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Updated: Mar 20, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

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

Sebastian Höhna¹, Michael J Landis², Tracy A Heath³

¹Department 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.

Systematic Biology

|May 29, 2016

Summary

This summary is machine-generated.

RevBayes is a new open-source software package for Bayesian inference in phylogenetics. It offers flexibility in model specification and outperforms existing software, enhancing transparency in phylogenetic analyses.

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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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Area of Science:

Computational Biology
Evolutionary Biology
Statistical Modeling

Background:

Current phylogenetic software offers limited, fixed model suites, restricting user flexibility.
Users often need multiple programs for a single phylogenetic study.
Lack of freedom to explore novel or un-implemented models hinders research.

Purpose of the Study:

Introduce RevBayes, an open-source software for Bayesian phylogenetic inference.
Provide a flexible and transparent framework for specifying and analyzing phylogenetic models.
Overcome limitations of existing software in terms of model choice and user interaction.

Main Methods:

Developed RevBayes based on probabilistic graphical models.
Implemented a new domain-specific language, Rev, for interactive model specification.
Utilized Markov Chain Monte Carlo (MCMC) methods for Bayesian inference.

Main Results:

RevBayes allows for the specification of complex phylogenetic-graphical models.
The Rev language is intuitive and similar to R and BUGS.
RevBayes demonstrates computational performance exceeding competing software in standard analyses.
The software reduces "black-box" elements, promoting explicit model definition.

Conclusions:

RevBayes offers unprecedented flexibility and transparency in phylogenetic modeling.
Explicit model specification in RevBayes can improve understanding and encourage methodological innovation.
The software is freely available and suitable for a wide range of statistical phylogenetic analyses.