SharePro: an accurate and efficient genetic colocalization method accounting for multiple causal signals.

ABSTRACT:

Motivation

Colocalization analysis is commonly used to assess whether two or more traits share the same genetic signals identified in genome-wide association studies (GWAS), and is important for prioritizing targets for functional follow-up of GWAS results. Existing colocalization methods can have suboptimal performance when there are multiple causal variants in one genomic locus.

Results

We propose SharePro to extend the COLOC framework for colocalization analysis. SharePro integrates linkage disequilibrium (LD) modeling and colocalization assessment by grouping correlated variants into effect groups. With an efficient variational inference algorithm, posterior colocalization probabilities can be accurately estimated. In simulation studies, SharePro demonstrated increased p

SUBMITTER: Zhang W 

PROVIDER: S-EPMC11105950 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature