PuMA A tool for Bayesian analysis of partitioned model adequacy
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PuMA Description

PuMA is a Java based application assessing the adequacy of phylogenetic models of sequence evolution in a Bayesian context by using a posterior predictive simulation. The accuracy of Bayesian phylogenetic inference using molecular data has been shown to depend on the use of proper models of sequence evolution. While choosing the best model available from a pool of alternatives has become standard practice in statistical phylogenetics, assessment of the adequacy of the chosen model is rare. Programs for Bayesian phylogenetic inference have recently begun to implement models of sequence evolution that account for heterogeneity in process across sites, 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 the efforts of theoretical phylogeneticists in improving models of sequence evolution.

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