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Bayesian methods outperform parsimony but at the expense of precision in the estimation of phylogeny from discrete morphological data

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Original languageEnglish
Article number20160081
Number of pages5
JournalBiology Letters
Volume12
Issue number4
Early online date19 Apr 2016
DOIs
DateAccepted/In press - 18 Mar 2016
DateE-pub ahead of print - 19 Apr 2016
DatePublished (current) - Apr 2016

Abstract

Different analytical methods can yield competing interpretations of evolutionary history and, currently, there is no definitive method for phylogenetic reconstruction using morphological data. Parsimony has been the primary method for analysing morphological data, but there has been a resurgence of interest in the likelihood-based Mk-model. Here we test the performance of the Bayesian implementation of the Mk-model relative to both equal and implied-weight implementations of parsimony. Using simulated morphological data, we demonstrate that the Mk-model outperforms equal-weights parsimony in terms of topological accuracy, and implied-weights performs the most poorly. However, the Mk-model produces phylogenies that have less resolution than parsimony methods. This difference in the accuracy and precision of parsimony and likelihood approaches to topology estimation needs to be considered when selecting a method for phylogeny reconstruction.

    Research areas

  • Bayesian, Likelihood, Morphology, Parsimony, Phylogenetics

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    Rights statement: This is the final published version of the article (version of record). It first appeared online via the Royal Society at http://rsbl.royalsocietypublishing.org/content/12/4/20160081. Please refer to any applicable terms of use of the publisher.

    Final published version, 529 KB, PDF-document

    Licence: CC BY

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