Pcadmix: Principal components-based assignment of ancestry along each chromosome in individuals with admixed ancestry from two or more populations

Abra Brisbin, Katarzyna Bryc, Jake Byrnes, Fouad Zakharia, Larsson Omberg, Jeremiah Degenhardt, Andrew Reynolds, Harry Ostrer, Jason G. Mezey, Carlos D. Bustamante

Research output: Contribution to journalArticlepeer-review

126 Scopus citations

Abstract

Identifying ancestry along each chromosome in admixed individuals provides a wealth of information for understanding the population genetic history of admixture events and is valuable for admixture mapping and identifying recent targets of selection. We present PCAdmix (available at https://sites.google.com/site/pcadmix/home), a Principal Components based algorithm for determining ancestry along each chromosome from a high-density, genome-wide set of phased single-nucleotide polymorphism (SNP) genotypes of admixed individuals. We compare our method to HAPMIX on simulated data from two ancestral populations, and we find high concordance between the methods. Our method also has better accuracy than LAMP when applied to three-population admixture, a situation as yet unaddressed by HAPMIX. Finally, we apply our method to a data set of four Latino populations with European, African, and Native American ancestry. We find evidence of assortative mating in each of the four populations, and we identify regions of shared ancestry that may be recent targets of selection and could serve as candidate regions for admixture-based association mapping.

Original languageEnglish (US)
Pages (from-to)343-364
Number of pages22
JournalHuman Biology
Volume84
Issue number4
DOIs
StatePublished - Aug 2012

Keywords

  • Admixture
  • Forward-backward algorithm
  • Haplotype-based
  • Local ancestry deconvolution
  • Principal components analysis (PCA)

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Genetics(clinical)

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