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Admix-kit: an integrated toolkit and pipeline for genetic analyses of admixed populations.
Hou, Kangcheng; Gogarten, Stephanie; Kim, Joohyun; Hua, Xing; Dias, Julie-Alexia; Sun, Quan; Wang, Ying; Tan, Taotao; Atkinson, Elizabeth G; Martin, Alicia; Shortt, Jonathan; Hirbo, Jibril; Li, Yun; Pasaniuc, Bogdan; Zhang, Haoyu.
Affiliation
  • Hou K; Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, United States.
  • Gogarten S; Department of Biostatistics, University of Washington, Seattle, WA, 98195, United States.
  • Kim J; Vanderbilt Genetics Institute and Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, United States.
  • Hua X; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, United States.
  • Dias JA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02120, United States.
  • Sun Q; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States.
  • Wang Y; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, United States.
  • Tan T; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, United States.
  • Atkinson EG; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, United States.
  • Martin A; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, United States.
  • Shortt J; Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States.
  • Hirbo J; Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, United States.
  • Li Y; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States.
  • Pasaniuc B; Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, United States.
  • Zhang H; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, United States.
Bioinformatics ; 40(4)2024 Mar 29.
Article in En | MEDLINE | ID: mdl-38490256
ABSTRACT

SUMMARY:

Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic studies of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations. AVAILABILITY AND IMPLEMENTATION Admix-kit package is open-source and available at https//github.com/KangchengHou/admix-kit. Additionally, users can use the pipeline designed for admixed genotype simulation available at https//github.com/UW-GAC/admix-kit_workflow.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2024 Document type: Article Affiliation country:
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2024 Document type: Article Affiliation country: