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

Bioinformatics
Jeremy M Brown, Robert ElDabaje

Abstract

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. 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.

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Citations

Aug 30, 2013·Systematic Biology·Noah M ReidBryan C Carstens
Nov 7, 2013·Systematic Biology·Paul O LewisLynn Kuo
Jun 22, 2014·Systematic Biology·Sebastian HöhnaJohn P Huelsenbeck
Jul 15, 2015·Molecular Biology and Evolution·David A DuchêneSimon Y W Ho
Jan 1, 2010·IEEE Reviews in Biomedical Engineering·Roger C BarrAndrew E Pollard
Jun 24, 2015·Systematic Biology·Vinson P DoyleJeremy M Brown
Feb 26, 2016·Molecular Ecology·Anthony J Barley, Robert C Thomson
Jul 7, 2015·PLoS Computational Biology·Bethany L Dearlove, Simon D W Frost
Nov 15, 2017·Molecular Biology and Evolution·Sebastian HöhnaJeremy M Brown
Sep 20, 2019·Genome Biology and Evolution·Suha Naser-KhdourRobert Lanfear
Feb 11, 2019·Molecular Phylogenetics and Evolution·Marek L BorowiecPhilip S Ward

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