An empirical Bayes approach to improving population-specific genetic association estimation by leveraging cross-population data.

ABSTRACT: Populations of non-European ancestry are substantially underrepresented in genome-wide association studies (GWAS). As genetic effects can differ between ancestries due to possibly different causal variants or linkage disequilibrium patterns, a meta-analysis that includes GWAS of all populations yields biased estimation in each of the populations and the bias disproportionately impacts non-European ancestry populations. This is because meta-analysis combines study-specific estimates with inverse variance as the weights, which causes biases towards studies with the largest sample size, typical of the European ancestry population. In this paper, we propose two empirical Bayes (EB) estimators to borrow the strength of information across populations although accounting for between-population he

SUBMITTER: Hsu L 

PROVIDER: S-EPMC9892209 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature