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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Univ Los Andes, Lab Genet Humana, Bogota, ColombiaPontificia Univ Javeriana, Fac Ciencias, Bogota, Colombia
Claudia Lattig, Maria
Groot, Helena
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Univ Los Andes, Lab Genet Humana, Bogota, ColombiaPontificia Univ Javeriana, Fac Ciencias, Bogota, Colombia
Groot, Helena
de Carvalho, Elizeu Fagundes
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State Univ Rio de Janeiro UERJ, DNA Diagnost Lab, Rio De Janeiro, BrazilPontificia Univ Javeriana, Fac Ciencias, Bogota, Colombia
de Carvalho, Elizeu Fagundes
Gusmao, Leonor
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State Univ Rio de Janeiro UERJ, DNA Diagnost Lab, Rio De Janeiro, Brazil
Univ Porto, IPATIMUP Inst Patol Imunol Mol, Oporto, PortugalPontificia Univ Javeriana, Fac Ciencias, Bogota, Colombia