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A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
Assessing the Goodness of Fit of Phylogenetic Comparative Methods: A Meta-Analysis and Simulation Study
1Department of Statistics, Feng-Chia University, Taichung, Taiwan, Republic of China.
Plos One
|July 5, 2013
Summary
Phylogenetic comparative methods (PCMs) fit to data is rarely assessed. For smaller phylogenies, independent contrast and non-phylogenetic models fit best, with correlations robust across methods.
Area of Science:
- Evolutionary biology
- Comparative genomics
- Phylogenetics
Background:
- Phylogenetic comparative methods (PCMs) are widely used for analyzing data from related species.
- The goodness-of-fit of these methods to the data is infrequently evaluated.
Purpose of the Study:
- To assess the fit of various PCMs to empirical data.
- To determine if specific PCMs are consistently more appropriate than others for comparative analyses.
Main Methods:
- A meta-analysis of 122 phylogenetic data sets (9-117 species) published between 2002-2005.
- Comparison of PCMs using Akaike information criterion and REML analysis for bivariate data.
- Evaluation of correlation estimates and bootstrapped confidence intervals across different models.
Main Results:
- For phylogenies with fewer than 100 taxa, the Independent Contrast method and independent, non-phylogenetic models demonstrated the best fit.
- Correlations derived from different PCMs for bivariate analyses were qualitatively similar.
- The choice of PCM did not significantly alter correlation estimates from real data.
Conclusions:
- Researchers can select PCMs based on their understanding of the underlying evolutionary mechanisms.
- The robustness of correlation estimates suggests flexibility in PCM choice for bivariate analyses.
- Further research could explore PCM fit for larger phylogenies and more complex data structures.
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