A Practical Introduction to Statistical Genetics
Sponsored by the MGH Division of Clinical Research
Brief description: This course provides a comprehensive introduction to modern statistical genetics and covers widely-used genetic analysis methods including genome-wide association studies (GWAS), statistical fine-mapping, polygenic risk score analysis, heritability and genetic correlation analyses, Mendelian randomization, transcriptome-wide association studies (TWAS), sequencing data analysis and genomic research using publicly available biobank resources. The course focuses on statistical analysis of large-scale genetic datasets, with an outlook to cutting-edge research and state-of-the-art statistical genetics methods. The course is a modified version of a genomic epidemiology workshop initiated and designed by Chia-Yen Chen, Hailiang Huang and colleagues, which has been offered in multiple cities in China over the past few years.
Format: 10 90-min sessions; one session per week. The lectures will cover both theory and applications essential to statistical genetics.
Target audience: Investigators, fellows, students and clinicians who wish to expand their toolsets and conduct statistical analysis of large-scale genetic datasets to explore the genetic basis of complex traits and diseases. Basic knowledge of modern concepts in genetics, genomics and statistics is required. Beginning investigators who do not have experience with genetic approaches to complex traits are recommended to first take the course “A Primer on Complex Trait Genetics” offered and sponsored by the MGH Division of Clinical Research.