Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data

Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data

November 2012 | Volume 8 | Issue 11 | e1002967 | Joseph K. Pickrell, Jonathan K. Pritchard
The paper presents a statistical model, TreeMix, for inferring population splits and mixtures from genome-wide allele frequency data. The model represents the relationships between populations as a graph, allowing for both population splits and gene flow. The authors apply TreeMix to 55 human populations and 82 dog breeds, identifying previously known and new migration events. In humans, they find that Cambodians trace about 16% of their ancestry to a population ancestral to other East Asians. In dogs, they infer that the boxer and basenji breeds have significant ancestry from wolves subsequent to domestication, and that East Asian toy breeds result from admixture between modern toy breeds and ancient Asian breeds. The model is validated through simulations and shown to be accurate in inferring population histories.The paper presents a statistical model, TreeMix, for inferring population splits and mixtures from genome-wide allele frequency data. The model represents the relationships between populations as a graph, allowing for both population splits and gene flow. The authors apply TreeMix to 55 human populations and 82 dog breeds, identifying previously known and new migration events. In humans, they find that Cambodians trace about 16% of their ancestry to a population ancestral to other East Asians. In dogs, they infer that the boxer and basenji breeds have significant ancestry from wolves subsequent to domestication, and that East Asian toy breeds result from admixture between modern toy breeds and ancient Asian breeds. The model is validated through simulations and shown to be accurate in inferring population histories.
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