Evidence map›Paper›PMID 41102819›Full record

ArticleGenome biology2025

SPAmix: a scalable, accurate, and universal analysis framework for large-scale genetic association studies in admixed populations.

Yuzhuo Ma, He Xu, Ying Li, Hyesung Kim, Lin-Lin Xu, Lin Miao, Peng Xu, Fengbiao Mao, Xu-Jie Zhou, Wei Zhou and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Yuzhuo MaDepartment of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing, China.
He XuDepartment of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing, China.
Ying LiDepartment of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing, China.
Hyesung KimGraduate School of Data Science, Seoul National University, Seoul, Korea.
Lin-Lin XuRenal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China.
Lin MiaoDepartment of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing, China.
Peng XuState Key Laboratory of Radiation Medicine and Protection, Cyrus Tang Medical Institute, National Clinical Research Center for Hematologic Diseases, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China.
Fengbiao MaoInstitute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China.
Xu-Jie ZhouRenal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China.
Wei ZhouCenter for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Seunggeun LeeGraduate School of Data Science, Seoul National University, Seoul, Korea.
Ji-Feng ZhangSchool of Automation and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, China. jif@iss.ac.cn.
Peipei ZhangDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China. peipei.zhang@pku.edu.cn.
Wenjian BiDepartment of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing, China. wenjianb@pku.edu.cn.ORCID http://orcid.org/0000-0002-5108-9311

Funding

Clinical Medicine Plus X - Young Scholars Project PKU2023LCXQ043Innovation Fund for Outstanding Doctoral Candidates of Peking University Health Science Center BMU2025BSS001National Natural Science Foundation of China 32471202National Natural Science Foundation of China 62273010National Natural Science Foundation of China 62411540239National Natural Science Foundation of China 82441004National Research Foundation of Korea 2024K2A9A2A0601368311
6 · The paper itself

Abstract

backgroundInclusion of individuals with diverse or admixed genetic ancestries is crucial to discover novel findings that may be missed by genomics analyses rooted solely in European population.

resultsHere, we present an analysis framework, SPAmix, which is scalable to a large-scale biobank data analysis including hundreds of thousands of admixed individuals and is universally applicable to various types of complex traits including quantitative traits, time-to-event traits, ordinal traits, and longitudinal traits. Since no alternative model is fitted, SPAmix primarily focuses on association p values. For each genetic variant, SPAmix uses genotype data and genetic principal components to estimate individual-specific allele frequency, which is subsequently used to calibrate p values via a retrospective analysis. A hybrid strategy including saddlepoint approximation (SPA) can greatly increase the accuracy to analyze rare genetic variants, especially if the phenotypic distribution is unbalanced or extremely unbalanced. We also propose SPAmix

conclusionsThe SPAmix-based approaches are more accurate than Tractor to address phenotypic variance heterogeneity among ancestries when analyzing quantitative traits and to address an unbalanced case-control ratio when analyzing binary traits. SPAmix

Indexed as

Genetic Association StudiesGenetics, PopulationGenome-Wide Association StudySoftwareBiological Specimen BanksGene FrequencyHumansModels, GeneticPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID41102819
PMCPMC12533355

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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.