## First line, from the Bioconductor download page; ## (all this does is define the biocLite() function) source("http://bioconductor.org/biocLite.R") ## ## Hexbin ## biocLite("hexbin") ### ONLY NEED TO DO ONCE! library(hexbin) library(Biobase) openVignette("hexbin") #the vignette example x <- rnorm(20000) y <- rnorm(20000) hbin <- hexbin(x, y, xbins = 40) plot(hbin, main="Made-up data, x and y are N(0,1)") #the niehs example niehs <- read.csv("niehs.csv") #which columns are trt, ctrl? trt <- grep("T", names(niehs)) ctrl <- grep("C", names(niehs)) means <- data.frame( trt.mean = rowMeans(niehs[, trt], na.rm=T), ctrl.mean = rowMeans(niehs[,ctrl], na.rm=T) ) hbin2 <- with(means, hexbin(y=trt.mean, x=ctrl.mean) ) plot(hbin2, main="NIEHS data") plot(trt.mean~ctrl.mean, data=means, pch=19, main="NIEHS data (clunky version)") ## ## snpMatrix example ## source("http://bioconductor.org/biocLite.R") biocLite("snpMatrix") ### ONLY NEED TO DO ONCE! library("snpMatrix") load("AMDchrom1.Rdata") snpsum <- summary(amd1) summary(snpsum) show(snpsum) sample.qc <- row.summary(amd1) plot(sample.qc) # plot of call rate vs heterozygosity cc.status <- rep(1:0, times=c(96,50) ) my.tests <- single.snp.tests(cc.status, snp.data=amd1) summary(my.tests) names(my.tests) qq.chisq(chi.squared(my.tests, df=1), df=1) pchisq(c(5,10,15,20,25), df=1, lower=F) ## ## siggenes ## source("http://bioconductor.org/biocLite.R") biocLite("siggenes") ### ONLY NEED TO DO ONCE! library(siggenes) library(multtest) vsn<-read.csv("data.vsn.csv") vsn<-vsn[,-1] ann<-read.table("annt.txt",header=TRUE) sam.cl<-as.character(ann$Donor) sam.cl[!sam.cl=="Hsa"]<-"other primate" sam.cl vsn.out<-sam(vsn, sam.cl, B=1000, rand=42) summary(vsn.out) plot(vsn.out) plot(vsn.out, 3) plot(vsn.out, delta=3)# don't blame me!