Protocol for constructing multi-ancestry polygenic models using S4-Multi.

Ping-Hung Lai, Jonathan P Tyrer, John Baierl, Paul D P Pharoah, Pei-Chen Peng

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Article in STAR protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Ping-Hung LaiDepartment of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, CA 90069, USA.

Jonathan P TyrerDepartment of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK.

John BaierlDepartment of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, CA 90069, USA.

Paul D P PharoahDepartment of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, CA 90069, USA.

Pei-Chen PengDepartment of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, CA 90069, USA. Electronic address: pei-chen.peng@csmc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Here, we present a protocol to construct multi-ancestry polygenic models using S4-Multi and generate polygenic risk scores. We describe steps for preparing reference genotype files, formatting genome-wide association stud (GWAS) summary statistics, and selecting SNPs using S4_select. We then perform Bayesian shrinkage with S4_shrink and describe procedures for polygenic score generation and performance evaluation. This workflow supports single- and multi-ancestry analyses and uses linkage disequilibrium information to improve prediction accuracy. For complete details on the use and execution of this protocol, please refer to Baierl et al.

Indexed as

BioinformaticsComputer sciencesGenetics

Identifiers

PMID42397746

DOI10.1016/j.xpro.2026.104681

PMCPMC13355460

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.