This module provides an overview of genetic epidemiology, with a focus on design, analysis and interpretation in studies of complex disease. The module is meant as an introduction to the field with a focus on surveying the various methods for discovering how genetic factors influence health and disease.

It discusses classic genetic epidemiology methods and study designs, including twin studies, family studies, segregation analysis, linkage analysis and population-based association studies, as well as more contemporary topics including gene-environment interactions, rare variant analysis and precision medicine applications. These topics will be reinforced through in-class exercises along with critical reading and discussion of recent publications.

Suggested pairng: This module is a great preparation for Module 15: Association Mapping: GWAS and Sequencing Data and Module 17: Computational Pipeline for WGS data. 

Learning Objectives: After attending this module, participants will be able to:

1. Conduct and interpret simple genetic association analyses.
2. Interpret common plots used to present genetic epidemiology results, and describe their rationale.
3. Describe the various ways population genetic patterns affect genetic epidemiology studies and the methods to account for these patterns in research.
4. Describe best practices for reproducible genetic epidemiology research.
5. Describe the ethical and public policy implications of genetic epidemiology results.