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      Bayesian identification of admixture events using multilocus molecular markers.

      1 ,

      Molecular ecology

      Wiley-Blackwell

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          Abstract

          Bayesian statistical methods for the estimation of hidden genetic structure of populations have gained considerable popularity in the recent years. Utilizing molecular marker data, Bayesian mixture models attempt to identify a hidden population structure by clustering individuals into genetically divergent groups, whereas admixture models target at separating the ancestral sources of the alleles observed in different individuals. We discuss the difficulties involved in the simultaneous estimation of the number of ancestral populations and the levels of admixture in studied individuals' genomes. To resolve this issue, we introduce a computationally efficient method for the identification of admixture events in the population history. Our approach is illustrated by analyses of several challenging real and simulated data sets. The software (baps), implementing the methods introduced here, is freely available at http://www.rni.helsinki.fi/~jic/bapspage.html.

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          Author and article information

          Journal
          Mol. Ecol.
          Molecular ecology
          Wiley-Blackwell
          0962-1083
          0962-1083
          Sep 2006
          : 15
          : 10
          Affiliations
          [1 ] Department of Mathematics and Statistics, PO Box 68, Fin-00014 University of Helsinki, Finland. jukka.corander@helsinki.fi
          Article
          MEC2994
          10.1111/j.1365-294X.2006.02994.x
          16911204

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