SparsePro: An efficient fine-mapping method integrating summary statistics and functional annotations.

ABSTRACT: Identifying causal variants from genome-wide association studies (GWAS) is challenging due to widespread linkage disequilibrium (LD) and the possible existence of multiple causal variants in the same genomic locus. Functional annotations of the genome may help to prioritize variants that are biologically relevant and thus improve fine-mapping of GWAS results. Classical fine-mapping methods conducting an exhaustive search of variant-level causal configurations have a high computational cost, especially when the underlying genetic architecture and LD patterns are complex. SuSiE provided an iterative Bayesian stepwise selection algorithm for efficient fine-mapping. In this work, we build connections between SuSiE and a paired mean field variational inference algorithm through the implementati

SUBMITTER: Zhang W 

PROVIDER: S-EPMC10781022 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature