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《Detecting the number of clusters of individuals using the software structure: a simulation study》

Abstract:The identification of genetically homogeneous groups of individuals is a long standingissue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE  allows the identification of such groups. However, the ability of this algorithm todetect the true number of clusters ( K ) in a sample of individuals when patterns of dispersalamong populations are not homogeneous has not been tested. The goal of this study is tocarry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated ‘log probability of data’ does notprovide a correct estimation of the number of clusters,  K . However, using an ad hoc statistic∆∆∆∆ K  based on the rate of change in the log probability of data between successive  K  values,we found that  STRUCTURE  accurately detects the uppermost hierarchical level of structure forthe scenarios we tested. As might be expected, the results are sensitive to the type of geneticmarker used (AFLP vs. microsatellite), the number of loci scored, the number of popula-tions sampled, and the number of individuals typed in each sample

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  • 附件 1 : EVANNO_et_al-2005-Molecular_Ecology.pdf
  • 2016-09-23 15:02:39, 260.04 K

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