1.1 Overview of MORGAN

MORGAN (Monte Carlo Genetic Analysis) is a collection of programs and libraries developed at the University of Washington under the PANGAEA (Pedigree Analysis for Genetics and Epidemiological Attributes) umbrella. This software implements a number of methods for the analysis of data observed on members of a pedigree, with the main programs implementing Markov Chain Monte Carlo (MCMC) methods. As of the date of this tutorial, the latest MORGAN version is 2.9 which was released in August 2008. It is available for download through the MORGAN V2.6 home page at the Department of Statistics, University of Washington.

The MORGAN programs are grouped into four categories:

1. Programs using deterministic algorithms: pedcheck checks for errors in pedigree structure and data format, see Checking Pedigree Validity. kin computes kinship and inbreeding coefficients for members of the pedigree, see Computing Kinship and One- or Two-Locus Inbreeding Coefficients.

2. Programs using simple Monte Carlo techniques (by simulating data on founders and "dropping" genes down the pedigree): genedrop simulates data on a pedigree for analysis by other programs, see Simulating Marker and Trait Data in Pedigrees. markerdrop simulates marker data at loci linked to a potential trait locus, see Simulating Marker Data Conditional on Trait Data in Pedigrees. ibddrop uses Monte Carlo to estimate gene ibd (identity by descent) probabilities in the absence of data, see Estimating a priori IBD Probabilities by Monte Carlo.

3. Programs using Markov chain Monte Carlo (MCMC) techniques: MORGAN's MCMC programs are split into two sections, "Autozyg" and "Lodscore". The Autozyg programs, lm_auto and lm_pval, estimate conditional gene ibd probabilities, see Estimating Conditional IBD Probabilities by MCMC. The Lodscore programs, lm_lods, lm_markers, lm_bayes and lm_schnell estimate multilocus LOD scores, see Estimating Location LOD Scores by MCMC. A brief introduction to the MCMC techniques employed by MORGAN can be found in Using MCMC to Estimate Parameters of Interest in Pedigree Data.

4. Programs using EM algorithm for segregation analysis with quantitative traits: includes univar, unibig, bivar and multivar, see Polygenic Modeling of Quantitative Traits by EM Algorithm.

This tutorial is based on the computing notes of Dr. Elizabeth Thompson. Descriptions of the parameter statements are taken from the `README_userdoc' files written by Myrna Jewett. The original version of this document was written in 2002 by Michael Na Li, and revised by Myrna Jewett and Adele Mitchell in 2006. It was revised again for MORGAN 2.8.3 with new Examples by Audrey Q. Fu. The current version together together with updated Examples for MORGAN 2.9 was by Tia Lerud in 2009, further revised by Marshall Brown in 2010.

Combined with hands-on examples, this tutorial gives a brief introduction to the usage of the main MORGAN programs. For further information, please refer to the MORGAN documentation and to the references cited.