0.3641 ***************************************** **************************************** Analysis of Marker 814: rs814 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.718602 pvalue = 0.396603 df = 1 ***************************************** RCHI test RCHI statistic value = 0.985522 pvalue = 0.320839 df = 1 ***************************************** RW test RW statistic value = 0.016272 pvalue = 0.898494 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1883 sd = 0.0422 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.8117 sd = 0.0422 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1938 freq = 0.1562 freq = 0.0000 freq = 0.1656 allele 2 : freq = 0.8063 freq = 0.8438 freq = 0.0000 freq = 0.8344 ***************************************** **************************************** Analysis of Marker 815: rs815 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.248869 pvalue = 0.617873 df = 1 ***************************************** RCHI test RCHI statistic value = 0.141448 pvalue = 0.706846 df = 1 ***************************************** RW test RW statistic value = 1.250885 pvalue = 0.263383 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4283 sd = 0.0534 freq = 0.4231 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.5717 sd = 0.0534 freq = 0.5769 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.4313 freq = 0.0000 freq = 0.4266 allele 2 : freq = 0.5875 freq = 0.5687 freq = 0.0000 freq = 0.5734 ***************************************** **************************************** Analysis of Marker 816: rs816 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.022382 pvalue = 0.881076 df = 1 ***************************************** RCHI test RCHI statistic value = 0.067473 pvalue = 0.795053 df = 1 ***************************************** RW test RW statistic value = 0.532233 pvalue = 0.46567 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8933 sd = 0.0333 freq = 0.8904 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 allele 2 : freq = 0.1067 sd = 0.0333 freq = 0.1096 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8875 freq = 0.8792 freq = 0.0000 freq = 0.8812 allele 2 : freq = 0.1125 freq = 0.1208 freq = 0.0000 freq = 0.1187 ***************************************** **************************************** Analysis of Marker 817: rs817 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.762018 pvalue = 0.184373 df = 1 ***************************************** RCHI test RCHI statistic value = 2.166083 pvalue = 0.141085 df = 1 ***************************************** RW test RW statistic value = 1.720141 pvalue = 0.189675 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3667 sd = 0.0521 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.6333 sd = 0.0521 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.2938 freq = 0.0000 freq = 0.3109 allele 2 : freq = 0.6375 freq = 0.7063 freq = 0.0000 freq = 0.6891 ***************************************** **************************************** Analysis of Marker 818: rs818 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.694259 pvalue = 0.40472 df = 1 ***************************************** RCHI test RCHI statistic value = 1.412695 pvalue = 0.23461 df = 1 ***************************************** RW test RW statistic value = 0.072901 pvalue = 0.78716 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9150 sd = 0.0301 freq = 0.9269 sd = 0.0198 freq = 0.0000 sd = 0.0000 freq = 0.9150 sd = 0.0197 allele 2 : freq = 0.0850 sd = 0.0301 freq = 0.0731 sd = 0.0198 freq = 0.0000 sd = 0.0000 freq = 0.0850 sd = 0.0197 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9000 freq = 0.9333 freq = 0.0000 freq = 0.9250 allele 2 : freq = 0.1000 freq = 0.0667 freq = 0.0000 freq = 0.0750 ***************************************** **************************************** Analysis of Marker 819: rs819 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.098945 pvalue = 0.753099 df = 1 ***************************************** RCHI test RCHI statistic value = 0.073575 pvalue = 0.786201 df = 1 ***************************************** RW test RW statistic value = 0.022313 pvalue = 0.881256 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7033 sd = 0.0493 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 allele 2 : freq = 0.2967 sd = 0.0493 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7125 freq = 0.7000 freq = 0.0000 freq = 0.7031 allele 2 : freq = 0.2875 freq = 0.3000 freq = 0.0000 freq = 0.2969 ***************************************** **************************************** Analysis of Marker 820: rs820 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.569207 pvalue = 0.210322 df = 1 ***************************************** RCHI test RCHI statistic value = 2.536056 pvalue = 0.111272 df = 1 ***************************************** RW test RW statistic value = 0.043143 pvalue = 0.835456 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.5731 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.4269 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5312 freq = 0.6104 freq = 0.0000 freq = 0.5906 allele 2 : freq = 0.4688 freq = 0.3896 freq = 0.0000 freq = 0.4094 ***************************************** **************************************** Analysis of Marker 821: rs821 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.723902 pvalue = 0.394867 df = 1 ***************************************** RCHI test RCHI statistic value = 1.775714 pvalue = 0.182676 df = 1 ***************************************** RW test RW statistic value = 6.134158 pvalue = 0.0132595 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4733 sd = 0.0539 freq = 0.4231 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.5267 sd = 0.0539 freq = 0.5769 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 freq = 0.4083 freq = 0.0000 freq = 0.4250 allele 2 : freq = 0.5250 freq = 0.5917 freq = 0.0000 freq = 0.5750 ***************************************** **************************************** Analysis of Marker 822: rs822 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.153359 pvalue = 0.0757708 df = 1 ***************************************** RCHI test RCHI statistic value = 1.450022 pvalue = 0.228524 df = 1 ***************************************** RW test RW statistic value = 1.798319 pvalue = 0.179916 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2450 sd = 0.0465 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.7550 sd = 0.0465 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.2938 freq = 0.0000 freq = 0.2797 allele 2 : freq = 0.7625 freq = 0.7063 freq = 0.0000 freq = 0.7203 ***************************************** **************************************** Analysis of Marker 823: rs823 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.556592 pvalue = 0.455637 df = 1 ***************************************** RCHI test RCHI statistic value = 0.815566 pvalue = 0.36648 df = 1 ***************************************** RW test RW statistic value = 0.252574 pvalue = 0.615268 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2300 sd = 0.0455 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7700 sd = 0.0455 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2313 freq = 0.2708 freq = 0.0000 freq = 0.2609 allele 2 : freq = 0.7688 freq = 0.7292 freq = 0.0000 freq = 0.7391 ***************************************** **************************************** Analysis of Marker 824: rs824 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.755063 pvalue = 0.384878 df = 1 ***************************************** RCHI test RCHI statistic value = 0.516815 pvalue = 0.472204 df = 1 ***************************************** RW test RW statistic value = 0.590608 pvalue = 0.442184 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4400 sd = 0.0536 freq = 0.4173 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 allele 2 : freq = 0.5600 sd = 0.0536 freq = 0.5827 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.4021 freq = 0.0000 freq = 0.4109 allele 2 : freq = 0.5625 freq = 0.5979 freq = 0.0000 freq = 0.5891 ***************************************** **************************************** Analysis of Marker 825: rs825 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.636625 pvalue = 0.424936 df = 1 ***************************************** RCHI test RCHI statistic value = 0.323230 pvalue = 0.569673 df = 1 ***************************************** RW test RW statistic value = 0.141159 pvalue = 0.707131 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3600 sd = 0.0518 freq = 0.3346 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335 allele 2 : freq = 0.6400 sd = 0.0518 freq = 0.6654 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.3479 freq = 0.0000 freq = 0.3547 allele 2 : freq = 0.6250 freq = 0.6521 freq = 0.0000 freq = 0.6453 ***************************************** **************************************** Analysis of Marker 826: rs826 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.135428 pvalue = 0.712869 df = 1 ***************************************** RCHI test RCHI statistic value = 0.004769 pvalue = 0.944945 df = 1 ***************************************** RW test RW statistic value = 0.013016 pvalue = 0.909168 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1000 sd = 0.0324 freq = 0.1058 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212 allele 2 : freq = 0.9000 sd = 0.0324 freq = 0.8942 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1125 freq = 0.1104 freq = 0.0000 freq = 0.1109 allele 2 : freq = 0.8875 freq = 0.8896 freq = 0.0000 freq = 0.8891 ***************************************** **************************************** Analysis of Marker 827: rs827 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.281057 pvalue = 0.59601 df = 1 ***************************************** RCHI test RCHI statistic value = 0.998809 pvalue = 0.317599 df = 1 ***************************************** RW test RW statistic value = 0.038077 pvalue = 0.845289 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7017 sd = 0.0494 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 allele 2 : freq = 0.2983 sd = 0.0494 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.7396 freq = 0.0000 freq = 0.7281 allele 2 : freq = 0.3063 freq = 0.2604 freq = 0.0000 freq = 0.2719 ***************************************** **************************************** Analysis of Marker 828: rs828 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000191 pvalue = 0.988978 df = 1 ***************************************** RCHI test RCHI statistic value = 0.319337 pvalue = 0.572006 df = 1 ***************************************** RW test RW statistic value = 0.674981 pvalue = 0.411321 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1617 sd = 0.0398 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 allele 2 : freq = 0.8383 sd = 0.0398 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1688 freq = 0.1896 freq = 0.0000 freq = 0.1844 allele 2 : freq = 0.8313 freq = 0.8104 freq = 0.0000 freq = 0.8156 ***************************************** **************************************** Analysis of Marker 829: rs829 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.039054 pvalue = 0.843342 df = 1 ***************************************** RCHI test RCHI statistic value = 0.057225 pvalue = 0.810937 df = 1 ***************************************** RW test RW statistic value = 0.024991 pvalue = 0.874389 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2550 sd = 0.0471 freq = 0.2462 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.7450 sd = 0.0471 freq = 0.7538 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.2542 freq = 0.0000 freq = 0.2516 allele 2 : freq = 0.7562 freq = 0.7458 freq = 0.0000 freq = 0.7484 ***************************************** **************************************** Analysis of Marker 830: rs830 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.232644 pvalue = 0.62957 df = 1 ***************************************** RCHI test RCHI statistic value = 0.504671 pvalue = 0.477455 df = 1 ***************************************** RW test RW statistic value = 0.247088 pvalue = 0.619133 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4717 sd = 0.0539 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.5283 sd = 0.0539 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.4146 freq = 0.0000 freq = 0.4234 allele 2 : freq = 0.5500 freq = 0.5854 freq = 0.0000 freq = 0.5766 ***************************************** **************************************** Analysis of Marker 831: rs831 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.401448 pvalue = 0.526342 df = 1 ***************************************** RCHI test RCHI statistic value = 0.045316 pvalue = 0.831424 df = 1 ***************************************** RW test RW statistic value = 5.322762 pvalue = 0.0210486 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6933 sd = 0.0498 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 allele 2 : freq = 0.3067 sd = 0.0498 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6562 freq = 0.6667 freq = 0.0000 freq = 0.6641 allele 2 : freq = 0.3438 freq = 0.3333 freq = 0.0000 freq = 0.3359 ***************************************** **************************************** Analysis of Marker 832: rs832 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.250974 pvalue = 0.263367 df = 1 ***************************************** RCHI test RCHI statistic value = 0.374871 pvalue = 0.540361 df = 1 ***************************************** RW test RW statistic value = 0.092088 pvalue = 0.76154 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3000 sd = 0.0495 freq = 0.3327 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335 allele 2 : freq = 0.7000 sd = 0.0495 freq = 0.6673 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2875 freq = 0.3167 freq = 0.0000 freq = 0.3094 allele 2 : freq = 0.7125 freq = 0.6833 freq = 0.0000 freq = 0.6906 ***************************************** **************************************** Analysis of Marker 833: rs833 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.125949 pvalue = 0.72267 df = 1 ***************************************** RCHI test RCHI statistic value = 0.336619 pvalue = 0.561788 df = 1 ***************************************** RW test RW statistic value = 1.837762 pvalue = 0.175213 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5133 sd = 0.0540 freq = 0.4712 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 allele 2 : freq = 0.4867 sd = 0.0540 freq = 0.5288 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.4708 freq = 0.0000 freq = 0.4781 allele 2 : freq = 0.5000 freq = 0.5292 freq = 0.0000 freq = 0.5219 ***************************************** **************************************** Analysis of Marker 834: rs834 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.359024 pvalue = 0.243707 df = 1 ***************************************** RCHI test RCHI statistic value = 0.837611 pvalue = 0.360081 df = 1 ***************************************** RW test RW statistic value = 1.171359 pvalue = 0.279122 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 sd = 0.0432 freq = 0.7558 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.2000 sd = 0.0432 freq = 0.2442 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 freq = 0.7604 freq = 0.0000 freq = 0.7703 allele 2 : freq = 0.2000 freq = 0.2396 freq = 0.0000 freq = 0.2297 ***************************************** **************************************** Analysis of Marker 835: rs835 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.057669 pvalue = 0.303747 df = 1 ***************************************** RCHI test RCHI statistic value = 0.565058 pvalue = 0.45223 df = 1 ***************************************** RW test RW statistic value = 0.171367 pvalue = 0.6789 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8917 sd = 0.0336 freq = 0.8788 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 allele 2 : freq = 0.1083 sd = 0.0336 freq = 0.1212 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9062 freq = 0.8812 freq = 0.0000 freq = 0.8875 allele 2 : freq = 0.0938 freq = 0.1187 freq = 0.0000 freq = 0.1125 ***************************************** **************************************** Analysis of Marker 836: rs836 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.032187 pvalue = 0.857617 df = 1 ***************************************** RCHI test RCHI statistic value = 0.047164 pvalue = 0.828074 df = 1 ***************************************** RW test RW statistic value = 0.623059 pvalue = 0.429913 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3317 sd = 0.0509 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 allele 2 : freq = 0.6683 sd = 0.0509 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.3542 freq = 0.0000 freq = 0.3516 allele 2 : freq = 0.6562 freq = 0.6458 freq = 0.0000 freq = 0.6484 ***************************************** **************************************** Analysis of Marker 837: rs837 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001239 pvalue = 0.971919 df = 1 ***************************************** RCHI test RCHI statistic value = 0.006870 pvalue = 0.933944 df = 1 ***************************************** RW test RW statistic value = 1.912765 pvalue = 0.166656 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4950 sd = 0.0540 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 allele 2 : freq = 0.5050 sd = 0.0540 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4938 freq = 0.4979 freq = 0.0000 freq = 0.4969 allele 2 : freq = 0.5062 freq = 0.5021 freq = 0.0000 freq = 0.5031 ***************************************** **************************************** Analysis of Marker 838: rs838 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.016949 pvalue = 0.896418 df = 1 ***************************************** RCHI test RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1 ***************************************** RW test RW statistic value = 0.125862 pvalue = 0.722762 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8458 freq = 0.0000 freq = 0.8438 allele 2 : freq = 0.1625 freq = 0.1542 freq = 0.0000 freq = 0.1562 ***************************************** **************************************** Analysis of Marker 839: rs839 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.121439 pvalue = 0.727479 df = 1 ***************************************** RCHI test RCHI statistic value = 0.112161 pvalue = 0.737697 df = 1 ***************************************** RW test RW statistic value = 0.056230 pvalue = 0.812557 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2442 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7558 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.2521 freq = 0.0000 freq = 0.2484 allele 2 : freq = 0.7625 freq = 0.7479 freq = 0.0000 freq = 0.7516 ***************************************** **************************************** Analysis of Marker 840: rs840 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.930951 pvalue = 0.0868963 df = 1 ***************************************** RCHI test RCHI statistic value = 1.468611 pvalue = 0.225565 df = 1 ***************************************** RW test RW statistic value = 0.068826 pvalue = 0.793053 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3567 sd = 0.0517 freq = 0.4423 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.6433 sd = 0.0517 freq = 0.5577 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3563 freq = 0.4167 freq = 0.0000 freq = 0.4016 allele 2 : freq = 0.6438 freq = 0.5833 freq = 0.0000 freq = 0.5984 ***************************************** **************************************** Analysis of Marker 841: rs841 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000024 pvalue = 0.996068 df = 1 ***************************************** RCHI test RCHI statistic value = 0.402364 pvalue = 0.525871 df = 1 ***************************************** RW test RW statistic value = 1.581463 pvalue = 0.20855 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3983 sd = 0.0529 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 allele 2 : freq = 0.6017 sd = 0.0529 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3875 freq = 0.3563 freq = 0.0000 freq = 0.3641 allele 2 : freq = 0.6125 freq = 0.6438 freq = 0.0000 freq = 0.6359 ***************************************** **************************************** Analysis of Marker 842: rs842 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.976478 pvalue = 0.0844829 df = 1 ***************************************** RCHI test RCHI statistic value = 2.007435 pvalue = 0.15653 df = 1 ***************************************** RW test RW statistic value = 6.268055 pvalue = 0.0122934 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1967 sd = 0.0429 freq = 0.1250 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.1300 sd = 0.0238 allele 2 : freq = 0.8033 sd = 0.0429 freq = 0.8750 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.8700 sd = 0.0238 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1812 freq = 0.1333 freq = 0.0000 freq = 0.1453 allele 2 : freq = 0.8187 freq = 0.8667 freq = 0.0000 freq = 0.8547 ***************************************** **************************************** Analysis of Marker 843: rs843 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.116676 pvalue = 0.732668 df = 1 ***************************************** RCHI test RCHI statistic value = 0.018760 pvalue = 0.891057 df = 1 ***************************************** RW test RW statistic value = 0.058260 pvalue = 0.809268 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6917 sd = 0.0499 freq = 0.7038 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321 allele 2 : freq = 0.3083 sd = 0.0499 freq = 0.2962 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.7000 freq = 0.0000 freq = 0.6984 allele 2 : freq = 0.3063 freq = 0.3000 freq = 0.0000 freq = 0.3016 ***************************************** **************************************** Analysis of Marker 844: rs844 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.550361 pvalue = 0.45817 df = 1 ***************************************** RCHI test RCHI statistic value = 0.852740 pvalue = 0.355778 df = 1 ***************************************** RW test RW statistic value = 0.032508 pvalue = 0.856917 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6017 sd = 0.0529 freq = 0.5673 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349 allele 2 : freq = 0.3983 sd = 0.0529 freq = 0.4327 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6062 freq = 0.5604 freq = 0.0000 freq = 0.5719 allele 2 : freq = 0.3937 freq = 0.4396 freq = 0.0000 freq = 0.4281 ***************************************** **************************************** Analysis of Marker 845: rs845 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.847782 pvalue = 0.357181 df = 1 ***************************************** RCHI test RCHI statistic value = 0.386842 pvalue = 0.533964 df = 1 ***************************************** RW test RW statistic value = 0.624775 pvalue = 0.429278 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2200 sd = 0.0447 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.7800 sd = 0.0447 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2125 freq = 0.2396 freq = 0.0000 freq = 0.2328 allele 2 : freq = 0.7875 freq = 0.7604 freq = 0.0000 freq = 0.7672 ***************************************** **************************************** Analysis of Marker 846: rs846 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.951610 pvalue = 0.0260664 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 3.961742 pvalue = 0.0465455 df = 1 ***************************************** RW test RW statistic value = 1.453804 pvalue = 0.227919 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5683 sd = 0.0535 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.4317 sd = 0.0535 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.4750 freq = 0.0000 freq = 0.5000 allele 2 : freq = 0.4250 freq = 0.5250 freq = 0.0000 freq = 0.5000 ***************************************** **************************************** Analysis of Marker 847: rs847 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.975661 pvalue = 0.323273 df = 1 ***************************************** RCHI test RCHI statistic value = 1.124566 pvalue = 0.288937 df = 1 ***************************************** RW test RW statistic value = 0.816595 pvalue = 0.366177 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8017 sd = 0.0431 freq = 0.8423 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 allele 2 : freq = 0.1983 sd = 0.0431 freq = 0.1577 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.8458 freq = 0.0000 freq = 0.8359 allele 2 : freq = 0.1938 freq = 0.1542 freq = 0.0000 freq = 0.1641 ***************************************** **************************************** Analysis of Marker 848: rs848 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.679498 pvalue = 0.194991 df = 1 ***************************************** RCHI test RCHI statistic value = 1.384759 pvalue = 0.239292 df = 1 ***************************************** RW test RW statistic value = 2.014173 pvalue = 0.155836 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1100 sd = 0.0338 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 allele 2 : freq = 0.8900 sd = 0.0338 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1062 freq = 0.1479 freq = 0.0000 freq = 0.1375 allele 2 : freq = 0.8938 freq = 0.8521 freq = 0.0000 freq = 0.8625 ***************************************** **************************************** Analysis of Marker 849: rs849 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.540857 pvalue = 0.462078 df = 1 ***************************************** RCHI test RCHI statistic value = 1.533830 pvalue = 0.215539 df = 1 ***************************************** RW test RW statistic value = 0.261658 pvalue = 0.608983 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6917 sd = 0.0499 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331 allele 2 : freq = 0.3083 sd = 0.0499 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.6354 freq = 0.0000 freq = 0.6500 allele 2 : freq = 0.3063 freq = 0.3646 freq = 0.0000 freq = 0.3500 ***************************************** **************************************** Analysis of Marker 850: rs850 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.061017 pvalue = 0.804896 df = 1 ***************************************** RCHI test RCHI statistic value = 0.300161 pvalue = 0.583781 df = 1 ***************************************** RW test RW statistic value = 0.003641 pvalue = 0.951883 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7133 sd = 0.0488 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321 allele 2 : freq = 0.2867 sd = 0.0488 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7063 freq = 0.7312 freq = 0.0000 freq = 0.7250 allele 2 : freq = 0.2938 freq = 0.2687 freq = 0.0000 freq = 0.2750 ***************************************** **************************************** Analysis of Marker 851: rs851 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.214319 pvalue = 0.643403 df = 1 ***************************************** RCHI test RCHI statistic value = 0.148496 pvalue = 0.699977 df = 1 ***************************************** RW test RW statistic value = 0.275867 pvalue = 0.599423 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7433 sd = 0.0472 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.2567 sd = 0.0472 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7375 freq = 0.7542 freq = 0.0000 freq = 0.7500 allele 2 : freq = 0.2625 freq = 0.2458 freq = 0.0000 freq = 0.2500 ***************************************** **************************************** Analysis of Marker 852: rs852 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.298378 pvalue = 0.584901 df = 1 ***************************************** RCHI test RCHI statistic value = 0.437209 pvalue = 0.508473 df = 1 ***************************************** RW test RW statistic value = 0.326510 pvalue = 0.567721 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7967 sd = 0.0435 freq = 0.7923 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2033 sd = 0.0435 freq = 0.2077 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.7792 freq = 0.0000 freq = 0.7859 allele 2 : freq = 0.1938 freq = 0.2208 freq = 0.0000 freq = 0.2141 ***************************************** **************************************** Analysis of Marker 853: rs853 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.418698 pvalue = 0.517588 df = 1 ***************************************** RCHI test RCHI statistic value = 0.142258 pvalue = 0.706047 df = 1 ***************************************** RW test RW statistic value = 2.996046 pvalue = 0.083468 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4683 sd = 0.0539 freq = 0.4154 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 allele 2 : freq = 0.5317 sd = 0.0539 freq = 0.5846 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4562 freq = 0.4375 freq = 0.0000 freq = 0.4422 allele 2 : freq = 0.5437 freq = 0.5625 freq = 0.0000 freq = 0.5578 ***************************************** **************************************** Analysis of Marker 854: rs854 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000053 pvalue = 0.994187 df = 1 ***************************************** RCHI test RCHI statistic value = 0.009281 pvalue = 0.923252 df = 1 ***************************************** RW test RW statistic value = 0.042811 pvalue = 0.836081 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2538 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7462 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.2396 freq = 0.0000 freq = 0.2406 allele 2 : freq = 0.7562 freq = 0.7604 freq = 0.0000 freq = 0.7594 ***************************************** **************************************** Analysis of Marker 855: rs855 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.186839 pvalue = 0.665561 df = 1 ***************************************** RCHI test RCHI statistic value = 0.770104 pvalue = 0.380185 df = 1 ***************************************** RW test RW statistic value = 0.597893 pvalue = 0.439383 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4483 sd = 0.0537 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.5517 sd = 0.0537 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4437 freq = 0.4000 freq = 0.0000 freq = 0.4109 allele 2 : freq = 0.5563 freq = 0.6000 freq = 0.0000 freq = 0.5891 ***************************************** **************************************** Analysis of Marker 856: rs856 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.199593 pvalue = 0.65505 df = 1 ***************************************** RCHI test RCHI statistic value = 0.721629 pvalue = 0.39561 df = 1 ***************************************** RW test RW statistic value = 0.113452 pvalue = 0.736247 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3983 sd = 0.0529 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 allele 2 : freq = 0.6017 sd = 0.0529 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4000 freq = 0.3583 freq = 0.0000 freq = 0.3688 allele 2 : freq = 0.6000 freq = 0.6417 freq = 0.0000 freq = 0.6312 ***************************************** **************************************** Analysis of Marker 857: rs857 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.348675 pvalue = 0.12539 df = 1 ***************************************** RCHI test RCHI statistic value = 3.041338 pvalue = 0.081169 df = 1 ***************************************** RW test RW statistic value = 0.027824 pvalue = 0.867523 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 sd = 0.0506 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 allele 2 : freq = 0.3250 sd = 0.0506 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6625 freq = 0.7417 freq = 0.0000 freq = 0.7219 allele 2 : freq = 0.3375 freq = 0.2583 freq = 0.0000 freq = 0.2781 ***************************************** **************************************** Analysis of Marker 858: rs858 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 4.879486 pvalue = 0.0271777 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** RCHI test RCHI statistic value = 5.436308 pvalue = 0.0197223 df = 1 The p-value might not be exact because of the small number of allele 2 in cases ***************************************** RW test RW statistic value = 1.530963 pvalue = 0.215968 df = 1 The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9500 sd = 0.0235 freq = 0.8923 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207 allele 2 : freq = 0.0500 sd = 0.0235 freq = 0.1077 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9563 freq = 0.8875 freq = 0.0000 freq = 0.9047 allele 2 : freq = 0.0437 freq = 0.1125 freq = 0.0000 freq = 0.0953 ***************************************** **************************************** Analysis of Marker 859: rs859 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.541300 pvalue = 0.461894 df = 1 ***************************************** RCHI test RCHI statistic value = 0.280573 pvalue = 0.596326 df = 1 ***************************************** RW test RW statistic value = 0.620308 pvalue = 0.430933 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8783 sd = 0.0353 freq = 0.8885 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221 allele 2 : freq = 0.1217 sd = 0.0353 freq = 0.1115 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8688 freq = 0.8854 freq = 0.0000 freq = 0.8812 allele 2 : freq = 0.1313 freq = 0.1146 freq = 0.0000 freq = 0.1187 ***************************************** **************************************** Analysis of Marker 860: rs860 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.217507 pvalue = 0.26985 df = 1 ***************************************** RCHI test RCHI statistic value = 0.885628 pvalue = 0.346665 df = 1 ***************************************** RW test RW statistic value = 0.961765 pvalue = 0.326743 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9367 sd = 0.0263 freq = 0.8942 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202 allele 2 : freq = 0.0633 sd = 0.0263 freq = 0.1058 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9375 freq = 0.9104 freq = 0.0000 freq = 0.9172 allele 2 : freq = 0.0625 freq = 0.0896 freq = 0.0000 freq = 0.0828 ***************************************** **************************************** Analysis of Marker 861: rs861 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.837688 pvalue = 0.175222 df = 1 ***************************************** RCHI test RCHI statistic value = 1.352564 pvalue = 0.24483 df = 1 ***************************************** RW test RW statistic value = 3.744697 pvalue = 0.0529753 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4167 sd = 0.0533 freq = 0.4731 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 allele 2 : freq = 0.5833 sd = 0.0533 freq = 0.5269 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4062 freq = 0.4646 freq = 0.0000 freq = 0.4500 allele 2 : freq = 0.5938 freq = 0.5354 freq = 0.0000 freq = 0.5500 ***************************************** **************************************** Analysis of Marker 862: rs862 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.004755 pvalue = 0.945026 df = 1 ***************************************** RCHI test RCHI statistic value = 0.019598 pvalue = 0.888667 df = 1 ***************************************** RW test RW statistic value = 0.173311 pvalue = 0.677186 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7383 sd = 0.0475 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 allele 2 : freq = 0.2617 sd = 0.0475 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7312 freq = 0.7250 freq = 0.0000 freq = 0.7266 allele 2 : freq = 0.2687 freq = 0.2750 freq = 0.0000 freq = 0.2734 ***************************************** **************************************** Analysis of Marker 863: rs863 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.024395 pvalue = 0.875883 df = 1 ***************************************** RCHI test RCHI statistic value = 0.173778 pvalue = 0.676776 df = 1 ***************************************** RW test RW statistic value = 0.027321 pvalue = 0.868716 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5375 freq = 0.5167 freq = 0.0000 freq = 0.5219 allele 2 : freq = 0.4625 freq = 0.4833 freq = 0.0000 freq = 0.4781 ***************************************** **************************************** Analysis of Marker 864: rs864 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.154866 pvalue = 0.693928 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.016886 pvalue = 0.89661 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9317 sd = 0.0273 freq = 0.9231 sd = 0.0202 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186 allele 2 : freq = 0.0683 sd = 0.0273 freq = 0.0769 sd = 0.0202 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9375 freq = 0.9375 freq = 0.0000 freq = 0.9375 allele 2 : freq = 0.0625 freq = 0.0625 freq = 0.0000 freq = 0.0625 ***************************************** **************************************** Analysis of Marker 865: rs865 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.305705 pvalue = 0.580328 df = 1 ***************************************** RCHI test RCHI statistic value = 1.711590 pvalue = 0.190779 df = 1 ***************************************** RW test RW statistic value = 2.268092 pvalue = 0.132062 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4017 sd = 0.0530 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 allele 2 : freq = 0.5983 sd = 0.0530 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.3479 freq = 0.0000 freq = 0.3641 allele 2 : freq = 0.5875 freq = 0.6521 freq = 0.0000 freq = 0.6359 ***************************************** **************************************** Analysis of Marker 866: rs866 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.998740 pvalue = 0.0455343 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 2.214743 pvalue = 0.136698 df = 1 ***************************************** RW test RW statistic value = 0.139158 pvalue = 0.709119 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1467 sd = 0.0382 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 allele 2 : freq = 0.8533 sd = 0.0382 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1313 freq = 0.1917 freq = 0.0000 freq = 0.1766 allele 2 : freq = 0.8688 freq = 0.8083 freq = 0.0000 freq = 0.8234 ***************************************** **************************************** Analysis of Marker 867: rs867 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 6.127169 pvalue = 0.013312 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 6.857690 pvalue = 0.00882606 df = 1 ***************************************** RW test RW statistic value = 3.139157 pvalue = 0.0764333 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.4938 freq = 0.0000 freq = 0.4609 allele 2 : freq = 0.6375 freq = 0.5062 freq = 0.0000 freq = 0.5391 ***************************************** **************************************** Analysis of Marker 868: rs868 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.520410 pvalue = 0.470667 df = 1 ***************************************** RCHI test RCHI statistic value = 0.718383 pvalue = 0.396675 df = 1 ***************************************** RW test RW statistic value = 0.153727 pvalue = 0.694999 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6233 sd = 0.0523 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.3767 sd = 0.0523 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6312 freq = 0.5896 freq = 0.0000 freq = 0.6000 allele 2 : freq = 0.3688 freq = 0.4104 freq = 0.0000 freq = 0.4000 ***************************************** **************************************** Analysis of Marker 869: rs869 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.721803 pvalue = 0.189461 df = 1 ***************************************** RCHI test RCHI statistic value = 1.280322 pvalue = 0.257839 df = 1 ***************************************** RW test RW statistic value = 6.562538 pvalue = 0.0104148 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.4423 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.5577 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3688 freq = 0.4250 freq = 0.0000 freq = 0.4109 allele 2 : freq = 0.6312 freq = 0.5750 freq = 0.0000 freq = 0.5891 ***************************************** **************************************** Analysis of Marker 870: rs870 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.629086 pvalue = 0.20183 df = 1 ***************************************** RCHI test RCHI statistic value = 2.556198 pvalue = 0.109863 df = 1 ***************************************** RW test RW statistic value = 0.582281 pvalue = 0.445419 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3550 sd = 0.0517 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 allele 2 : freq = 0.6450 sd = 0.0517 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3625 freq = 0.2875 freq = 0.0000 freq = 0.3063 allele 2 : freq = 0.6375 freq = 0.7125 freq = 0.0000 freq = 0.6937 ***************************************** **************************************** Analysis of Marker 871: rs871 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.549211 pvalue = 0.213252 df = 1 ***************************************** RCHI test RCHI statistic value = 2.181083 pvalue = 0.139716 df = 1 ***************************************** RW test RW statistic value = 2.288403 pvalue = 0.130344 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2687 freq = 0.2062 freq = 0.0000 freq = 0.2219 allele 2 : freq = 0.7312 freq = 0.7937 freq = 0.0000 freq = 0.7781 ***************************************** **************************************** Analysis of Marker 872: rs872 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.658144 pvalue = 0.417216 df = 1 ***************************************** RCHI test RCHI statistic value = 0.840349 pvalue = 0.359297 df = 1 ***************************************** RW test RW statistic value = 2.134649 pvalue = 0.144003 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8550 sd = 0.0380 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 allele 2 : freq = 0.1450 sd = 0.0380 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8083 freq = 0.0000 freq = 0.8172 allele 2 : freq = 0.1562 freq = 0.1917 freq = 0.0000 freq = 0.1828 ***************************************** **************************************** Analysis of Marker 873: rs873 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.317014 pvalue = 0.573408 df = 1 ***************************************** RCHI test RCHI statistic value = 0.376932 pvalue = 0.53925 df = 1 ***************************************** RW test RW statistic value = 0.991750 pvalue = 0.319315 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8283 sd = 0.0407 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 allele 2 : freq = 0.1717 sd = 0.0407 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8187 freq = 0.8417 freq = 0.0000 freq = 0.8359 allele 2 : freq = 0.1812 freq = 0.1583 freq = 0.0000 freq = 0.1641 ***************************************** **************************************** Analysis of Marker 874: rs874 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.007118 pvalue = 0.932766 df = 1 ***************************************** RCHI test RCHI statistic value = 0.067061 pvalue = 0.795665 df = 1 ***************************************** RW test RW statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7900 sd = 0.0440 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 allele 2 : freq = 0.2100 sd = 0.0440 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 freq = 0.8104 freq = 0.0000 freq = 0.8078 allele 2 : freq = 0.2000 freq = 0.1896 freq = 0.0000 freq = 0.1922 ***************************************** **************************************** Analysis of Marker 875: rs875 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.932493 pvalue = 0.334216 df = 1 ***************************************** RCHI test RCHI statistic value = 0.431888 pvalue = 0.511064 df = 1 ***************************************** RW test RW statistic value = 0.162629 pvalue = 0.686747 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7700 sd = 0.0455 freq = 0.7365 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 allele 2 : freq = 0.2300 sd = 0.0455 freq = 0.2635 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 freq = 0.7458 freq = 0.0000 freq = 0.7531 allele 2 : freq = 0.2250 freq = 0.2542 freq = 0.0000 freq = 0.2469 ***************************************** **************************************** Analysis of Marker 876: rs876 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.673345 pvalue = 0.411888 df = 1 ***************************************** RCHI test RCHI statistic value = 1.277347 pvalue = 0.258393 df = 1 ***************************************** RW test RW statistic value = 0.022313 pvalue = 0.881256 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3283 sd = 0.0507 freq = 0.2923 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 allele 2 : freq = 0.6717 sd = 0.0507 freq = 0.7077 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.2729 freq = 0.0000 freq = 0.2859 allele 2 : freq = 0.6750 freq = 0.7271 freq = 0.0000 freq = 0.7141 ***************************************** **************************************** Analysis of Marker 877: rs877 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.546384 pvalue = 0.459799 df = 1 ***************************************** RCHI test RCHI statistic value = 1.475249 pvalue = 0.224519 df = 1 ***************************************** RW test RW statistic value = 1.449588 pvalue = 0.228594 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7933 sd = 0.0437 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.2067 sd = 0.0437 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7937 freq = 0.8417 freq = 0.0000 freq = 0.8297 allele 2 : freq = 0.2062 freq = 0.1583 freq = 0.0000 freq = 0.1703 ***************************************** **************************************** Analysis of Marker 878: rs878 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.640516 pvalue = 0.423524 df = 1 ***************************************** RCHI test RCHI statistic value = 0.172521 pvalue = 0.677881 df = 1 ***************************************** RW test RW statistic value = 0.655666 pvalue = 0.418094 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5700 sd = 0.0535 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 allele 2 : freq = 0.4300 sd = 0.0535 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.5542 freq = 0.0000 freq = 0.5594 allele 2 : freq = 0.4250 freq = 0.4458 freq = 0.0000 freq = 0.4406 ***************************************** **************************************** Analysis of Marker 879: rs879 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.698987 pvalue = 0.403124 df = 1 ***************************************** RCHI test RCHI statistic value = 0.122407 pvalue = 0.726439 df = 1 ***************************************** RW test RW statistic value = 0.175614 pvalue = 0.67517 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6200 sd = 0.0524 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335 allele 2 : freq = 0.3800 sd = 0.0524 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6188 freq = 0.6354 freq = 0.0000 freq = 0.6312 allele 2 : freq = 0.3812 freq = 0.3646 freq = 0.0000 freq = 0.3688 ***************************************** **************************************** Analysis of Marker 880: rs880 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000657 pvalue = 0.979557 df = 1 ***************************************** RCHI test RCHI statistic value = 0.006187 pvalue = 0.937308 df = 1 ***************************************** RW test RW statistic value = 0.067543 pvalue = 0.794948 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9250 sd = 0.0284 freq = 0.9250 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186 allele 2 : freq = 0.0750 sd = 0.0284 freq = 0.0750 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9250 freq = 0.9229 freq = 0.0000 freq = 0.9234 allele 2 : freq = 0.0750 freq = 0.0771 freq = 0.0000 freq = 0.0766 ***************************************** **************************************** Analysis of Marker 881: rs881 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.083611 pvalue = 0.772462 df = 1 ***************************************** RCHI test RCHI statistic value = 0.574854 pvalue = 0.448337 df = 1 ***************************************** RW test RW statistic value = 0.015690 pvalue = 0.900317 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.6250 freq = 0.0000 freq = 0.6156 allele 2 : freq = 0.4125 freq = 0.3750 freq = 0.0000 freq = 0.3844 ***************************************** **************************************** Analysis of Marker 882: rs882 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.230186 pvalue = 0.631386 df = 1 ***************************************** RCHI test RCHI statistic value = 0.499338 pvalue = 0.479791 df = 1 ***************************************** RW test RW statistic value = 0.399162 pvalue = 0.527522 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 sd = 0.0539 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 allele 2 : freq = 0.5250 sd = 0.0539 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 freq = 0.4396 freq = 0.0000 freq = 0.4484 allele 2 : freq = 0.5250 freq = 0.5604 freq = 0.0000 freq = 0.5516 ***************************************** **************************************** Analysis of Marker 883: rs883 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.188902 pvalue = 0.663832 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.329552 pvalue = 0.565923 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6400 sd = 0.0518 freq = 0.6423 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 allele 2 : freq = 0.3600 sd = 0.0518 freq = 0.3577 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6250 freq = 0.6250 freq = 0.0000 freq = 0.6250 allele 2 : freq = 0.3750 freq = 0.3750 freq = 0.0000 freq = 0.3750 ***************************************** **************************************** Analysis of Marker 884: rs884 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.009499 pvalue = 0.922358 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002847 pvalue = 0.957451 df = 1 ***************************************** RW test RW statistic value = 1.081832 pvalue = 0.298288 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275 allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1812 freq = 0.1833 freq = 0.0000 freq = 0.1828 allele 2 : freq = 0.8187 freq = 0.8167 freq = 0.0000 freq = 0.8172 ***************************************** **************************************** Analysis of Marker 885: rs885 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.721543 pvalue = 0.395638 df = 1 ***************************************** RCHI test RCHI statistic value = 1.747037 pvalue = 0.18625 df = 1 ***************************************** RW test RW statistic value = 3.418250 pvalue = 0.0644793 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6900 sd = 0.0500 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 allele 2 : freq = 0.3100 sd = 0.0500 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.6312 freq = 0.0000 freq = 0.6469 allele 2 : freq = 0.3063 freq = 0.3688 freq = 0.0000 freq = 0.3531 ***************************************** **************************************** Analysis of Marker 886: rs886 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.084130 pvalue = 0.771776 df = 1 ***************************************** RCHI test RCHI statistic value = 0.304173 pvalue = 0.581278 df = 1 ***************************************** RW test RW statistic value = 0.047821 pvalue = 0.826899 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.1542 freq = 0.0000 freq = 0.1594 allele 2 : freq = 0.8250 freq = 0.8458 freq = 0.0000 freq = 0.8406 ***************************************** **************************************** Analysis of Marker 887: rs887 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.358116 pvalue = 0.549555 df = 1 ***************************************** RCHI test RCHI statistic value = 0.065255 pvalue = 0.798375 df = 1 ***************************************** RW test RW statistic value = 0.256480 pvalue = 0.612548 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4483 sd = 0.0537 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 allele 2 : freq = 0.5517 sd = 0.0537 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 freq = 0.4375 freq = 0.0000 freq = 0.4344 allele 2 : freq = 0.5750 freq = 0.5625 freq = 0.0000 freq = 0.5656 ***************************************** **************************************** Analysis of Marker 888: rs888 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.502033 pvalue = 0.478608 df = 1 ***************************************** RCHI test RCHI statistic value = 0.545271 pvalue = 0.460256 df = 1 ***************************************** RW test RW statistic value = 0.362218 pvalue = 0.547277 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2050 sd = 0.0436 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 allele 2 : freq = 0.7950 sd = 0.0436 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2062 freq = 0.2375 freq = 0.0000 freq = 0.2297 allele 2 : freq = 0.7937 freq = 0.7625 freq = 0.0000 freq = 0.7703 ***************************************** **************************************** Analysis of Marker 889: rs889 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.301614 pvalue = 0.582872 df = 1 ***************************************** RCHI test RCHI statistic value = 0.572167 pvalue = 0.449399 df = 1 ***************************************** RW test RW statistic value = 0.004442 pvalue = 0.946861 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 freq = 0.7688 freq = 0.0000 freq = 0.7766 allele 2 : freq = 0.2000 freq = 0.2313 freq = 0.0000 freq = 0.2234 ***************************************** **************************************** Analysis of Marker 890: rs890 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.438769 pvalue = 0.507717 df = 1 ***************************************** RCHI test RCHI statistic value = 1.009306 pvalue = 0.315069 df = 1 ***************************************** RW test RW statistic value = 0.149987 pvalue = 0.698548 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1450 sd = 0.0380 freq = 0.1808 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 allele 2 : freq = 0.8550 sd = 0.0380 freq = 0.8192 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1500 freq = 0.1875 freq = 0.0000 freq = 0.1781 allele 2 : freq = 0.8500 freq = 0.8125 freq = 0.0000 freq = 0.8219 ***************************************** **************************************** Analysis of Marker 891: rs891 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.772057 pvalue = 0.379581 df = 1 ***************************************** RCHI test RCHI statistic value = 0.157233 pvalue = 0.691717 df = 1 ***************************************** RW test RW statistic value = 0.573064 pvalue = 0.449044 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7283 sd = 0.0480 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 allele 2 : freq = 0.2717 sd = 0.0480 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7125 freq = 0.6937 freq = 0.0000 freq = 0.6984 allele 2 : freq = 0.2875 freq = 0.3063 freq = 0.0000 freq = 0.3016 ***************************************** **************************************** Analysis of Marker 892: rs892 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.282699 pvalue = 0.257398 df = 1 ***************************************** RCHI test RCHI statistic value = 1.417707 pvalue = 0.233781 df = 1 ***************************************** RW test RW statistic value = 0.026872 pvalue = 0.869789 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7617 sd = 0.0460 freq = 0.7981 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 allele 2 : freq = 0.2383 sd = 0.0460 freq = 0.2019 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7375 freq = 0.7875 freq = 0.0000 freq = 0.7750 allele 2 : freq = 0.2625 freq = 0.2125 freq = 0.0000 freq = 0.2250 ***************************************** **************************************** Analysis of Marker 893: rs893 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.138756 pvalue = 0.709521 df = 1 ***************************************** RCHI test RCHI statistic value = 0.712679 pvalue = 0.398556 df = 1 ***************************************** RW test RW statistic value = 1.602685 pvalue = 0.205523 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8800 sd = 0.0351 freq = 0.8923 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 allele 2 : freq = 0.1200 sd = 0.0351 freq = 0.1077 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8812 freq = 0.9083 freq = 0.0000 freq = 0.9016 allele 2 : freq = 0.1187 freq = 0.0917 freq = 0.0000 freq = 0.0984 ***************************************** **************************************** Analysis of Marker 894: rs894 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.362410 pvalue = 0.547171 df = 1 ***************************************** RCHI test RCHI statistic value = 0.205980 pvalue = 0.649937 df = 1 ***************************************** RW test RW statistic value = 3.298603 pvalue = 0.0693388 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2350 sd = 0.0458 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290 allele 2 : freq = 0.7650 sd = 0.0458 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.2188 freq = 0.0000 freq = 0.2234 allele 2 : freq = 0.7625 freq = 0.7812 freq = 0.0000 freq = 0.7766 ***************************************** **************************************** Analysis of Marker 895: rs895 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.852395 pvalue = 0.355876 df = 1 ***************************************** RCHI test RCHI statistic value = 0.128329 pvalue = 0.720171 df = 1 ***************************************** RW test RW statistic value = 0.099632 pvalue = 0.752272 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1133 sd = 0.0342 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8867 sd = 0.0342 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1062 freq = 0.1187 freq = 0.0000 freq = 0.1156 allele 2 : freq = 0.8938 freq = 0.8812 freq = 0.0000 freq = 0.8844 ***************************************** **************************************** Analysis of Marker 896: rs896 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.076412 pvalue = 0.78222 df = 1 ***************************************** RCHI test RCHI statistic value = 0.213185 pvalue = 0.644282 df = 1 ***************************************** RW test RW statistic value = 2.243651 pvalue = 0.134164 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4050 sd = 0.0530 freq = 0.4077 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349 allele 2 : freq = 0.5950 sd = 0.0530 freq = 0.5923 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.4354 freq = 0.0000 freq = 0.4297 allele 2 : freq = 0.5875 freq = 0.5646 freq = 0.0000 freq = 0.5703 ***************************************** **************************************** Analysis of Marker 897: rs897 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.075441 pvalue = 0.783574 df = 1 ***************************************** RCHI test RCHI statistic value = 0.044620 pvalue = 0.832704 df = 1 ***************************************** RW test RW statistic value = 3.293163 pvalue = 0.0695689 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7833 sd = 0.0445 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.2167 sd = 0.0445 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7937 freq = 0.7854 freq = 0.0000 freq = 0.7875 allele 2 : freq = 0.2062 freq = 0.2146 freq = 0.0000 freq = 0.2125 ***************************************** **************************************** Analysis of Marker 898: rs898 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.280120 pvalue = 0.596623 df = 1 ***************************************** RCHI test RCHI statistic value = 0.056480 pvalue = 0.812149 df = 1 ***************************************** RW test RW statistic value = 0.435098 pvalue = 0.509498 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2383 sd = 0.0460 freq = 0.2558 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7617 sd = 0.0460 freq = 0.7442 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2313 freq = 0.2417 freq = 0.0000 freq = 0.2391 allele 2 : freq = 0.7688 freq = 0.7583 freq = 0.0000 freq = 0.7609 ***************************************** **************************************** Analysis of Marker 899: rs899 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.015831 pvalue = 0.899873 df = 1 ***************************************** RCHI test RCHI statistic value = 0.496142 pvalue = 0.4812 df = 1 ***************************************** RW test RW statistic value = 0.299892 pvalue = 0.58395 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5050 sd = 0.0540 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.4950 sd = 0.0540 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5062 freq = 0.5417 freq = 0.0000 freq = 0.5328 allele 2 : freq = 0.4938 freq = 0.4583 freq = 0.0000 freq = 0.4672 ***************************************** **************************************** Analysis of Marker 900: rs900 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.766398 pvalue = 0.0163355 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** RCHI test RCHI statistic value = 3.374604 pvalue = 0.0662085 df = 1 The p-value might not be exact because of the small number of allele 2 in cases ***************************************** RW test RW statistic value = 8.929619 pvalue = 0.00280583 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) The p-value might not be exact because of the small number of type 2 alleles in cases ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9667 sd = 0.0194 freq = 0.8981 sd = 0.0230 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207 allele 2 : freq = 0.0333 sd = 0.0194 freq = 0.1019 sd = 0.0230 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9688 freq = 0.9146 freq = 0.0000 freq = 0.9281 allele 2 : freq = 0.0312 freq = 0.0854 freq = 0.0000 freq = 0.0719 ***************************************** **************************************** Analysis of Marker 901: rs901 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.005970 pvalue = 0.938412 df = 1 ***************************************** RCHI test RCHI statistic value = 0.024607 pvalue = 0.87535 df = 1 ***************************************** RW test RW statistic value = 0.217612 pvalue = 0.640866 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8117 sd = 0.0422 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280 allele 2 : freq = 0.1883 sd = 0.0422 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.8000 freq = 0.0000 freq = 0.8016 allele 2 : freq = 0.1938 freq = 0.2000 freq = 0.0000 freq = 0.1984 ***************************************** **************************************** Analysis of Marker 902: rs902 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.081216 pvalue = 0.775656 df = 1 ***************************************** RCHI test RCHI statistic value = 0.058806 pvalue = 0.808394 df = 1 ***************************************** RW test RW statistic value = 0.271258 pvalue = 0.602489 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8450 sd = 0.0391 freq = 0.8481 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 allele 2 : freq = 0.1550 sd = 0.0391 freq = 0.1519 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8500 freq = 0.8417 freq = 0.0000 freq = 0.8438 allele 2 : freq = 0.1500 freq = 0.1583 freq = 0.0000 freq = 0.1562 ***************************************** **************************************** Analysis of Marker 903: rs903 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.385127 pvalue = 0.23923 df = 1 ***************************************** RCHI test RCHI statistic value = 1.888431 pvalue = 0.169379 df = 1 ***************************************** RW test RW statistic value = 0.170393 pvalue = 0.679763 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5967 sd = 0.0530 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 allele 2 : freq = 0.4033 sd = 0.0530 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5938 freq = 0.5250 freq = 0.0000 freq = 0.5422 allele 2 : freq = 0.4062 freq = 0.4750 freq = 0.0000 freq = 0.4578 ***************************************** **************************************** Analysis of Marker 904: rs904 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.474881 pvalue = 0.49075 df = 1 ***************************************** RCHI test RCHI statistic value = 0.065029 pvalue = 0.798718 df = 1 ***************************************** RW test RW statistic value = 0.001775 pvalue = 0.966395 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8717 sd = 0.0361 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8800 sd = 0.0230 allele 2 : freq = 0.1283 sd = 0.0361 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1200 sd = 0.0230 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8562 freq = 0.8646 freq = 0.0000 freq = 0.8625 allele 2 : freq = 0.1437 freq = 0.1354 freq = 0.0000 freq = 0.1375 ***************************************** **************************************** Analysis of Marker 905: rs905 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000068 pvalue = 0.993403 df = 1 ***************************************** RCHI test RCHI statistic value = 0.027940 pvalue = 0.867249 df = 1 ***************************************** RW test RW statistic value = 0.048808 pvalue = 0.825151 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5687 freq = 0.5771 freq = 0.0000 freq = 0.5750 allele 2 : freq = 0.4313 freq = 0.4229 freq = 0.0000 freq = 0.4250 ***************************************** **************************************** Analysis of Marker 906: rs906 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.298163 pvalue = 0.585036 df = 1 ***************************************** RCHI test RCHI statistic value = 0.043195 pvalue = 0.835358 df = 1 ***************************************** RW test RW statistic value = 1.177302 pvalue = 0.277906 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5717 sd = 0.0534 freq = 0.5288 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 allele 2 : freq = 0.4283 sd = 0.0534 freq = 0.4712 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5687 freq = 0.5583 freq = 0.0000 freq = 0.5609 allele 2 : freq = 0.4313 freq = 0.4417 freq = 0.0000 freq = 0.4391 ***************************************** **************************************** Analysis of Marker 907: rs907 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.265823 pvalue = 0.260552 df = 1 ***************************************** RCHI test RCHI statistic value = 1.510421 pvalue = 0.219075 df = 1 ***************************************** RW test RW statistic value = 0.003365 pvalue = 0.953739 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7083 sd = 0.0491 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334 allele 2 : freq = 0.2917 sd = 0.0491 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7063 freq = 0.6479 freq = 0.0000 freq = 0.6625 allele 2 : freq = 0.2938 freq = 0.3521 freq = 0.0000 freq = 0.3375 ***************************************** **************************************** Analysis of Marker 908: rs908 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.071382 pvalue = 0.300633 df = 1 ***************************************** RCHI test RCHI statistic value = 1.140882 pvalue = 0.285466 df = 1 ***************************************** RW test RW statistic value = 0.034176 pvalue = 0.853332 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7600 sd = 0.0461 freq = 0.8058 sd = 0.0300 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2400 sd = 0.0461 freq = 0.1942 sd = 0.0300 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.8000 freq = 0.0000 freq = 0.7891 allele 2 : freq = 0.2437 freq = 0.2000 freq = 0.0000 freq = 0.2109 ***************************************** **************************************** Analysis of Marker 909: rs909 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.053893 pvalue = 0.816423 df = 1 ***************************************** RCHI test RCHI statistic value = 0.046525 pvalue = 0.829225 df = 1 ***************************************** RW test RW statistic value = 0.002857 pvalue = 0.957371 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1900 sd = 0.0424 freq = 0.1827 sd = 0.0294 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 allele 2 : freq = 0.8100 sd = 0.0424 freq = 0.8173 sd = 0.0294 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1792 freq = 0.0000 freq = 0.1812 allele 2 : freq = 0.8125 freq = 0.8208 freq = 0.0000 freq = 0.8187 ***************************************** **************************************** Analysis of Marker 910: rs910 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.317664 pvalue = 0.573015 df = 1 ***************************************** RCHI test RCHI statistic value = 2.038101 pvalue = 0.153401 df = 1 ***************************************** RW test RW statistic value = 0.139966 pvalue = 0.708315 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7567 sd = 0.0463 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 allele 2 : freq = 0.2433 sd = 0.0463 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 freq = 0.7146 freq = 0.0000 freq = 0.7297 allele 2 : freq = 0.2250 freq = 0.2854 freq = 0.0000 freq = 0.2703 ***************************************** **************************************** Analysis of Marker 911: rs911 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.858630 pvalue = 0.172783 df = 1 ***************************************** RCHI test RCHI statistic value = 1.572577 pvalue = 0.209833 df = 1 ***************************************** RW test RW statistic value = 1.590337 pvalue = 0.207278 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2217 sd = 0.0449 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 allele 2 : freq = 0.7783 sd = 0.0449 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2188 freq = 0.1708 freq = 0.0000 freq = 0.1828 allele 2 : freq = 0.7812 freq = 0.8292 freq = 0.0000 freq = 0.8172 ***************************************** **************************************** Analysis of Marker 912: rs912 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.363530 pvalue = 0.546552 df = 1 ***************************************** RCHI test RCHI statistic value = 1.545590 pvalue = 0.213788 df = 1 ***************************************** RW test RW statistic value = 0.235685 pvalue = 0.62734 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8217 sd = 0.0413 freq = 0.8615 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 allele 2 : freq = 0.1783 sd = 0.0413 freq = 0.1385 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8313 freq = 0.8771 freq = 0.0000 freq = 0.8656 allele 2 : freq = 0.1688 freq = 0.1229 freq = 0.0000 freq = 0.1344 ***************************************** **************************************** Analysis of Marker 913: rs913 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.496992 pvalue = 0.480825 df = 1 ***************************************** RCHI test RCHI statistic value = 1.588934 pvalue = 0.207478 df = 1 The p-value might not be exact because of the small number of allele 1 in cases ***************************************** RW test RW statistic value = 0.340016 pvalue = 0.55982 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0683 sd = 0.0273 freq = 0.0692 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174 allele 2 : freq = 0.9317 sd = 0.0273 freq = 0.9308 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0563 freq = 0.0875 freq = 0.0000 freq = 0.0797 allele 2 : freq = 0.9437 freq = 0.9125 freq = 0.0000 freq = 0.9203 ***************************************** **************************************** Analysis of Marker 914: rs914 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.469517 pvalue = 0.225422 df = 1 ***************************************** RCHI test RCHI statistic value = 0.212891 pvalue = 0.644511 df = 1 ***************************************** RW test RW statistic value = 0.253118 pvalue = 0.614888 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3217 sd = 0.0505 freq = 0.2750 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 allele 2 : freq = 0.6783 sd = 0.0505 freq = 0.7250 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3167 freq = 0.0000 freq = 0.3219 allele 2 : freq = 0.6625 freq = 0.6833 freq = 0.0000 freq = 0.6781 ***************************************** **************************************** Analysis of Marker 915: rs915 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.194799 pvalue = 0.658952 df = 1 ***************************************** RCHI test RCHI statistic value = 0.144851 pvalue = 0.703505 df = 1 ***************************************** RW test RW statistic value = 0.175718 pvalue = 0.675079 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4233 sd = 0.0534 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 allele 2 : freq = 0.5767 sd = 0.0534 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4188 freq = 0.4000 freq = 0.0000 freq = 0.4047 allele 2 : freq = 0.5813 freq = 0.6000 freq = 0.0000 freq = 0.5953 ***************************************** **************************************** Analysis of Marker 916: rs916 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.591672 pvalue = 0.207087 df = 1 ***************************************** RCHI test RCHI statistic value = 0.985522 pvalue = 0.320839 df = 1 ***************************************** RW test RW statistic value = 3.124652 pvalue = 0.0771164 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 sd = 0.0451 freq = 0.1712 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.7750 sd = 0.0451 freq = 0.8288 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2125 freq = 0.1750 freq = 0.0000 freq = 0.1844 allele 2 : freq = 0.7875 freq = 0.8250 freq = 0.0000 freq = 0.8156 ***************************************** **************************************** Analysis of Marker 917: rs917 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.476660 pvalue = 0.489939 df = 1 ***************************************** RCHI test RCHI statistic value = 0.076641 pvalue = 0.781902 df = 1 ***************************************** RW test RW statistic value = 0.318198 pvalue = 0.572692 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7050 sd = 0.0493 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.2950 sd = 0.0493 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.7000 freq = 0.0000 freq = 0.6969 allele 2 : freq = 0.3125 freq = 0.3000 freq = 0.0000 freq = 0.3031 ***************************************** **************************************** Analysis of Marker 918: rs918 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.624778 pvalue = 0.429277 df = 1 ***************************************** RCHI test RCHI statistic value = 0.355100 pvalue = 0.55124 df = 1 ***************************************** RW test RW statistic value = 0.172786 pvalue = 0.677647 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0933 sd = 0.0314 freq = 0.1173 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221 allele 2 : freq = 0.9067 sd = 0.0314 freq = 0.8827 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0875 freq = 0.1062 freq = 0.0000 freq = 0.1016 allele 2 : freq = 0.9125 freq = 0.8938 freq = 0.0000 freq = 0.8984 ***************************************** **************************************** Analysis of Marker 919: rs919 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.737715 pvalue = 0.0166044 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 3.955407 pvalue = 0.046721 df = 1 ***************************************** RW test RW statistic value = 3.761240 pvalue = 0.0524537 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8583 sd = 0.0377 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 allele 2 : freq = 0.1417 sd = 0.0377 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8500 freq = 0.7646 freq = 0.0000 freq = 0.7859 allele 2 : freq = 0.1500 freq = 0.2354 freq = 0.0000 freq = 0.2141 ***************************************** **************************************** Analysis of Marker 920: rs920 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.294332 pvalue = 0.587458 df = 1 ***************************************** RCHI test RCHI statistic value = 1.213165 pvalue = 0.270706 df = 1 ***************************************** RW test RW statistic value = 0.045070 pvalue = 0.831875 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2933 sd = 0.0492 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 allele 2 : freq = 0.7067 sd = 0.0492 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2750 freq = 0.3250 freq = 0.0000 freq = 0.3125 allele 2 : freq = 0.7250 freq = 0.6750 freq = 0.0000 freq = 0.6875 ***************************************** **************************************** Analysis of Marker 921: rs921 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.204379 pvalue = 0.137619 df = 1 ***************************************** RCHI test RCHI statistic value = 1.670009 pvalue = 0.196257 df = 1 ***************************************** RW test RW statistic value = 0.350808 pvalue = 0.553656 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 sd = 0.0529 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 allele 2 : freq = 0.4000 sd = 0.0529 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6188 freq = 0.5542 freq = 0.0000 freq = 0.5703 allele 2 : freq = 0.3812 freq = 0.4458 freq = 0.0000 freq = 0.4297 ***************************************** **************************************** Analysis of Marker 922: rs922 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.057087 pvalue = 0.81116 df = 1 ***************************************** RCHI test RCHI statistic value = 0.172781 pvalue = 0.677652 df = 1 ***************************************** RW test RW statistic value = 0.015280 pvalue = 0.901623 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4417 sd = 0.0536 freq = 0.4288 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 allele 2 : freq = 0.5583 sd = 0.0536 freq = 0.5712 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.4167 freq = 0.0000 freq = 0.4219 allele 2 : freq = 0.5625 freq = 0.5833 freq = 0.0000 freq = 0.5781 ***************************************** **************************************** Analysis of Marker 923: rs923 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.071935 pvalue = 0.788539 df = 1 ***************************************** RCHI test RCHI statistic value = 0.049842 pvalue = 0.823338 df = 1 ***************************************** RW test RW statistic value = 3.469425 pvalue = 0.062513 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1467 sd = 0.0382 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 allele 2 : freq = 0.8533 sd = 0.0382 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1562 freq = 0.1646 freq = 0.0000 freq = 0.1625 allele 2 : freq = 0.8438 freq = 0.8354 freq = 0.0000 freq = 0.8375 ***************************************** **************************************** Analysis of Marker 924: rs924 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.027265 pvalue = 0.868848 df = 1 ***************************************** RCHI test RCHI statistic value = 0.258703 pvalue = 0.611012 df = 1 ***************************************** RW test RW statistic value = 0.190935 pvalue = 0.66214 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8050 sd = 0.0428 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.1950 sd = 0.0428 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.8271 freq = 0.0000 freq = 0.8219 allele 2 : freq = 0.1938 freq = 0.1729 freq = 0.0000 freq = 0.1781 ***************************************** **************************************** Analysis of Marker 925: rs925 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.462073 pvalue = 0.496657 df = 1 ***************************************** RCHI test RCHI statistic value = 0.481067 pvalue = 0.487939 df = 1 ***************************************** RW test RW statistic value = 1.353766 pvalue = 0.244621 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1917 sd = 0.0425 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275 allele 2 : freq = 0.8083 sd = 0.0425 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2062 freq = 0.1792 freq = 0.0000 freq = 0.1859 allele 2 : freq = 0.7937 freq = 0.8208 freq = 0.0000 freq = 0.8141 ***************************************** **************************************** Analysis of Marker 926: rs926 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.079483 pvalue = 0.778 df = 1 ***************************************** RCHI test RCHI statistic value = 1.283910 pvalue = 0.257173 df = 1 ***************************************** RW test RW statistic value = 0.383408 pvalue = 0.535785 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3567 sd = 0.0517 freq = 0.3654 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 allele 2 : freq = 0.6433 sd = 0.0517 freq = 0.6346 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3500 freq = 0.4042 freq = 0.0000 freq = 0.3906 allele 2 : freq = 0.6500 freq = 0.5958 freq = 0.0000 freq = 0.6094 ***************************************** **************************************** Analysis of Marker 927: rs927 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000162 pvalue = 0.989846 df = 1 ***************************************** RCHI test RCHI statistic value = 0.381802 pvalue = 0.53664 df = 1 ***************************************** RW test RW statistic value = 0.179811 pvalue = 0.671536 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2183 sd = 0.0446 freq = 0.2538 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7817 sd = 0.0446 freq = 0.7462 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.2167 freq = 0.0000 freq = 0.2234 allele 2 : freq = 0.7562 freq = 0.7833 freq = 0.0000 freq = 0.7766 ***************************************** **************************************** Analysis of Marker 928: rs928 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.366643 pvalue = 0.54484 df = 1 ***************************************** RCHI test RCHI statistic value = 1.652446 pvalue = 0.198626 df = 1 ***************************************** RW test RW statistic value = 0.973208 pvalue = 0.323881 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4783 sd = 0.0540 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.5217 sd = 0.0540 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4688 freq = 0.5333 freq = 0.0000 freq = 0.5172 allele 2 : freq = 0.5312 freq = 0.4667 freq = 0.0000 freq = 0.4828 ***************************************** **************************************** Analysis of Marker 929: rs929 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.209212 pvalue = 0.647386 df = 1 ***************************************** RCHI test RCHI statistic value = 0.015607 pvalue = 0.900581 df = 1 ***************************************** RW test RW statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4467 sd = 0.0537 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352 allele 2 : freq = 0.5533 sd = 0.0537 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 freq = 0.4688 freq = 0.0000 freq = 0.4703 allele 2 : freq = 0.5250 freq = 0.5312 freq = 0.0000 freq = 0.5297 ***************************************** **************************************** Analysis of Marker 930: rs930 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.182884 pvalue = 0.668906 df = 1 ***************************************** RCHI test RCHI statistic value = 0.073575 pvalue = 0.786201 df = 1 ***************************************** RW test RW statistic value = 0.139459 pvalue = 0.70882 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7133 sd = 0.0488 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 allele 2 : freq = 0.2867 sd = 0.0488 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7188 freq = 0.7063 freq = 0.0000 freq = 0.7094 allele 2 : freq = 0.2812 freq = 0.2938 freq = 0.0000 freq = 0.2906 ***************************************** **************************************** Analysis of Marker 931: rs931 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.059207 pvalue = 0.807754 df = 1 ***************************************** RCHI test RCHI statistic value = 0.021486 pvalue = 0.883462 df = 1 ***************************************** RW test RW statistic value = 0.150134 pvalue = 0.698408 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7783 sd = 0.0449 freq = 0.7635 sd = 0.0323 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 allele 2 : freq = 0.2217 sd = 0.0449 freq = 0.2365 sd = 0.0323 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7750 freq = 0.7688 freq = 0.0000 freq = 0.7703 allele 2 : freq = 0.2250 freq = 0.2313 freq = 0.0000 freq = 0.2297 ***************************************** **************************************** Analysis of Marker 932: rs932 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.664095 pvalue = 0.415118 df = 1 ***************************************** RCHI test RCHI statistic value = 0.334116 pvalue = 0.563245 df = 1 ***************************************** RW test RW statistic value = 0.823042 pvalue = 0.364292 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7538 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2462 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7875 freq = 0.7625 freq = 0.0000 freq = 0.7688 allele 2 : freq = 0.2125 freq = 0.2375 freq = 0.0000 freq = 0.2313 ***************************************** **************************************** Analysis of Marker 933: rs933 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.321893 pvalue = 0.570472 df = 1 ***************************************** RCHI test RCHI statistic value = 0.007216 pvalue = 0.932302 df = 1 ***************************************** RW test RW statistic value = 1.078584 pvalue = 0.299014 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5717 sd = 0.0534 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 allele 2 : freq = 0.4283 sd = 0.0534 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.5708 freq = 0.0000 freq = 0.5719 allele 2 : freq = 0.4250 freq = 0.4292 freq = 0.0000 freq = 0.4281 ***************************************** **************************************** Analysis of Marker 934: rs934 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.710003 pvalue = 0.190985 df = 1 ***************************************** RCHI test RCHI statistic value = 1.623665 pvalue = 0.202582 df = 1 ***************************************** RW test RW statistic value = 0.416780 pvalue = 0.518548 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3650 sd = 0.0520 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 allele 2 : freq = 0.6350 sd = 0.0520 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.4000 freq = 0.0000 freq = 0.3844 allele 2 : freq = 0.6625 freq = 0.6000 freq = 0.0000 freq = 0.6156 ***************************************** **************************************** Analysis of Marker 935: rs935 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.400819 pvalue = 0.526666 df = 1 ***************************************** RCHI test RCHI statistic value = 0.291560 pvalue = 0.589222 df = 1 ***************************************** RW test RW statistic value = 0.181010 pvalue = 0.670507 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4450 sd = 0.0537 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 allele 2 : freq = 0.5550 sd = 0.0537 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.4646 freq = 0.0000 freq = 0.4578 allele 2 : freq = 0.5625 freq = 0.5354 freq = 0.0000 freq = 0.5422 ***************************************** **************************************** Analysis of Marker 936: rs936 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.081049 pvalue = 0.775881 df = 1 ***************************************** RCHI test RCHI statistic value = 0.424472 pvalue = 0.514714 df = 1 ***************************************** RW test RW statistic value = 0.961765 pvalue = 0.326743 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1017 sd = 0.0326 freq = 0.0904 sd = 0.0218 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202 allele 2 : freq = 0.8983 sd = 0.0326 freq = 0.9096 sd = 0.0218 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0875 freq = 0.1062 freq = 0.0000 freq = 0.1016 allele 2 : freq = 0.9125 freq = 0.8938 freq = 0.0000 freq = 0.8984 ***************************************** **************************************** Analysis of Marker 937: rs937 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.022701 pvalue = 0.880238 df = 1 ***************************************** RCHI test RCHI statistic value = 0.049842 pvalue = 0.823338 df = 1 ***************************************** RW test RW statistic value = 0.027549 pvalue = 0.868174 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8317 sd = 0.0404 freq = 0.8346 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 allele 2 : freq = 0.1683 sd = 0.0404 freq = 0.1654 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.8167 freq = 0.0000 freq = 0.8187 allele 2 : freq = 0.1750 freq = 0.1833 freq = 0.0000 freq = 0.1812 ***************************************** **************************************** Analysis of Marker 938: rs938 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.015937 pvalue = 0.899541 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003366 pvalue = 0.953734 df = 1 ***************************************** RW test RW statistic value = 1.552751 pvalue = 0.21273 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8350 sd = 0.0401 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1650 sd = 0.0401 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8417 freq = 0.0000 freq = 0.8422 allele 2 : freq = 0.1562 freq = 0.1583 freq = 0.0000 freq = 0.1578 ***************************************** **************************************** Analysis of Marker 939: rs939 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.217058 pvalue = 0.269939 df = 1 ***************************************** RCHI test RCHI statistic value = 1.267089 pvalue = 0.260314 df = 1 ***************************************** RW test RW statistic value = 1.376020 pvalue = 0.24078 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6667 sd = 0.0509 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338 allele 2 : freq = 0.3333 sd = 0.0509 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6875 freq = 0.6333 freq = 0.0000 freq = 0.6469 allele 2 : freq = 0.3125 freq = 0.3667 freq = 0.0000 freq = 0.3531 ***************************************** **************************************** Analysis of Marker 940: rs940 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.379026 pvalue = 0.122974 df = 1 ***************************************** RCHI test RCHI statistic value = 2.845260 pvalue = 0.0916438 df = 1 ***************************************** RW test RW statistic value = 0.241849 pvalue = 0.622874 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1933 sd = 0.0427 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 allele 2 : freq = 0.8067 sd = 0.0427 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1750 freq = 0.2458 freq = 0.0000 freq = 0.2281 allele 2 : freq = 0.8250 freq = 0.7542 freq = 0.0000 freq = 0.7719 ***************************************** **************************************** Analysis of Marker 941: rs941 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.043295 pvalue = 0.835171 df = 1 ***************************************** RCHI test RCHI statistic value = 0.024607 pvalue = 0.87535 df = 1 ***************************************** RW test RW statistic value = 0.838506 pvalue = 0.359824 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1867 sd = 0.0421 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280 allele 2 : freq = 0.8133 sd = 0.0421 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1938 freq = 0.0000 freq = 0.1922 allele 2 : freq = 0.8125 freq = 0.8063 freq = 0.0000 freq = 0.8078 ***************************************** **************************************** Analysis of Marker 942: rs942 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.307308 pvalue = 0.252883 df = 1 ***************************************** RCHI test RCHI statistic value = 1.748834 pvalue = 0.186023 df = 1 ***************************************** RW test RW statistic value = 0.429604 pvalue = 0.512183 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8183 sd = 0.0416 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.1817 sd = 0.0416 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.7708 freq = 0.0000 freq = 0.7844 allele 2 : freq = 0.1750 freq = 0.2292 freq = 0.0000 freq = 0.2156 ***************************************** **************************************** Analysis of Marker 943: rs943 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.027628 pvalue = 0.867986 df = 1 ***************************************** RCHI test RCHI statistic value = 0.107018 pvalue = 0.743564 df = 1 ***************************************** RW test RW statistic value = 0.073026 pvalue = 0.786981 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1800 sd = 0.0415 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 allele 2 : freq = 0.8200 sd = 0.0415 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.2000 freq = 0.0000 freq = 0.1969 allele 2 : freq = 0.8125 freq = 0.8000 freq = 0.0000 freq = 0.8031 ***************************************** **************************************** Analysis of Marker 944: rs944 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.005669 pvalue = 0.939979 df = 1 ***************************************** RCHI test RCHI statistic value = 0.318826 pvalue = 0.572314 df = 1 ***************************************** RW test RW statistic value = 1.009253 pvalue = 0.315082 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3583 sd = 0.0518 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 allele 2 : freq = 0.6417 sd = 0.0518 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3438 freq = 0.3167 freq = 0.0000 freq = 0.3234 allele 2 : freq = 0.6562 freq = 0.6833 freq = 0.0000 freq = 0.6766 ***************************************** **************************************** Analysis of Marker 945: rs945 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.147927 pvalue = 0.700524 df = 1 ***************************************** RCHI test RCHI statistic value = 0.072695 pvalue = 0.787453 df = 1 ***************************************** RW test RW statistic value = 0.891765 pvalue = 0.344999 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8033 sd = 0.0429 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272 allele 2 : freq = 0.1967 sd = 0.0429 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8063 freq = 0.8167 freq = 0.0000 freq = 0.8141 allele 2 : freq = 0.1938 freq = 0.1833 freq = 0.0000 freq = 0.1859 ***************************************** **************************************** Analysis of Marker 946: rs946 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.018204 pvalue = 0.892672 df = 1 ***************************************** RCHI test RCHI statistic value = 0.017902 pvalue = 0.893563 df = 1 ***************************************** RW test RW statistic value = 0.000217 pvalue = 0.988242 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6817 sd = 0.0503 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.3183 sd = 0.0503 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 freq = 0.6687 freq = 0.0000 freq = 0.6703 allele 2 : freq = 0.3250 freq = 0.3312 freq = 0.0000 freq = 0.3297 ***************************************** **************************************** Analysis of Marker 947: rs947 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.100947 pvalue = 0.750697 df = 1 ***************************************** RCHI test RCHI statistic value = 0.010004 pvalue = 0.920327 df = 1 ***************************************** RW test RW statistic value = 1.836097 pvalue = 0.175409 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7583 freq = 0.0000 freq = 0.7594 allele 2 : freq = 0.2375 freq = 0.2417 freq = 0.0000 freq = 0.2406 ***************************************** **************************************** Analysis of Marker 948: rs948 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.223484 pvalue = 0.135926 df = 1 ***************************************** RCHI test RCHI statistic value = 1.160526 pvalue = 0.281356 df = 1 ***************************************** RW test RW statistic value = 0.566984 pvalue = 0.45146 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5687 freq = 0.5146 freq = 0.0000 freq = 0.5281 allele 2 : freq = 0.4313 freq = 0.4854 freq = 0.0000 freq = 0.4719 ***************************************** **************************************** Analysis of Marker 949: rs949 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000019 pvalue = 0.996501 df = 1 ***************************************** RCHI test RCHI statistic value = 0.112401 pvalue = 0.737427 df = 1 ***************************************** RW test RW statistic value = 0.580034 pvalue = 0.446299 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5983 sd = 0.0530 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350 allele 2 : freq = 0.4017 sd = 0.0530 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5813 freq = 0.5979 freq = 0.0000 freq = 0.5938 allele 2 : freq = 0.4188 freq = 0.4021 freq = 0.0000 freq = 0.4062 ***************************************** **************************************** Analysis of Marker 950: rs950 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.312339 pvalue = 0.576249 df = 1 ***************************************** RCHI test RCHI statistic value = 0.136250 pvalue = 0.712037 df = 1 ***************************************** RW test RW statistic value = 1.562868 pvalue = 0.211246 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.7077 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.2923 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7438 freq = 0.7271 freq = 0.0000 freq = 0.7312 allele 2 : freq = 0.2562 freq = 0.2729 freq = 0.0000 freq = 0.2687 ***************************************** **************************************** Analysis of Marker 951: rs951 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.006995 pvalue = 0.933344 df = 1 ***************************************** RCHI test RCHI statistic value = 0.008175 pvalue = 0.927957 df = 1 ***************************************** RW test RW statistic value = 0.273339 pvalue = 0.601101 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7033 sd = 0.0493 freq = 0.6981 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 allele 2 : freq = 0.2967 sd = 0.0493 freq = 0.3019 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6937 freq = 0.6896 freq = 0.0000 freq = 0.6906 allele 2 : freq = 0.3063 freq = 0.3104 freq = 0.0000 freq = 0.3094 ***************************************** **************************************** Analysis of Marker 952: rs952 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000514 pvalue = 0.981911 df = 1 ***************************************** RCHI test RCHI statistic value = 0.020333 pvalue = 0.886612 df = 1 ***************************************** RW test RW statistic value = 0.002220 pvalue = 0.962421 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7467 sd = 0.0470 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 allele 2 : freq = 0.2533 sd = 0.0470 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7438 freq = 0.7375 freq = 0.0000 freq = 0.7391 allele 2 : freq = 0.2562 freq = 0.2625 freq = 0.0000 freq = 0.2609 ***************************************** **************************************** Analysis of Marker 953: rs953 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.065838 pvalue = 0.797496 df = 1 ***************************************** RCHI test RCHI statistic value = 0.006951 pvalue = 0.933555 df = 1 ***************************************** RW test RW statistic value = 0.273968 pvalue = 0.600683 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4450 sd = 0.0537 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.5550 sd = 0.0537 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4313 freq = 0.4354 freq = 0.0000 freq = 0.4344 allele 2 : freq = 0.5687 freq = 0.5646 freq = 0.0000 freq = 0.5656 ***************************************** **************************************** Analysis of Marker 954: rs954 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.197771 pvalue = 0.656526 df = 1 ***************************************** RCHI test RCHI statistic value = 0.011891 pvalue = 0.913166 df = 1 ***************************************** RW test RW statistic value = 0.292103 pvalue = 0.588876 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1650 sd = 0.0401 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 allele 2 : freq = 0.8350 sd = 0.0401 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1562 freq = 0.1604 freq = 0.0000 freq = 0.1594 allele 2 : freq = 0.8438 freq = 0.8396 freq = 0.0000 freq = 0.8406 ***************************************** **************************************** Analysis of Marker 955: rs955 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.915665 pvalue = 0.338616 df = 1 ***************************************** RCHI test RCHI statistic value = 0.928830 pvalue = 0.335167 df = 1 ***************************************** RW test RW statistic value = 0.445184 pvalue = 0.504631 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 freq = 0.2938 freq = 0.0000 freq = 0.2828 allele 2 : freq = 0.7500 freq = 0.7063 freq = 0.0000 freq = 0.7172 ***************************************** **************************************** Analysis of Marker 956: rs956 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.244035 pvalue = 0.621307 df = 1 ***************************************** RCHI test RCHI statistic value = 1.005850 pvalue = 0.315899 df = 1 ***************************************** RW test RW statistic value = 0.003050 pvalue = 0.955954 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 sd = 0.0534 freq = 0.4442 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.5750 sd = 0.0534 freq = 0.5558 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4250 freq = 0.4750 freq = 0.0000 freq = 0.4625 allele 2 : freq = 0.5750 freq = 0.5250 freq = 0.0000 freq = 0.5375 ***************************************** **************************************** Analysis of Marker 957: rs957 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.990927 pvalue = 0.158244 df = 1 ***************************************** RCHI test RCHI statistic value = 3.754293 pvalue = 0.0526721 df = 1 ***************************************** RW test RW statistic value = 0.720790 pvalue = 0.395885 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5650 sd = 0.0535 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 allele 2 : freq = 0.4350 sd = 0.0535 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5437 freq = 0.6396 freq = 0.0000 freq = 0.6156 allele 2 : freq = 0.4562 freq = 0.3604 freq = 0.0000 freq = 0.3844 ***************************************** **************************************** Analysis of Marker 958: rs958 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 6.608352 pvalue = 0.0101502 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 5.764266 pvalue = 0.0163553 df = 1 ***************************************** RW test RW statistic value = 0.037605 pvalue = 0.846239 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2433 sd = 0.0463 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275 allele 2 : freq = 0.7567 sd = 0.0463 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2687 freq = 0.1750 freq = 0.0000 freq = 0.1984 allele 2 : freq = 0.7312 freq = 0.8250 freq = 0.0000 freq = 0.8016 ***************************************** **************************************** Analysis of Marker 959: rs959 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.086276 pvalue = 0.768965 df = 1 ***************************************** RCHI test RCHI statistic value = 0.207914 pvalue = 0.648407 df = 1 ***************************************** RW test RW statistic value = 0.108058 pvalue = 0.742366 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4900 sd = 0.0540 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 allele 2 : freq = 0.5100 sd = 0.0540 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4938 freq = 0.4708 freq = 0.0000 freq = 0.4766 allele 2 : freq = 0.5062 freq = 0.5292 freq = 0.0000 freq = 0.5234 ***************************************** **************************************** Analysis of Marker 960: rs960 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.509870 pvalue = 0.219159 df = 1 ***************************************** RCHI test RCHI statistic value = 0.989178 pvalue = 0.319943 df = 1 ***************************************** RW test RW statistic value = 0.273339 pvalue = 0.601101 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 sd = 0.0468 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 allele 2 : freq = 0.7500 sd = 0.0468 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 freq = 0.2958 freq = 0.0000 freq = 0.2844 allele 2 : freq = 0.7500 freq = 0.7042 freq = 0.0000 freq = 0.7156 ***************************************** **************************************** Analysis of Marker 961: rs961 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.963315 pvalue = 0.0851731 df = 1 ***************************************** RCHI test RCHI statistic value = 4.213542 pvalue = 0.0401025 df = 1 ***************************************** RW test RW statistic value = 0.139158 pvalue = 0.709119 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.8058 sd = 0.0300 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.1942 sd = 0.0300 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7438 freq = 0.8271 freq = 0.0000 freq = 0.8063 allele 2 : freq = 0.2562 freq = 0.1729 freq = 0.0000 freq = 0.1938 ***************************************** **************************************** Analysis of Marker 962: rs962 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.392849 pvalue = 0.237925 df = 1 ***************************************** RCHI test RCHI statistic value = 1.301291 pvalue = 0.253978 df = 1 ***************************************** RW test RW statistic value = 8.170177 pvalue = 0.00425847 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7933 sd = 0.0437 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 allele 2 : freq = 0.2067 sd = 0.0437 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7875 freq = 0.7375 freq = 0.0000 freq = 0.7500 allele 2 : freq = 0.2125 freq = 0.2625 freq = 0.0000 freq = 0.2500 ***************************************** **************************************** Analysis of Marker 963: rs963 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.898764 pvalue = 0.0886475 df = 1 ***************************************** RCHI test RCHI statistic value = 2.352355 pvalue = 0.125094 df = 1 ***************************************** RW test RW statistic value = 5.045729 pvalue = 0.0246867 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4283 sd = 0.0534 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 allele 2 : freq = 0.5717 sd = 0.0534 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.4896 freq = 0.0000 freq = 0.4703 allele 2 : freq = 0.5875 freq = 0.5104 freq = 0.0000 freq = 0.5297 ***************************************** **************************************** Analysis of Marker 964: rs964 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.549831 pvalue = 0.458387 df = 1 ***************************************** RCHI test RCHI statistic value = 0.386309 pvalue = 0.534246 df = 1 ***************************************** RW test RW statistic value = 0.346598 pvalue = 0.556046 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5375 freq = 0.5062 freq = 0.0000 freq = 0.5141 allele 2 : freq = 0.4625 freq = 0.4938 freq = 0.0000 freq = 0.4859 ***************************************** **************************************** Analysis of Marker 965: rs965 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.035589 pvalue = 0.850367 df = 1 ***************************************** RCHI test RCHI statistic value = 0.095116 pvalue = 0.757771 df = 1 ***************************************** RW test RW statistic value = 0.001907 pvalue = 0.965165 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3433 sd = 0.0513 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 allele 2 : freq = 0.6567 sd = 0.0513 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.3396 freq = 0.0000 freq = 0.3359 allele 2 : freq = 0.6750 freq = 0.6604 freq = 0.0000 freq = 0.6641 ***************************************** **************************************** Analysis of Marker 966: rs966 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.264488 pvalue = 0.260803 df = 1 ***************************************** RCHI test RCHI statistic value = 2.789861 pvalue = 0.0948624 df = 1 ***************************************** RW test RW statistic value = 1.151624 pvalue = 0.28321 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7200 sd = 0.0485 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316 allele 2 : freq = 0.2800 sd = 0.0485 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7562 freq = 0.6813 freq = 0.0000 freq = 0.7000 allele 2 : freq = 0.2437 freq = 0.3187 freq = 0.0000 freq = 0.3000 ***************************************** **************************************** Analysis of Marker 967: rs967 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.098610 pvalue = 0.753504 df = 1 ***************************************** RCHI test RCHI statistic value = 0.297274 pvalue = 0.585597 df = 1 ***************************************** RW test RW statistic value = 0.032456 pvalue = 0.857031 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1904 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8096 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1688 freq = 0.1896 freq = 0.0000 freq = 0.1844 allele 2 : freq = 0.8313 freq = 0.8104 freq = 0.0000 freq = 0.8156 ***************************************** **************************************** Analysis of Marker 968: rs968 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.004964 pvalue = 0.943829 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 3.126523 pvalue = 0.0770279 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2687 freq = 0.2687 freq = 0.0000 freq = 0.2687 allele 2 : freq = 0.7312 freq = 0.7312 freq = 0.0000 freq = 0.7312 ***************************************** **************************************** Analysis of Marker 969: rs969 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.045650 pvalue = 0.830813 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003115 pvalue = 0.95549 df = 1 ***************************************** RW test RW statistic value = 0.326842 pvalue = 0.567524 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8367 sd = 0.0399 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262 allele 2 : freq = 0.1633 sd = 0.0399 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8438 freq = 0.8417 freq = 0.0000 freq = 0.8422 allele 2 : freq = 0.1562 freq = 0.1583 freq = 0.0000 freq = 0.1578 ***************************************** **************************************** Analysis of Marker 970: rs970 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.483112 pvalue = 0.487016 df = 1 ***************************************** RCHI test RCHI statistic value = 0.841087 pvalue = 0.359086 df = 1 ***************************************** RW test RW statistic value = 0.027321 pvalue = 0.868716 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4558 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5442 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4688 freq = 0.4229 freq = 0.0000 freq = 0.4344 allele 2 : freq = 0.5312 freq = 0.5771 freq = 0.0000 freq = 0.5656 ***************************************** **************************************** Analysis of Marker 971: rs971 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.746424 pvalue = 0.186327 df = 1 ***************************************** RCHI test RCHI statistic value = 1.859713 pvalue = 0.172658 df = 1 ***************************************** RW test RW statistic value = 0.442453 pvalue = 0.505941 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0800 sd = 0.0293 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 allele 2 : freq = 0.9200 sd = 0.0293 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0813 freq = 0.1250 freq = 0.0000 freq = 0.1141 allele 2 : freq = 0.9187 freq = 0.8750 freq = 0.0000 freq = 0.8859 ***************************************** **************************************** Analysis of Marker 972: rs972 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.809071 pvalue = 0.368395 df = 1 ***************************************** RCHI test RCHI statistic value = 0.459845 pvalue = 0.497696 df = 1 ***************************************** RW test RW statistic value = 1.612144 pvalue = 0.204191 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3183 sd = 0.0503 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 allele 2 : freq = 0.6817 sd = 0.0503 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3375 freq = 0.3063 freq = 0.0000 freq = 0.3141 allele 2 : freq = 0.6625 freq = 0.6937 freq = 0.0000 freq = 0.6859 ***************************************** **************************************** Analysis of Marker 973: rs973 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.350022 pvalue = 0.554101 df = 1 ***************************************** RCHI test RCHI statistic value = 0.269890 pvalue = 0.603405 df = 1 ***************************************** RW test RW statistic value = 0.000460 pvalue = 0.982881 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1350 sd = 0.0369 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226 allele 2 : freq = 0.8650 sd = 0.0369 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1313 freq = 0.1146 freq = 0.0000 freq = 0.1187 allele 2 : freq = 0.8688 freq = 0.8854 freq = 0.0000 freq = 0.8812 ***************************************** **************************************** Analysis of Marker 974: rs974 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.116741 pvalue = 0.732597 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.144990 pvalue = 0.70337 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6117 sd = 0.0526 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 allele 2 : freq = 0.3883 sd = 0.0526 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.6000 freq = 0.0000 freq = 0.6000 allele 2 : freq = 0.4000 freq = 0.4000 freq = 0.0000 freq = 0.4000 ***************************************** **************************************** Analysis of Marker 975: rs975 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.838684 pvalue = 0.359773 df = 1 ***************************************** RCHI test RCHI statistic value = 0.642959 pvalue = 0.422641 df = 1 ***************************************** RW test RW statistic value = 1.867520 pvalue = 0.171759 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4467 sd = 0.0537 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 allele 2 : freq = 0.5533 sd = 0.0537 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4437 freq = 0.4042 freq = 0.0000 freq = 0.4141 allele 2 : freq = 0.5563 freq = 0.5958 freq = 0.0000 freq = 0.5859 ***************************************** **************************************** Analysis of Marker 976: rs976 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.319470 pvalue = 0.571927 df = 1 ***************************************** RCHI test RCHI statistic value = 0.139361 pvalue = 0.708917 df = 1 ***************************************** RW test RW statistic value = 1.799439 pvalue = 0.17978 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7033 sd = 0.0493 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 allele 2 : freq = 0.2967 sd = 0.0493 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7063 freq = 0.7229 freq = 0.0000 freq = 0.7188 allele 2 : freq = 0.2938 freq = 0.2771 freq = 0.0000 freq = 0.2812 ***************************************** **************************************** Analysis of Marker 977: rs977 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.056014 pvalue = 0.812911 df = 1 ***************************************** RCHI test RCHI statistic value = 0.024607 pvalue = 0.87535 df = 1 ***************************************** RW test RW statistic value = 0.096716 pvalue = 0.755806 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8217 sd = 0.0413 freq = 0.8173 sd = 0.0294 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280 allele 2 : freq = 0.1783 sd = 0.0413 freq = 0.1827 sd = 0.0294 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8187 freq = 0.8250 freq = 0.0000 freq = 0.8234 allele 2 : freq = 0.1812 freq = 0.1750 freq = 0.0000 freq = 0.1766 ***************************************** **************************************** Analysis of Marker 978: rs978 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.460468 pvalue = 0.497405 df = 1 ***************************************** RCHI test RCHI statistic value = 3.238076 pvalue = 0.0719451 df = 1 ***************************************** RW test RW statistic value = 0.513441 pvalue = 0.473653 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7283 sd = 0.0480 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.2717 sd = 0.0480 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7250 freq = 0.6438 freq = 0.0000 freq = 0.6641 allele 2 : freq = 0.2750 freq = 0.3563 freq = 0.0000 freq = 0.3359 ***************************************** **************************************** Analysis of Marker 979: rs979 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.229146 pvalue = 0.135429 df = 1 ***************************************** RCHI test RCHI statistic value = 0.842476 pvalue = 0.35869 df = 1 ***************************************** RW test RW statistic value = 1.001664 pvalue = 0.316908 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6533 sd = 0.0514 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 allele 2 : freq = 0.3467 sd = 0.0514 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 freq = 0.6917 freq = 0.0000 freq = 0.6813 allele 2 : freq = 0.3500 freq = 0.3083 freq = 0.0000 freq = 0.3187 ***************************************** **************************************** Analysis of Marker 980: rs980 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.869985 pvalue = 0.0154012 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 5.023297 pvalue = 0.0250085 df = 1 ***************************************** RW test RW statistic value = 2.152546 pvalue = 0.142334 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5050 sd = 0.0540 freq = 0.3635 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 allele 2 : freq = 0.4950 sd = 0.0540 freq = 0.6365 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.3896 freq = 0.0000 freq = 0.4172 allele 2 : freq = 0.5000 freq = 0.6104 freq = 0.0000 freq = 0.5828 ***************************************** **************************************** Analysis of Marker 981: rs981 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.007835 pvalue = 0.929468 df = 1 ***************************************** RCHI test RCHI statistic value = 0.009156 pvalue = 0.923769 df = 1 ***************************************** RW test RW statistic value = 0.056230 pvalue = 0.812557 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2437 freq = 0.2396 freq = 0.0000 freq = 0.2406 allele 2 : freq = 0.7562 freq = 0.7604 freq = 0.0000 freq = 0.7594 ***************************************** **************************************** Analysis of Marker 982: rs982 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.298922 pvalue = 0.129464 df = 1 ***************************************** RCHI test RCHI statistic value = 1.885947 pvalue = 0.16966 df = 1 ***************************************** RW test RW statistic value = 0.885757 pvalue = 0.34663 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7517 sd = 0.0467 freq = 0.8038 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288 allele 2 : freq = 0.2483 sd = 0.0467 freq = 0.1962 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7375 freq = 0.7937 freq = 0.0000 freq = 0.7797 allele 2 : freq = 0.2625 freq = 0.2062 freq = 0.0000 freq = 0.2203 ***************************************** **************************************** Analysis of Marker 983: rs983 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.015412 pvalue = 0.901199 df = 1 ***************************************** RCHI test RCHI statistic value = 0.171676 pvalue = 0.678627 df = 1 ***************************************** RW test RW statistic value = 0.263577 pvalue = 0.607673 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1850 sd = 0.0419 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 allele 2 : freq = 0.8150 sd = 0.0419 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1875 freq = 0.1708 freq = 0.0000 freq = 0.1750 allele 2 : freq = 0.8125 freq = 0.8292 freq = 0.0000 freq = 0.8250 ***************************************** **************************************** Analysis of Marker 984: rs984 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.890255 pvalue = 0.169173 df = 1 ***************************************** RCHI test RCHI statistic value = 1.839380 pvalue = 0.175024 df = 1 ***************************************** RW test RW statistic value = 0.293212 pvalue = 0.588169 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1383 sd = 0.0373 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259 allele 2 : freq = 0.8617 sd = 0.0373 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1187 freq = 0.1688 freq = 0.0000 freq = 0.1562 allele 2 : freq = 0.8812 freq = 0.8313 freq = 0.0000 freq = 0.8438 ***************************************** **************************************** Analysis of Marker 985: rs985 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 5.610408 pvalue = 0.0178541 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** RCHI test RCHI statistic value = 7.604816 pvalue = 0.00582126 df = 1 ***************************************** RW test RW statistic value = 0.089254 pvalue = 0.765128 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3783 sd = 0.0524 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 allele 2 : freq = 0.6217 sd = 0.0524 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3812 freq = 0.2542 freq = 0.0000 freq = 0.2859 allele 2 : freq = 0.6188 freq = 0.7458 freq = 0.0000 freq = 0.7141 ***************************************** **************************************** Analysis of Marker 986: rs986 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.295876 pvalue = 0.586479 df = 1 ***************************************** RCHI test RCHI statistic value = 0.228140 pvalue = 0.632906 df = 1 ***************************************** RW test RW statistic value = 0.591954 pvalue = 0.441665 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1633 sd = 0.0399 freq = 0.1327 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8367 sd = 0.0399 freq = 0.8673 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1562 freq = 0.1396 freq = 0.0000 freq = 0.1437 allele 2 : freq = 0.8438 freq = 0.8604 freq = 0.0000 freq = 0.8562 ***************************************** **************************************** Analysis of Marker 987: rs987 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.249216 pvalue = 0.617628 df = 1 ***************************************** RCHI test RCHI statistic value = 0.055088 pvalue = 0.814436 df = 1 ***************************************** RW test RW statistic value = 0.086848 pvalue = 0.768223 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2933 sd = 0.0492 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312 allele 2 : freq = 0.7067 sd = 0.0492 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2875 freq = 0.2771 freq = 0.0000 freq = 0.2797 allele 2 : freq = 0.7125 freq = 0.7229 freq = 0.0000 freq = 0.7203 ***************************************** **************************************** Analysis of Marker 988: rs988 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.027546 pvalue = 0.86818 df = 1 ***************************************** RCHI test RCHI statistic value = 0.008255 pvalue = 0.927608 df = 1 ***************************************** RW test RW statistic value = 0.032444 pvalue = 0.857056 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7100 sd = 0.0490 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 allele 2 : freq = 0.2900 sd = 0.0490 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7125 freq = 0.7083 freq = 0.0000 freq = 0.7094 allele 2 : freq = 0.2875 freq = 0.2917 freq = 0.0000 freq = 0.2906 ***************************************** **************************************** Analysis of Marker 989: rs989 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.492887 pvalue = 0.482642 df = 1 ***************************************** RCHI test RCHI statistic value = 0.028248 pvalue = 0.866528 df = 1 ***************************************** RW test RW statistic value = 0.444102 pvalue = 0.505149 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9217 sd = 0.0290 freq = 0.9327 sd = 0.0190 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174 allele 2 : freq = 0.0783 sd = 0.0290 freq = 0.0673 sd = 0.0190 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9125 freq = 0.9083 freq = 0.0000 freq = 0.9094 allele 2 : freq = 0.0875 freq = 0.0917 freq = 0.0000 freq = 0.0906 ***************************************** **************************************** Analysis of Marker 990: rs990 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.497315 pvalue = 0.0614684 df = 1 ***************************************** RCHI test RCHI statistic value = 1.987740 pvalue = 0.158577 df = 1 ***************************************** RW test RW statistic value = 0.979973 pvalue = 0.322205 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2833 sd = 0.0487 freq = 0.3346 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 allele 2 : freq = 0.7167 sd = 0.0487 freq = 0.6654 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 freq = 0.3167 freq = 0.0000 freq = 0.3000 allele 2 : freq = 0.7500 freq = 0.6833 freq = 0.0000 freq = 0.7000 ***************************************** **************************************** Analysis of Marker 991: rs991 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.884205 pvalue = 0.347053 df = 1 ***************************************** RCHI test RCHI statistic value = 0.744980 pvalue = 0.38807 df = 1 ***************************************** RW test RW statistic value = 0.632886 pvalue = 0.426299 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3033 sd = 0.0497 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 allele 2 : freq = 0.6967 sd = 0.0497 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3312 freq = 0.2917 freq = 0.0000 freq = 0.3016 allele 2 : freq = 0.6687 freq = 0.7083 freq = 0.0000 freq = 0.6984 ***************************************** **************************************** Analysis of Marker 992: rs992 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.393726 pvalue = 0.237777 df = 1 ***************************************** RCHI test RCHI statistic value = 0.913087 pvalue = 0.339297 df = 1 ***************************************** RW test RW statistic value = 0.005149 pvalue = 0.942794 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 sd = 0.0529 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 allele 2 : freq = 0.4000 sd = 0.0529 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6000 freq = 0.6458 freq = 0.0000 freq = 0.6344 allele 2 : freq = 0.4000 freq = 0.3542 freq = 0.0000 freq = 0.3656 ***************************************** **************************************** Analysis of Marker 993: rs993 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.621670 pvalue = 0.202859 df = 1 ***************************************** RCHI test RCHI statistic value = 1.354605 pvalue = 0.244475 df = 1 ***************************************** RW test RW statistic value = 0.003018 pvalue = 0.956187 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5483 sd = 0.0538 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352 allele 2 : freq = 0.4517 sd = 0.0538 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5938 freq = 0.5354 freq = 0.0000 freq = 0.5500 allele 2 : freq = 0.4062 freq = 0.4646 freq = 0.0000 freq = 0.4500 ***************************************** **************************************** Analysis of Marker 994: rs994 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.165258 pvalue = 0.280378 df = 1 ***************************************** RCHI test RCHI statistic value = 0.468789 pvalue = 0.493545 df = 1 ***************************************** RW test RW statistic value = 0.019993 pvalue = 0.887557 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6800 sd = 0.0504 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.3200 sd = 0.0504 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6750 freq = 0.6417 freq = 0.0000 freq = 0.6500 allele 2 : freq = 0.3250 freq = 0.3583 freq = 0.0000 freq = 0.3500 ***************************************** **************************************** Analysis of Marker 995: rs995 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.178786 pvalue = 0.0746001 df = 1 ***************************************** RCHI test RCHI statistic value = 1.669067 pvalue = 0.196383 df = 1 ***************************************** RW test RW statistic value = 0.628494 pvalue = 0.427908 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7900 sd = 0.0440 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317 allele 2 : freq = 0.2100 sd = 0.0440 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7937 freq = 0.7354 freq = 0.0000 freq = 0.7500 allele 2 : freq = 0.2062 freq = 0.2646 freq = 0.0000 freq = 0.2500 ***************************************** **************************************** Analysis of Marker 996: rs996 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.969221 pvalue = 0.324875 df = 1 ***************************************** RCHI test RCHI statistic value = 1.869733 pvalue = 0.171506 df = 1 ***************************************** RW test RW statistic value = 6.625281 pvalue = 0.0100541 df = 1 Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5367 sd = 0.0539 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 allele 2 : freq = 0.4633 sd = 0.0539 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5375 freq = 0.4688 freq = 0.0000 freq = 0.4859 allele 2 : freq = 0.4625 freq = 0.5312 freq = 0.0000 freq = 0.5141 ***************************************** **************************************** Analysis of Marker 997: rs997 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.168285 pvalue = 0.68164 df = 1 ***************************************** RCHI test RCHI statistic value = 0.273496 pvalue = 0.600996 df = 1 ***************************************** RW test RW statistic value = 0.010161 pvalue = 0.919709 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3333 sd = 0.0509 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 allele 2 : freq = 0.6667 sd = 0.0509 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3312 freq = 0.3563 freq = 0.0000 freq = 0.3500 allele 2 : freq = 0.6687 freq = 0.6438 freq = 0.0000 freq = 0.6500 ***************************************** **************************************** Analysis of Marker 998: rs998 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.039320 pvalue = 0.842817 df = 1 ***************************************** RCHI test RCHI statistic value = 0.086331 pvalue = 0.768894 df = 1 ***************************************** RW test RW statistic value = 0.196974 pvalue = 0.657175 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4533 sd = 0.0538 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349 allele 2 : freq = 0.5467 sd = 0.0538 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4375 freq = 0.4521 freq = 0.0000 freq = 0.4484 allele 2 : freq = 0.5625 freq = 0.5479 freq = 0.0000 freq = 0.5516 ***************************************** **************************************** Analysis of Marker 999: rs999 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.931930 pvalue = 0.334362 df = 1 ***************************************** RCHI test RCHI statistic value = 1.823302 pvalue = 0.176921 df = 1 ***************************************** RW test RW statistic value = 1.661334 pvalue = 0.197423 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1800 sd = 0.0415 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 allele 2 : freq = 0.8200 sd = 0.0415 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1938 freq = 0.2500 freq = 0.0000 freq = 0.2359 allele 2 : freq = 0.8063 freq = 0.7500 freq = 0.0000 freq = 0.7641 ***************************************** **************************************** Analysis of Marker 1000: rs1000 **************************************** There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.027542 pvalue = 0.86819 df = 1 ***************************************** RCHI test RCHI statistic value = 0.116009 pvalue = 0.733404 df = 1 ***************************************** RW test RW statistic value = 0.016030 pvalue = 0.899249 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6312 freq = 0.6479 freq = 0.0000 freq = 0.6438 allele 2 : freq = 0.3688 freq = 0.3521 freq = 0.0000 freq = 0.3563 *****************************************