In:
PLOS Genetics, Public Library of Science (PLoS), Vol. 19, No. 2 ( 2023-2-13), p. e1010410-
Abstract:
Admixture graphs are mathematical structures that describe the ancestry of populations in terms of divergence and merging (admixing) of ancestral populations as a graph. An admixture graph consists of a graph topology, branch lengths, and admixture proportions. The branch lengths and admixture proportions can be estimated using numerous numerical optimization methods, but inferring the topology involves a combinatorial search for which no polynomial algorithm is known. In this paper, we present a reversible jump MCMC algorithm for sampling high-probability admixture graphs and show that this approach works well both as a heuristic search for a single best-fitting graph and for summarizing shared features extracted from posterior samples of graphs. We apply the method to 11 Native American and Siberian populations and exploit the shared structure of high-probability graphs to characterize the relationship between Saqqaq, Inuit, Koryaks, and Athabascans. Our analyses show that the Saqqaq is not a good proxy for the previously identified gene flow from Arctic people into the Na-Dene speaking Athabascans.
Type of Medium:
Online Resource
ISSN:
1553-7404
DOI:
10.1371/journal.pgen.1010410
DOI:
10.1371/journal.pgen.1010410.g001
DOI:
10.1371/journal.pgen.1010410.g002
DOI:
10.1371/journal.pgen.1010410.g003
DOI:
10.1371/journal.pgen.1010410.g004
DOI:
10.1371/journal.pgen.1010410.g005
DOI:
10.1371/journal.pgen.1010410.s001
DOI:
10.1371/journal.pgen.1010410.s002
DOI:
10.1371/journal.pgen.1010410.s003
DOI:
10.1371/journal.pgen.1010410.s004
DOI:
10.1371/journal.pgen.1010410.s005
DOI:
10.1371/journal.pgen.1010410.s006
DOI:
10.1371/journal.pgen.1010410.s007
DOI:
10.1371/journal.pgen.1010410.s008
DOI:
10.1371/journal.pgen.1010410.s009
DOI:
10.1371/journal.pgen.1010410.s010
DOI:
10.1371/journal.pgen.1010410.s011
DOI:
10.1371/journal.pgen.1010410.s012
DOI:
10.1371/journal.pgen.1010410.s013
DOI:
10.1371/journal.pgen.1010410.s014
DOI:
10.1371/journal.pgen.1010410.s015
DOI:
10.1371/journal.pgen.1010410.s016
DOI:
10.1371/journal.pgen.1010410.s017
DOI:
10.1371/journal.pgen.1010410.s018
DOI:
10.1371/journal.pgen.1010410.s019
DOI:
10.1371/journal.pgen.1010410.r001
DOI:
10.1371/journal.pgen.1010410.r002
DOI:
10.1371/journal.pgen.1010410.r003
DOI:
10.1371/journal.pgen.1010410.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2023
detail.hit.zdb_id:
2186725-2
