Admixed Populations Improve Power for Variant Discovery and Portability in Genome-Wide Association Studies.

ABSTRACT: Genome-wide association studies (GWAS) are primarily conducted in single-ancestry settings. The low transferability of results has limited our understanding of human genetic architecture across a range of complex traits. In contrast to homogeneous populations, admixed populations provide an opportunity to capture genetic architecture contributed from multiple source populations and thus improve statistical power. Here, we provide a mechanistic simulation framework to investigate the statistical power and transferability of GWAS under directional polygenic selection or varying divergence. We focus on a two-way admixed population and show that GWAS in admixed populations can be enriched for power in discovery by up to 2-fold compared to the ancestral populations under similar sample size. Mo

SUBMITTER: Lin M 

PROVIDER: S-EPMC8181458 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature