Cross-population enhancement of PrediXcan predictions with a gnomAD-based east Asian reference framework.

ABSTRACT: Over the past decade, genome-wide association studies have identified thousands of variants significantly associated with complex traits. For each locus, gene expression levels are needed to further explore its biological functions. To address this, the PrediXcan algorithm leverages large-scale reference data to impute the gene expression level from single nucleotide polymorphisms, and thus the gene-trait associations can be tested to identify the candidate causal genes. However, a challenge arises due to the fact that most reference data are from subjects of European ancestry, and the accuracy and robustness of predicted gene expression in subjects of East Asian (EAS) ancestry remains unclear. Here, we first simulated a variety of scenarios to explore the impact of the level of population

SUBMITTER: Chan HC 

PROVIDER: S-EPMC11497844 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature