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Updated: May 21, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Bayesian models for comparative analysis integrating phylogenetic uncertainty.

Pierre de Villemereuil¹, Jessie A Wells, Robert D Edwards

¹School of Biological Sciences, University of Queensland, Brisbane, 4072 Queensland, Australia.

BMC Evolutionary Biology

|June 30, 2012

Summary

This summary is machine-generated.

Phylogenetic uncertainty and intraspecific variation can skew biological analyses. New Bayesian models accurately incorporate these factors, providing more precise results and realistic confidence intervals for comparative studies.

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Area of Science:

Evolutionary biology
Bioinformatics
Statistical modeling

Background:

Comparative analyses are susceptible to phylogenetic uncertainty and intraspecific variation.
Current methods often fail to account for these uncertainties, leading to inaccurate precision and significance.
A need exists for more general and flexible software to address these limitations.

Purpose of the Study:

To develop Bayesian models for incorporating phylogenetic uncertainty into common biological analyses.
To provide a flexible framework for addressing intraspecific variation and measurement error.

Main Methods:

Developed Bayesian models using Markov Chain Monte Carlo (MCMC) analyses.
Incorporated phylogenetic uncertainty via prior distributions from Bayesian phylogenetic tree estimation.
Utilized OpenBUGS and JAGS for model analysis and application.

Main Results:

Demonstrated applications in linear regression, phylogenetic signal quantification, and measurement error models.
Showed more precise estimation of regression parameters and realistic confidence intervals compared to single-tree methods.
Successfully applied models to a real dataset of Australian rainforest plant traits.

Conclusions:

Empirical priors of phylogenetic uncertainty improve estimation precision and confidence intervals.
Bayesian framework easily accommodates measurement errors and individual variation.
BUGS is a flexible tool for phylogenetic comparative analyses, especially with phylogenetic uncertainty and error.