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Bioinformatics Advance Access originally published online on December 19, 2008
Bioinformatics 2009 25(4):537-538; doi:10.1093/bioinformatics/btn651
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

PuMA: Bayesian analysis of partitioned (and unpartitioned) model adequacy

Jeremy M. Brown 1,2,* and Robert ElDabaje 1

1Section of Integrative Biology and 2Center for Computational Biology and Bioinformatics, University of Texas – Austin, Austin, TX 78712, USA

*To whom correspondence should be addressed.


  Abstract

Summary: The accuracy of Bayesian phylogenetic inference using molecular data depends on the use of proper models of sequence evolution. Although choosing the best model available from a pool of alternatives has become standard practice in statistical phylogenetics, assessment of the chosen model's adequacy is rare. Programs for Bayesian phylogenetic inference have recently begun to implement models of sequence evolution that account for heterogeneity across sites beyond variation in rates of evolution, yet no program exists to assess the adequacy of these models. PuMA implements a posterior predictive simulation approach to assessing the adequacy of partitioned, unpartitioned and mixture models of DNA sequence evolution in a Bayesian context. Assessment of model adequacy allows empirical phylogeneticists to have appropriate confidence in their results and guides efforts to improve models of sequence evolution.

Availability: This program is available as source code, a Java.jar application, and a native Mac OS X application. It is distributed under the terms of the GNU General Public License at http://code.google.com/p/phylo-puma.

Contact: jembrown{at}mail.utexas.edu

Associate Editor: Martin Bishop

Received on August 14, 2008; revised on December 17, 2008; accepted on December 17, 2008

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