Introduction to Statistical Genetics

Catalog description

This course will cover quantitative topics in human statistical genetics, including the HapMap project, linkage disequilibrium, population structure and stratification, natural selection, genome-wide association studies, estimating and partitioning heritability, association testing, statistical fine-mapping, disease gene mapping, expression quantitative trait loci, single-cell genomics, and polygenic risk prediction. The course will emphasize hands-on analysis of large empirical data sets, thus requiring prior experience with a general-purpose high-level programming language such as Python. After taking this course, each student will have the experience and skills to develop and apply statistical methods to population genetic data. Prerequisites: ( 02-120 or 15-112 ) and ( 36-226 or 36-236 or 15-259 or 15-260 or 02-680 or 36-218 )