Höhna Sebastian, Landis Michael J, Heath Tracy A, Boussau Bastien, Lartillot Nicolas, Moore Brian R, Huelsenbeck John P, Ronquist Fredrik
Department of Integrative Biology; Department of Statistics, University of California, Berkeley, CA 94720, USA; Department of Evolution and Ecology, University of California, Davis, CA 95616, USA; Department of Mathematics, Stockholm University, Stockholm, SE-106 91 Stockholm, Sweden;
Department of Integrative Biology;
Syst Biol. 2016 Jul;65(4):726-36. doi: 10.1093/sysbio/syw021. Epub 2016 May 28.
Programs for Bayesian inference of phylogeny currently implement a unique and fixed suite of models. Consequently, users of these software packages are simultaneously forced to use a number of programs for a given study, while also lacking the freedom to explore models that have not been implemented by the developers of those programs. We developed a new open-source software package, RevBayes, to address these problems. RevBayes is entirely based on probabilistic graphical models, a powerful generic framework for specifying and analyzing statistical models. Phylogenetic-graphical models can be specified interactively in RevBayes, piece by piece, using a new succinct and intuitive language called Rev. Rev is similar to the R language and the BUGS model-specification language, and should be easy to learn for most users. The strength of RevBayes is the simplicity with which one can design, specify, and implement new and complex models. Fortunately, this tremendous flexibility does not come at the cost of slower computation; as we demonstrate, RevBayes outperforms competing software for several standard analyses. Compared with other programs, RevBayes has fewer black-box elements. Users need to explicitly specify each part of the model and analysis. Although this explicitness may initially be unfamiliar, we are convinced that this transparency will improve understanding of phylogenetic models in our field. Moreover, it will motivate the search for improvements to existing methods by brazenly exposing the model choices that we make to critical scrutiny. RevBayes is freely available at http://www.RevBayes.com [Bayesian inference; Graphical models; MCMC; statistical phylogenetics.].
目前用于系统发育贝叶斯推断的程序实现了一套独特且固定的模型。因此，这些软件包的用户在进行特定研究时，不得不同时使用多个程序，而且还没有自由去探索那些程序开发者未实现的模型。我们开发了一个新的开源软件包RevBayes来解决这些问题。RevBayes完全基于概率图模型，这是一个用于指定和分析统计模型的强大通用框架。在RevBayes中，可以使用一种名为Rev的简洁直观的新语言，逐块交互式地指定系统发育图模型。Rev类似于R语言和BUGS模型指定语言，大多数用户应该很容易学习。RevBayes的优势在于能够以简单的方式设计、指定和实现新的复杂模型。幸运的是，这种极大的灵活性并没有以计算速度变慢为代价；正如我们所展示的，在一些标准分析中，RevBayes优于其他竞争软件。与其他程序相比，RevBayes的黑箱元素更少。用户需要明确指定模型和分析的每个部分。虽然这种明确性最初可能不熟悉，但我们相信这种透明度将增进我们领域对系统发育模型的理解。此外，通过公然将我们所做的模型选择置于严格审查之下，它将促使人们寻求对现有方法的改进。可在http://www.RevBayes.com免费获取RevBayes[贝叶斯推断；图模型；MCMC；统计系统发育学。]
