Quantifying the impact of an inference model in Bayesian phylogenetics

Richel J. C. Bilderbeek*, Giovanni Laudanno, Rampal S. Etienne

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Phylogenetic trees are currently routinely reconstructed from an alignment of character sequences (usually nucleotide sequences). Bayesian tools, such as MrBayes, RevBayes and BEAST2, have gained much popularity over the last decade, as they allow joint estimation of the posterior distribution of the phylogenetic trees and the parameters of the underlying inference model. An important ingredient of these Bayesian approaches is the species tree prior. In principle, the Bayesian framework allows for comparing different tree priors, which may elucidate the macroevolutionary processes underlying the species tree. In practice, however, only macroevolutionary models that allow for fast computation of the prior probability are used. The question is how accurate the tree estimation is when the real macroevolutionary processes are substantially different from those assumed in the tree prior.

Here we present pirouette, a free and open-source r package that assesses the inference error made by Bayesian phylogenetics for a given macroevolutionary diversification model. pirouette makes use of BEAST2, but its philosophy applies to any Bayesian phylogenetic inference tool.

We describe pirouette's usage providing full examples in which we interrogate a model for its power to describe another.

Last, we discuss the results obtained by the examples and their interpretation.

Original languageEnglish
Pages (from-to)351-358
Number of pages8
JournalMethods in ecology and evolution
Volume12
Issue number2
Early online date28-Oct-2020
DOIs
Publication statusPublished - Feb-2021

Keywords

  • babette
  • Bayesian model selection
  • BEAST2
  • computational biology
  • evolution
  • phylogenetics
  • r
  • tree prior
  • PROTRACTED SPECIATION
  • MOLECULAR CLOCK
  • RADIATIONS
  • DIVERSITY
  • NUMBER
  • DNA

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