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Science
Vol. 312 no. 5772 p. 367
DOI: 10.1126/science.1123622
  • Technical Comments

Comment on "Phylogenetic MCMC Algorithms Are Misleading on Mixtures of Trees"

  1. Paul van der Mark1

+ Author Affiliations

  1. 1 School of Computational Science, Florida State University, Tallahassee, FL 32306–4120, USA.
  2. 2 Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.
  3. 3 Division of Biological Sciences, University of California at San Diego, San Diego, CA 92093–0116, USA.
  4. 4 Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
  5. 5 Department of Mathematics and Computer Science, Duquesne University, Pittsburgh, PA 15282, USA.
  1. ↵* To whom correspondence should be addressed. E-mail: ronquist@scs.fsu.edu

Mossel and Vigoda (Reports, 30 September 2005, p. 2207) show that nearest neighbor interchange transitions, commonly used in phylogenetic Markov chain Monte Carlo (MCMC) algorithms, perform poorly on mixtures of dissimilar trees. However, the conditions leading to their results are artificial. Standard MCMC convergence diagnostics would detect the problem in real data, and correction of the model misspecification would solve it.

  • Received for publication 8 December 2005.
  • Accepted for publication 15 March 2006.
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THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:

  • An Evaluation of Phylogenetic Informativeness Profiles and the Molecular Phylogeny of Diplazontinae (Hymenoptera, Ichneumonidae) Syst Biol 1 March 2010: 226-241.
  • Efficiency of Markov Chain Monte Carlo Tree Proposals in Bayesian Phylogenetics Syst Biol 1 February 2008: 86-103.

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