Campus Units
Ecology, Evolution and Organismal Biology
Document Type
Article
Publication Version
Published Version
Publication Date
7-2016
Journal or Book Title
Systematic Biology
Volume
65
Issue
4
First Page
726
Last Page
736
DOI
10.1093/sysbio/syw021
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.
Rights
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright Owner
The authors
Copyright Date
2016
Language
en
File Format
application/pdf
Recommended Citation
Höhna, Sebastian; Landis, Michael J.; Heath, Tracy A.; Lartillot, Nicolas; Moore, Brian R.; Huelsenbeck, John P.; and Ronquist, Fredrik, "RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language" (2016). Ecology, Evolution and Organismal Biology Publications. 179.
https://lib.dr.iastate.edu/eeob_ag_pubs/179
Comments
This article is fromSyst Biol (2016) 65 (4):726-736. doi:10.1093/sysbio/syw021. Posted with permission.