This module will provide students with the basic tools to carry out genetic association analysis within the context of genome wide association studies (GWAS) and next-generation sequencing studies with considerable emphasis on hands-on learning.
Topics covered include: case-control (disease) association testing; quantitative trait analysis; quality control processes in GWAS; multi-locus testing using gene and pathway information; population structure and ancestry inference; association testing in the presence of population structure and/or relatedness; gene-environment and gene-gene interactions; basic rare variant association analysis in sequencing studies; advanced rare variant methods; sequence kernel association tests (SKAT); meta analysis; design considerations; and other emerging topics.
An important component of this module is in-class software exercises which will provide students with hands-on experience analyzing real data using state-of-the-art analysis tools for GWAS and next generation sequencing data.
Assumes basic familiarity with R. Other public domain software that will be used includes PLINK.
Suggested pairing: Module 14: Advanced Quantitative Genetics and Module 15: Association Mapping: GWAS and Sequencing Data
Learning Objectives: After attending this module, participants will be able to:
- Perform SNP-based association testing with adjustment for covariates in R.
- Run a GWAS with PLINK.
- Create Manhattan plots and quantile-quantile plots in R from PLINK GWAS results.
- Perform multi-loci association testing in PLINK using gene and pathway information.
- Perform principal components analysis (PCA) for population structure inference and correction in a GWAS.
- Perform a linear mixed model (LMM) for GWAS with relatedness and/or population structure.
- Test gene-gene and gene-environment interactions.
- Run sequence kernel association tests and other advanced methods for rare variant association methods.
- Perform a meta-analysis.