Brown Jeremy M, ElDabaje Robert
Section of Integrative Biology, Center for Computational Biology and Bioinformatics, University of Texas - Austin, Austin, TX 78712, USA.
Bioinformatics. 2009 Feb 15;25(4):537-8. doi: 10.1093/bioinformatics/btn651. Epub 2008 Dec 19.
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.
使用分子数据进行贝叶斯系统发育推断的准确性取决于对序列进化恰当模型的使用。尽管从一系列备选模型中选择最佳可用模型已成为统计系统发育学中的标准做法，但对所选模型充分性的评估却很少见。用于贝叶斯系统发育推断的程序最近开始采用能解释除进化速率变化之外的位点间异质性的序列进化模型，然而尚无程序可评估这些模型的充分性。PuMA在贝叶斯背景下实现了一种后验预测模拟方法，用于评估DNA序列进化的分区、非分区和混合模型的充分性。对模型充分性的评估使经验丰富的系统发育学家能够对其结果有适当的信心，并指导改进序列进化模型的工作。
该程序以源代码、Java.jar应用程序和原生Mac OS X应用程序的形式提供。它根据GNU通用公共许可证的条款在http://code.google.com/p/phylo-puma上分发。
