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Science 21 April 2006:
Vol. 312. no. 5772, p. 367
DOI: 10.1126/science.1123622
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Technical Comments

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

Fredrik Ronquist,1* Bret Larget,2 John P. Huelsenbeck,3 Joseph B. Kadane,4 Donald Simon,5 Paul van der Mark1

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.

1 School of Computational Science, Florida State University, Tallahassee, FL 32306–4120, USA.
2 Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.
3 Division of Biological Sciences, University of California at San Diego, San Diego, CA 92093–0116, USA.
4 Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
5 Department of Mathematics and Computer Science, Duquesne University, Pittsburgh, PA 15282, USA.

* To whom correspondence should be addressed. E-mail: ronquist{at}scs.fsu.edu

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THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Efficiency of Markov Chain Monte Carlo Tree Proposals in Bayesian Phylogenetics.
C. Lakner, P. van der Mark, J. P. Huelsenbeck, B. Larget, and F. Ronquist (2008)
Syst Biol 57, 86-103
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