This module assumes the material in Modules 1 and 4. Material in Modules 7 and 10  would be helpful. This module focuses on the genetics and analysis of quantitative traits in human populations, with emphasis on estimation and prediction analysis using genetic markers. It is a good match with Module 19 that deals with similar topics but with a focus on disease (binary) outcomes. Topics include: the resemblance between relatives; estimation of genetic variance associated with genome-wide identity by descent; GWAS for quantitative traits; the use of GWAS data to estimate and partition genetic variation; principles and pitfalls of prediction analyses using genetic markers. For computer exercises, we will be using R, the Merlin suite of software, PLINK and GCTA (http://www.complextraitgenomics.com/software/gcta/).

Background reading: Vinkhuyzen et al. 2013. Estimation and partition of heritability in human populations using whole-genome analysis methods. Annu Rev Genet. 23;47:75-95. doi: 10.1146/annurev-genet-111212-133258
Yang, J. et al. 2010. Common SNPs explain a large proportion of the heritability for human height. Nature Genetics 42: 565-569.
Wray NR et al. 2013. Pitfalls of predicting complex traits from SNPs. Nature Review Genetics 14:507-15. doi: 10.1038/nrg3457.