This course covers methods in statistical genetics used to detect disease or quantitative trait loci in experimental and human populations. Basic concepts in Genetics, Genomics and Genetic Epidemiology are reviewed, with an emphasis on the statistical and practical issues involved in genetic analysis. Both linkage and association approaches will be covered, with a focus on applications in the human genome wide association (GWAS) setting for both SNPs and CNVs. Approaches to extracting and enriching GWAS through genotype imputation, GSEA, meta-analysis and genetics of gene expression analysis will also be covered, along with topics relevant to pharmacogenetics and techniques to analyze next generation sequencing data in a population setting.
At the end of the course, students will be able to:
Use appropriate methods and tools to explore and interpret underlying genetic structure and architecture in the GWAS setting.
Design case-control studies that are sufficiently powered.
Perform and interpret pedigree linkage analysis and genetics association for binary and quantitative traits using standard statistical approaches.
Apply various methods to account for population substructure and multiplicity in GWAS analysis.
Apply advanced techniques to improve inference and interpretation of association studies.