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Comparing three different methods to detect selective loci using dominant markers.

Abstract

We carried out a simulation study to compare the efficiency of three alternative programs (DFDIST, DETSELD and BAYESCAN) to detect loci under directional selection from genome-wide scans using dominant markers. We also evaluated the efficiency of correcting for multiple testing those methods that use a classical probability approach. Under a wide range of scenarios, we conclude that BAYESCAN appears to be more efficient than the other methods, detecting a usually high percentage of true selective loci as well as less than 1% of outliers (false positives) under a fully neutral model. In addition, the percentage of outliers detected by this software is always correlated with the true percentage of selective loci in the genome. Our results show, nevertheless, that false positives are common even with a combination of methods and multitest correction, suggesting that conclusions obtained from this approach should be taken with extreme caution.

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  • Publisher Full Text
  • Authors

    , , , ,

    Source

    Journal of evolutionary biology 23:10 2010 Oct pg 2267-76

    MeSH

    Computer Simulation
    Genes, Dominant
    Genetic Loci
    Genome
    Genomics
    Selection, Genetic
    Software

    Pub Type(s)

    Comparative Study
    Journal Article
    Research Support, Non-U.S. Gov't

    Language

    eng

    PubMed ID

    20796133

    Citation

    TY - JOUR T1 - Comparing three different methods to detect selective loci using dominant markers. AU - Pérez-Figueroa,A, AU - García-Pereira,M J, AU - Saura,M, AU - Rolán-Alvarez,E, AU - Caballero,A, PY - 2010/8/28/entrez PY - 2010/8/28/pubmed PY - 2010/12/29/medline SP - 2267 EP - 76 JF - Journal of evolutionary biology JO - J. Evol. Biol. VL - 23 IS - 10 N2 - We carried out a simulation study to compare the efficiency of three alternative programs (DFDIST, DETSELD and BAYESCAN) to detect loci under directional selection from genome-wide scans using dominant markers. We also evaluated the efficiency of correcting for multiple testing those methods that use a classical probability approach. Under a wide range of scenarios, we conclude that BAYESCAN appears to be more efficient than the other methods, detecting a usually high percentage of true selective loci as well as less than 1% of outliers (false positives) under a fully neutral model. In addition, the percentage of outliers detected by this software is always correlated with the true percentage of selective loci in the genome. Our results show, nevertheless, that false positives are common even with a combination of methods and multitest correction, suggesting that conclusions obtained from this approach should be taken with extreme caution. SN - 1420-9101 UR - https://www.unboundmedicine.com/medline/citation/20796133/Comparing_three_different_methods_to_detect_selective_loci_using_dominant_markers_ L2 - http://onlinelibrary.wiley.com/resolve/openurl?genre=article&sid=nlm:pubmed&issn=1010-061X&date=2010&volume=23&issue=10&spage=2267 ER -