Genome-wide iterative fine-mapping for non-Gaussian phenotypes.

ABSTRACT: Fine-mapping seeks to identify causal variants associated to a phenotype of interest. Fine-mapping searches through genomic regions previously identified by single marker analysis of genome-wide association studies (GWAS) data. This two-stage approach (1) often fails to identify causal variants with smaller effect sizes, and (2) does not properly correct for multiple comparisons. The former problem leads fine-mapping to have low recall of causal genetic variants, and the latter problem leads to high false discovery rate (FDR). To address these issues, we propose a novel Genome-wide Iterative fiNe-mApping method for non-Gaussian data (GINA-X). GINA-X efficiently extracts information from GWAS data by iterating a screening step and a variable selection step. The screening step provides a lis

SUBMITTER: Xu S 

PROVIDER: S-EPMC12358508 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature