Evaluating the performance of likelihood methods for detecting population structure and migration

Authors

  • ZAID Abdo,

    1. Department of Mathematics, PO Box 441103, University of Idaho, Moscow, ID 83844–1104 USA,
    2. Initiative in Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, USA,
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  • Keith A. Crandall,

    1. Department of Integrative Biology, Brigham Young University, Provo, UT 84602, USA
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  • PAUL Joyce

    Corresponding author
    1. Department of Mathematics, PO Box 441103, University of Idaho, Moscow, ID 83844–1104 USA,
    2. Initiative in Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, USA,
      Paul Joyce. Fax: 208-885-6338; E-mail: joyce@uidaho.edu
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Paul Joyce. Fax: 208-885-6338; E-mail: joyce@uidaho.edu

Abstract

A plethora of statistical models have recently been developed to estimate components of population genetic history. Very few of these methods, however, have been adequately evaluated for their performance in accurately estimating population genetic parameters of interest. In this paper, we continue a research program of evaluation of population genetic methods through computer simulation. Specifically, we examine the software migratee-n 1.6.8 and test the accuracy of this software to estimate genetic diversity (Θ), migration rates, and confidence intervals. We simulated nucleotide sequence data under a neutral coalescent model with lengths of 500 bp and 1000 bp, and with three different per site Θ values of (0.00025, 0.0025, 0.025) crossed with four different migration rates (0.0000025, 0.025, 0.25, 2.5) to construct 1000 evolutionary trees per-combination per-sequence-length. We found that while migratee-n 1.6.8 performs reasonably well in estimating genetic diversity (Θ), it does poorly at estimating migration rates and the confidence intervals associated with them. We recommend researchers use this software with caution under conditions similar to those used in this evaluation.

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