16 Scopus citations


Bayesian phylogenetic inference aims to estimate the evolutionary relationships among different lineages (species, populations, gene families, viral strains, etc.) in a model-based statistical framework that uses the likelihood function for parameter estimates. In recent years, evolutionary models for Bayesian analysis have grown in number and complexity. RevBayes uses a probabilisticgraphical model framework and an interactive scripting language for model specification to accommodate and exploit model diversity and complexity within a single software package. In this unit we describe how to specify standard phylogenetic models and perform Bayesian phylogenetic analyses in RevBayes. The protocols focus on the basic analysis of inferring a phylogeny from single and multiple loci, describe a hypothesis-testing approach, and point to advanced topics. Thus, this unit is a starting point to illustrate the power and potential of Bayesian inference under complex phylogenetic models in RevBayes.

Original languageEnglish
Pages (from-to)6.16.1-6.16.34
JournalCurrent Protocols in Bioinformatics
StatePublished - Mar 1 2017


  • Bayesian phylogenetics
  • Markov chain monte carlo
  • posterior probabilities
  • probabilistic graphical models
  • substitution model


Dive into the research topics of 'Phylogenetic inference using RevBayes'. Together they form a unique fingerprint.

Cite this