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A general approach for inferring the ancestry of recent ancestors of an admixed individual.
Zhang, Yiming; Zhang, Haotian; Wu, Yufeng.
Afiliación
  • Zhang Y; School of Computing, College of Engineering, University of Connecticut, Storrs, CT 06269.
  • Zhang H; School of Computing, College of Engineering, University of Connecticut, Storrs, CT 06269.
  • Wu Y; School of Computing, College of Engineering, University of Connecticut, Storrs, CT 06269.
Proc Natl Acad Sci U S A ; 121(2): e2316242120, 2024 Jan 09.
Article en En | MEDLINE | ID: mdl-38165936
ABSTRACT
The genome of an individual from an admixed population consists of segments originated from different ancestral populations. Most existing ancestry inference approaches focus on calling these segments for the extant individual. In this paper, we present a general ancestry inference approach for inferring recent ancestors from an extant genome. Given the genome of an individual from a recently admixed population, our method can estimate the proportions of the genomes of the recent ancestors of this individual that originated from some ancestral populations. The key step of our method is the inference of ancestors (called founders) right after the formation of an admixed population. The inferred founders can then be used to infer the ancestry of recent ancestors of an extant individual. Our method is implemented in a computer program called PedMix2. To the best of our knowledge, there is no existing method that can practically infer ancestors beyond grandparents from an extant individual's genome. Results on both simulated and real data show that PedMix2 performs well in ancestry inference.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Abuelos / Genética de Población Límite: Humans Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Abuelos / Genética de Población Límite: Humans Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2024 Tipo del documento: Article