Methods for Analyzing Biobank Data: Statistical, Computational, and Privacy Challenges

Explore methods for analyzing biobank data in this comprehensive lecture from the Computational Genomics Summer Institute (CGSI) 2024. Delve into statistical, computational, and privacy challenges associated with large-scale genomic datasets. Learn about scalable estimators of SNP heritability for biobank-scale data, efficient variance components analysis for millions of genomes, and robust methods for uncovering gene-environment interactions in complex traits. Discover insights into genome-wide signals of polygenic epistasis and summary statistics-based heritability estimation with individual genotype level accuracy. Gain valuable knowledge on cutting-edge techniques and recent advancements in the field of computational genomics, supported by references to key publications and preprints in prestigious journals such as Bioinformatics, Nature Communications, and Genome Research.

Sriram Sankararaman | Methods for Analyzing Biobank Data: Statistical, Computational ... | CGSI 2024