XMAP: Cross-population fine-mapping by leveraging genetic diversity and accounting for confounding bias.

ABSTRACT: Fine-mapping prioritizes risk variants identified by genome-wide association studies (GWASs), serving as a critical step to uncover biological mechanisms underlying complex traits. However, several major challenges still remain for existing fine-mapping methods. First, the strong linkage disequilibrium among variants can limit the statistical power and resolution of fine-mapping. Second, it is computationally expensive to simultaneously search for multiple causal variants. Third, the confounding bias hidden in GWAS summary statistics can produce spurious signals. To address these challenges, we develop a statistical method for cross-population fine-mapping (XMAP) by leveraging genetic diversity and accounting for confounding bias. By using cross-population GWAS summary statistics from glob

SUBMITTER: Cai M 

PROVIDER: S-EPMC10613261 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature