RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language

dc.contributor.author Höhna, Sebastian
dc.contributor.author Landis, Michael
dc.contributor.author Heath, Tracy
dc.contributor.author Lartillot, Nicolas
dc.contributor.author Moore, Brian
dc.contributor.author Huelsenbeck, John
dc.contributor.author Ronquist, Fredrik
dc.contributor.department Department of Ecology, Evolution, and Organismal Biology (CALS)
dc.date 2018-02-18T02:26:36.000
dc.date.accessioned 2020-06-30T02:16:55Z
dc.date.available 2020-06-30T02:16:55Z
dc.date.copyright Fri Jan 01 00:00:00 UTC 2016
dc.date.issued 2016-07-01
dc.description.abstract <p>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 <a href="http://www.revbayes.com/">http://www.RevBayes.com</a>.</p>
dc.description.comments <p>This article is fromSyst Biol (2016) 65 (4):726-736. doi:<a href="http://dx.doi.org/10.1093/sysbio/syw021" target="_blank">10.1093/sysbio/syw021</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/eeob_ag_pubs/179/
dc.identifier.articleid 1178
dc.identifier.contextkey 9465869
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath eeob_ag_pubs/179
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/23044
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/eeob_ag_pubs/179/2016_Hohna_RevBayesBayesian.pdf|||Fri Jan 14 21:30:39 UTC 2022
dc.source.uri 10.1093/sysbio/syw021
dc.subject.disciplines Evolution
dc.subject.disciplines Systems Biology
dc.subject.keywords Bayesian inference
dc.subject.keywords Graphical models
dc.subject.keywords MCMC
dc.subject.keywords Statistical phylogenetics
dc.title RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language
dc.type article
dc.type.genre article
dspace.entity.type Publication
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relation.isOrgUnitOfPublication 6fa4d3a0-d4c9-4940-945f-9e5923aed691
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