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Bioinformatics Advance Access published online on November 16, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl474
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received July 3, 2006
Accepted September 2, 2006

Applications note

GARD: a genetic algorithm for recombination detection

Sergei L. Kosakovsky Pond 1 *, David Posada 2, Michael B. Gravenor 3, Christopher H. Woelk 1, and Simon D. W. Frost 1

1 Department of Pathology, University of California San Diego, La Jolla, California, 92093, USA
2 Departamento de Bioquímica, Genética e Inmunología, Facultad de Biología, Universidad de Vigo, Vigo 36310, Spain
3 School of Medicine, University of Wales, Swansea, United Kingdom

* To whom correspondence should be addressed.
Sergei L. Kosakovsky Pond, E-mail: spond{at}ucsd.edu


  Abstract

Motivation: Phylogenetic and evolutionary inference can be severely misled if recombination is not accounted for, hence screening for it should be an essential component of nearly every comparative study. The evolution of recombinant sequences can not be properly explained by a single phylogenetic tree, but several phylogenies may be used to correctly model the evolution of non-recombinant fragments.

Results: We developed a likelihood-based model selection procedure that uses a genetic algorithm to search multiple sequence alignments for evidence of recombination breakpoints and identify putative recombinant sequences. GARD is an extensible and intuitive method that can be run efficiently in parallel. Extensive simulation studies show that the method nearly always outperforms other available tools, both in terms of power and accuracy and that the use of GARD to screen sequences for recombination ensures good statistical properties for methods aimed at detecting positive selection.

Availability: Freely available. http://www.datamonkey.org/GARD/.

Associate Editor: Christos Ouzounis
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