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Updated: Jan 13, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data
Jordan Rossen1,2, Huwenbo Shi3, Benjamin J Strober4,5
1Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. jordanerossen@gmail.com.
Abstract:
Leveraging multi-ancestry data can improve fine-mapping power. We propose MultiSuSiE, an extension of Sum of Single Effects (SuSiE), to multiple ancestries that allows causal effect sizes to vary across ancestries. We evaluated MultiSuSiE using whole-genome sequencing data from 47,000 African-ancestry, 36,000 Latino-ancestry and 116,000 European-ancestry individuals from All of Us. In simulations, MultiSuSiE applied to Afr36k + Lat36k + Eur36k was well-calibrated and attained higher power than SuSiE applied to Eur109k; compared to recent multi-ancestry methods (SuSiEx and MESuSiE), MultiSuSiE attained higher power and lower computational cost. In analyses of 14 quantitative traits, MultiSuSiE applied to Afr47k + Lat36k + Eur116k identified 348 fine-mapped variants with posterior inclusion probability (PIP) > 0.9, and MultiSuSiE applied to Afr36k + Lat36k + Eur36k identified 59% more PIP > 0.9 variants than SuSiE applied to Eur109k; MultiSuSiE identified 29% more PIP > 0.9 variants than SuSiEx, and MESuSiE was not included due to its high computational cost. We validated these findings through functional enrichment of fine-mapped variants and highlighted examples implicating biologically plausible fine-mapped variants.
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