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

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... Full description

Journal Title: Systematic Biology 2016, Vol.65 (4), p.726-736
Main Author: Höhna, Sebastian
Other Authors: Landis, Michael J , Heath, Tracy A , Boussau, Bastien , Lartillot, Nicolas , Moore, Brian R , Huelsenbeck, John P , Ronquist, Fredrik
Format: Electronic Article Electronic Article
Language: English
Subjects:
Quelle: Alma/SFX Local Collection
Publisher: England: Oxford University Press
ID: ISSN: 1063-5157
Zum Text:
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recordid: cdi_swepub_primary_oai_DiVA_org_su_134166
title: RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language
format: Article
creator:
  • Höhna, Sebastian
  • Landis, Michael J
  • Heath, Tracy A
  • Boussau, Bastien
  • Lartillot, Nicolas
  • Moore, Brian R
  • Huelsenbeck, John P
  • Ronquist, Fredrik
subjects:
  • Algorithms
  • Bayes Theorem
  • Bayesian analysis
  • Bayesian inference
  • Bioinformatics
  • Bioinformatics (Computational Biology)
  • Bioinformatik (beräkningsbiologi)
  • Biological Sciences
  • Biologiska vetenskaper
  • Classification - methods
  • Computer and Information Sciences
  • Computer software
  • Data- och informationsvetenskap
  • Diversity of life
  • Evolution
  • Graph theory
  • Inference
  • Life Sciences
  • Livets mångfald
  • Mathematical models
  • Models, Biological
  • Natural Sciences
  • Naturvetenskap
  • Open source software
  • Phylogenetics
  • Phylogeny
  • Probabilistic modeling
  • Programming languages
  • rev genes
  • Software
  • Software for Systematics
  • Software for Systematics and Evolution
  • Software packages
ispartof: Systematic Biology, 2016, Vol.65 (4), p.726-736
description: 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. Phylogeneticgraphical 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.
language: eng
source: Alma/SFX Local Collection
identifier: ISSN: 1063-5157
fulltext: fulltext
issn:
  • 1063-5157
  • 1076-836X
  • 1076-836X
url: Link


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descriptionPrograms 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. Phylogeneticgraphical 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.
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subjectAlgorithms ; Bayes Theorem ; Bayesian analysis ; Bayesian inference ; Bioinformatics ; Bioinformatics (Computational Biology) ; Bioinformatik (beräkningsbiologi) ; Biological Sciences ; Biologiska vetenskaper ; Classification - methods ; Computer and Information Sciences ; Computer software ; Data- och informationsvetenskap ; Diversity of life ; Evolution ; Graph theory ; Inference ; Life Sciences ; Livets mångfald ; Mathematical models ; Models, Biological ; Natural Sciences ; Naturvetenskap ; Open source software ; Phylogenetics ; Phylogeny ; Probabilistic modeling ; Programming languages ; rev genes ; Software ; Software for Systematics ; Software for Systematics and Evolution ; Software packages
ispartofSystematic Biology, 2016, Vol.65 (4), p.726-736
rights
0Copyright © 2016 Society of Systematic Biologists
1The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. 2016
2The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.
3Distributed under a Creative Commons Attribution 4.0 International License
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7Ronquist, Fredrik
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descriptionPrograms 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. Phylogeneticgraphical 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.
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0Algorithms
1Bayes Theorem
2Bayesian analysis
3Bayesian inference
4Bioinformatics
5Bioinformatics (Computational Biology)
6Bioinformatik (beräkningsbiologi)
7Biological Sciences
8Biologiska vetenskaper
9Classification - methods
10Computer and Information Sciences
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titleRevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language
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volume65
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issn
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notesAssociate Editor: David Posada
abstractPrograms 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. Phylogeneticgraphical 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.
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