Fast and Flexible Joint Fine-mapping of Multiple Traits Via the Sum of Single Effects Model

Overview

Journal bioRxiv

Date 2023 Jul 10

PMID 37425935

Authors

Yuxin Zou

Peter Carbonetto

Dongyue Xie

Gao Wang

Matthew Stephens

Affiliations

Soon will be listed here.

Abstract

We introduce mvSuSiE, a multi-trait fine-mapping method for identifying putative causal variants from genetic association data (individual-level or summary data). mvSuSiE learns patterns of shared genetic effects from data, and exploits these patterns to improve power to identify causal SNPs. Comparisons on simulated data show that mvSuSiE is competitive in speed, power and precision with existing multi-trait methods, and uniformly improves on single-trait fine-mapping (SuSiE) in each trait separately. We applied mvSuSiE to jointly fine-map 16 blood cell traits using data from the UK Biobank. By jointly analyzing the traits and modeling heterogeneous effect sharing patterns, we discovered a much larger number of causal SNPs (>3,000) compared with single-trait fine-mapping, and with narrower credible sets. mvSuSiE also more comprehensively characterized the ways in which the genetic variants affect one or more blood cell traits; 68% of causal SNPs showed significant effects in more than one blood cell type.

Citing Articles

Integration of expression QTLs with fine mapping via SuSiE.

Zhang X, Jiang W, Zhao H PLoS Genet. 2024; 20(1):e1010929.

PMID: 38271473 PMC: 10846745. DOI: 10.1371/journal.pgen.1010929.

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