A Model-Based Method for Identifying Species Hybrids Using Multilocus Genetic Data

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ID: 292203
2002
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Abstract
Abstract We present a statistical method for identifying species hybrids using data on multiple, unlinked markers. The method does not require that allele frequencies be known in the parental species nor that separate, pure samples of the parental species be available. The method is suitable for both markers with fixed allelic differences between the species and markers without fixed differences. The probability model used is one in which parentals and various classes of hybrids (F1's, F2's, and various backcrosses) form a mixture from which the sample is drawn. Using the framework of Bayesian model-based clustering allows us to compute, by Markov chain Monte Carlo, the posterior probability that each individual belongs to each of the distinct hybrid classes. We demonstrate the method on allozyme data from two species of hybridizing trout, as well as on two simulated data sets.
Reference Key
openalex_W2139718698 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Eric C. Anderson, E. A. Thompson
Journal current genetics
Year 2002
DOI
10.1093/genetics/160.3.1217
URL
https://doi.org/10.1093/genetics/160.3.1217
Keywords Keywords not found

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