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GARD: a genetic algorithm for recombination detection.

Sergei L Kosakovsky Pond1, David Posada, Michael B Gravenor

  • 1Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA. spond@ucsd.edu

Bioinformatics (Oxford, England)
|November 18, 2006
PubMed
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Detecting recombination is crucial for accurate evolutionary studies. Our new GARD method efficiently identifies recombinant sequences, improving phylogenetic analysis and positive selection detection.

Area of Science:

  • Evolutionary Biology
  • Bioinformatics
  • Genetics

Background:

  • Recombination significantly impacts phylogenetic and evolutionary inference.
  • Accurate evolutionary modeling requires accounting for recombination events.
  • Standard phylogenetic trees may not adequately represent recombinant sequence evolution.

Purpose of the Study:

  • To develop a robust method for detecting recombination breakpoints and identifying recombinant sequences.
  • To improve the accuracy of evolutionary inference by screening for recombination.
  • To enhance the statistical properties of positive selection detection methods.

Main Methods:

  • Developed a likelihood-based model selection procedure.
  • Utilized a genetic algorithm to search sequence alignments for recombination evidence.

Related Experiment Videos

  • Implemented an extensible and intuitive method (GARD) for efficient parallel processing.

    • Main Results:

    • GARD effectively identifies recombination breakpoints and putative recombinant sequences.
    • Extensive simulations demonstrate GARD's superior power and accuracy compared to existing tools.
    • Screening sequences with GARD ensures reliable statistical properties for downstream analyses.

    Conclusions:

    • GARD is a highly effective tool for detecting recombination in sequence data.
    • The method significantly improves the reliability of phylogenetic and evolutionary analyses.
    • GARD facilitates more accurate detection of positive selection by pre-screening for recombination.