Journal Article

A novel parallel approach to the likelihood-based estimation of admixture in population genetics

Ambra Giovannini, Gaetano Zanghirati, Mark A. Beaumont, Lounès Chikhi and Guido Barbujani

in Bioinformatics

Volume 25, issue 11, pages 1440-1441
Published in print June 2009 | ISSN: 1367-4803
Published online March 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp136
A novel parallel approach to the likelihood-based estimation of admixture in population genetics

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Summary: Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C++ implementation are reported.

Availability: The software package parLEA is freely available at http://dm.unife.it/parlea.

Contact: ambra.giovannini@unife.it

Supplementary information: Additional information, including instructions for installation/use the original sequential LEA code and the data used in this paper, are also available in the web site.

Journal Article.  1242 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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