StocSum: A Reference Panel Free Summary Statistics Framework for Diverse Populations

Explore a groundbreaking conference talk from the Computational Genomics Summer Institute (CGSI) 2024 that introduces StocSum, a novel summary statistics framework for diverse populations that operates without the need for a reference panel. Delve into Han Chen's presentation, which outlines an innovative approach to genome-wide association studies (GWAS) and meta-analysis of rare variant associations in large-scale whole-genome sequencing studies. Learn about the efficient variant set mixed model association tests for continuous and binary traits, and discover how StocSum leverages advanced matrix sketching algorithms to enhance computational efficiency. Gain insights into how this framework distinguishes confounding from polygenicity in GWAS and its potential impact on genetic research across diverse populations. Examine the related papers that form the foundation of this research, including works on efficient variant set mixed model association tests, meta-analysis of rare variant associations, and practical sketching algorithms for low-rank matrix approximation.

Han Chen | StocSum: a reference panel free summary statistics framework for diverse... | CGSI 2024