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Bioinformatics Advance Access published online on September 8, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn478
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

ADZE: A rarefaction approach for counting alleles private to combinations of populations

Zachary A. Szpiech 1,*, Mattias Jakobsson 1,2,3 and Noah A. Rosenberg 1,2,4

1Center for Computational Medicine and Biology, University of Michigan, Ann Arbor, Michigan 48109 USA
2Department of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109 USA
3Department of Evolution, Genomics and Systematics, Uppsala University, SE-752 36 Uppsala, Sweden
4Life Sciences Institute, University of Michigan, Ann Arbor, Michigan 48109 USA

*To whom correspondence should be addressed. Zachary A. Szpiech, E-mail: szpiechz{at}umich.edu


  Abstract

Motivation: Analysis of the distribution of alleles across populations is a useful tool for examining population diversity and relationships. However, sample sizes often differ across populations, sometimes making it difficult to assess allelic distributions across groups.

Results: We introduce a generalized rarefaction approach for counting alleles private to combinations of populations. Our method evaluates the number of alleles found in each of a set of populations but absent in all remaining populations, considering equal-sized subsamples from each population. Applying this method to a worldwide human microsatellite dataset, we observe a high number of alleles private to the combination of African and Oceanian populations. This result supports the possibility of a migration out of Africa into Oceania separate from the migrations responsible for the majority of the ancestry of the modern populations of Asia, and it highlights the utility of our approach to sample size correction in evaluating hypotheses about population history.

Availability: We have implemented our method in the computer program ADZE, which is available for download at http://rosenberglab.bioinformatics.med.umich.edu/adze.html.

Associate Editor: Prof. Martin Bishop

Received on May 1, 2008; revised on September 4, 2008; accepted on September 5, 2008

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