GARD: a genetic algorithm for recombination detection

• Published in: Bioinformatics Vol. 22; no. 24; pp. 3096 - 3098
• Main Authors: Kosakovsky Pond, Sergei L., Posada, David, Gravenor, Michael B., Woelk, Christopher H., Frost, Simon D.W.
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 15.12.2006; Oxford Publishing Limited (England)
• Subjects: Algorithms; Base Sequence; Biological and medical sciences; Chromosome Mapping - methods; Comparative studies; Computer Simulation; Conserved Sequence - genetics; Evolution, Molecular; Fundamental and applied biological sciences. Psychology; General aspects; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Models, Genetic; Molecular Sequence Data; Recombination, Genetic - genetics; Sequence Alignment - methods; Sequence Analysis, DNA - methods; Sequence Homology, Nucleic Acid; Software; Breakpoint; Recombination; Multiple; Genetic algorithm; Sequence alignment; Evolution; Phylogeny; Detection; Bioinformatics; Algorithm; Scope note; Comparative study
• ISSN: 1367-4803; 1367-4811; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btl474

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 Contact:spond@ucsd.edu