Module dates/times: Wednesday, July 25, 1:30-5 p.m.; Thursday, July 26, 8:30 a.m.-5 p.m., and Friday, July 27, 8:30 a.m.-5 p.m.
This module focuses on the quantitative genetic analysis of common polygenic disease. It contrasts and synthesizes the traditional viewpoints of quantitative geneticists and epidemiologists. The module demonstrates the caution needed in interpreting “precision medicine” 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 modelling; risk profile scoring; power; GxE; pleiotropy and Mendelian Randomisation.
Participants should have basic knowledge of R programming, matrix algebra, statistical methods and analysis of GWAS data.
John Witte is Professor of Epidemiology and Biostatistics at the University of California at San Francisco. His research program encompasses a synthesis of methodological and applied genetic epidemiology, with the overall aim of deciphering the mechanisms underlying complex diseases and traits. His methods work is focused on the design and statistical analysis of next-generation sequencing and genetic association studies, and is applied to studies of prostate cancer, birth defects and pharmacogenomics. He recently published “Non-additive and epistatic effects of HLA polymorphisms contributing to risk of adult glioma.” J Neuro-Oncology 135:237-244, 2017.
Naomi Wray is Professor in the Institute for Molecular Bioscience & Queensland Brain Institute at the University of Queensland. Her research focuses on development of quantitative genetics and genomics methodology with application to psychiatric and neurological disorders. She recently published “Inference in psychiatry via 2-sample Mendelian randomization - From association to causal pathway?” JAMA Psychiatry 74:1191-1192.
Access 2017 Course Materials (2018 materials will be uploaded to this page prior to the start of the module)