This module builds on the advanced quantitative genetics module, but now focusing on the analysis of genetic data for qualitative phenotypes, such as disease status from case-control or cohort studies, and interpretation of the ensuing results particularly with respect to risk prediction. We will consider in detail the statistical genetics of binary disease with emphasis on the equivalences and relationships between different models. We will contrast and synthesize the traditional viewpoints of quantitative geneticists and epidemiologists. We will demonstrate the caution needed in interpreting ³precision medicine² risk predictors for common complex diseases. Topics will include: risk models on different scales including the observed (or disease) scale and the liability threshold scale; estimation of heritability from familial risk ratios; estimation of the contribution of individual and multiple risk loci to disease; estimation of variance attributable to genome-wide SNPs individually and together; approaches for the analysis of rare genetic variants; polygenic modeling; risk profile scoring; power; GxE and pleiotropy. We assume that students have Basic R programming, matrix algebra, statistical methods and analysis of GWAS data. Modules 8 and 10 may be helpful.