title: RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language.
abstract: 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.].
authors.affiliation: 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; Sebastian.Hoehna@gmail.com.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Höhna
authors.affiliation: Department of Integrative Biology;
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Landis
authors.affiliation: Department of Integrative Biology; Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA; Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA 50011, USA; Sebastian.Hoehna@gmail.com.
authors.forename: Tracy A
authors.initials: TA
authors.lastname: Heath
authors.affiliation: Department of Integrative Biology; Laboratoire de Biométrie et Biologie Evolutive, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 5558, Université Lyon 1, F-69622 Villeurbanne, France; and Sebastian.Hoehna@gmail.com.
authors.forename: Bastien
authors.initials: B
authors.lastname: Boussau
authors.affiliation: Laboratoire de Biométrie et Biologie Evolutive, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 5558, Université Lyon 1, F-69622 Villeurbanne, France; and Sebastian.Hoehna@gmail.com.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Lartillot
authors.affiliation: Department of Evolution and Ecology, University of California, Davis, CA 95616, USA; Sebastian.Hoehna@gmail.com.
authors.forename: Brian R
authors.initials: BR
authors.lastname: Moore
authors.affiliation: Department of Integrative Biology; Sebastian.Hoehna@gmail.com.
authors.forename: John P
authors.initials: JP
authors.lastname: Huelsenbeck
authors.affiliation: Department of Bioinformatics and Genetics, Swedish Museum of Natural History, SE-10405 Stockholm, Sweden Sebastian.Hoehna@gmail.com.
authors.forename: Fredrik
authors.initials: F
authors.lastname: Ronquist
mesh_terms: D001499:Bayes Theorem; D002965:Classification / Q000379:methods*; D008954:Models, Biological; D010802:Phylogeny; D012984:Software