Genetic fine-mapping from summary data using a nonlocal prior improves the detection of multiple causal variants.

ABSTRACT:

Motivation

Genome-wide association studies (GWAS) have been successful in identifying genomic loci associated with complex traits. Genetic fine-mapping aims to detect independent causal variants from the GWAS-identified loci, adjusting for linkage disequilibrium patterns.

Results

We present "FiniMOM" (fine-mapping using a product inverse-moment prior), a novel Bayesian fine-mapping method for summarized genetic associations. For causal effects, the method uses a nonlocal inverse-moment prior, which is a natural prior distribution to model non-null effects in finite samples. A beta-binomial prior is set for the number of causal variants, with a parameterization that can be used to control for potential misspecifications in the linkage disequilibrium reference. The results of

SUBMITTER: Karhunen V 

PROVIDER: S-EPMC10326304 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature