Publication Date
8-10-2023
Journal
Annual Review of Biomedical Data Science
DOI
10.1146/annurev-biodatasci-020722-014310
PMID
37127050
PMCID
PMC10871708
PubMedCentral® Posted Date
2-16-2024
PubMedCentral® Full Text Version
Author MSS
Published Open-Access
yes
Keywords
Humans, Genetics, Population, Genomics, Software, Genome, Human, admixture, statistical genetics, complex traits, genomics, methods, ancestry
Abstract
Admixed populations constitute a large portion of global human genetic diversity, yet they are often left out of genomics analyses. This exclusion is problematic, as it leads to disparities in the understanding of the genetic structure and history of diverse cohorts and the performance of genomic medicine across populations. Admixed populations have particular statistical challenges, as they inherit genomic segments from multiple source populations-the primary reason they have historically been excluded from genetic studies. In recent years, however, an increasing number of statistical methods and software tools have been developed to account for and leverage admixture in the context of genomics analyses. Here, we provide a survey of such computational strategies for the informed consideration of admixture to allow for the well-calibrated inclusion of mixed ancestry populations in large-scale genomics studies, and we detail persisting gaps in existing tools.
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Biological Phenomena, Cell Phenomena, and Immunity Commons, Biomedical Informatics Commons, Genetics and Genomics Commons, Medical Genetics Commons, Medical Molecular Biology Commons, Medical Specialties Commons