Taught by Dr. Bruce Weir, University of Washington. Methods and designs using genetic data are built upon the foundation of population genetics. In this module, you will learn these foundations, including the Hardy Weinberg principle, genetic drift, population structure, inbreeding, and linkage disequilibrium. These principles will be essential to subsequent modules in this course.

Taught by Dr. Todd Edwards, Vanderbilt University Medical Center. Building from the introduction to population genetics, in this module you will learn processes that lead to genetic differences between populations, methods to characterize these differences, and how to conduct association studies in structured populations. In addition, you will be able to describe how admixture methods can be applied for association mapping.

Taught by Dr. Gonçalo Abecasis, University of Michigan and Regeneron, Inc. Quality control is an important step for high throughput genotype data. In this module, you will learn a range of different approaches to identify and to deal with quality problems at different stages of the analysis. In addition, genotype imputation is introduced to infer genotypes at markers that were not typed in the study samples.

Taught by Dr. Celia Greenwood, McGill University. Population based association studies have played an important role in mapping genes and genomic regions for complex traits by detecting association between alleles and a trait. In this module, you will learn basic measures of association, common modeling strategies, how to adjust for multiple testing and why, how to evaluate association results, and how to increase reproducibility of study results, including the use of meta-analysis and genetic imputation.

Taught by Dr. Joan Bailey Wilson, National Human Genome Research Institute, National Institutes of Health. In this module, you will learn about the various ways in which family-based collections of genetic data are utilized in Genetic Epidemiology. This includes methods that provide support that a genetic component to a trait exists as well as to identify modes of inheritance consistent with a set of data. In addition, linkage methods, which identify large regions of the genome, and association methods, which identify a smaller set of variants, are covered to understand genetic factors affecting a trait.