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A Practical Guide to Phylogenetics for Nonexperts
Published on: February 6, 2014
A likelihood-based method for testing for nonstochastic variation of diversification rates in phylogenies
Kevin J McConway1, Hallie J Sims
1Department of Statistics, The Open University, Milton Keynes MK7 6AA, United Kingdom. k.j.mcconway@open.ac.uk
Evolution; International Journal of Organic Evolution
|April 3, 2004
Summary
A new likelihood-based relative rates test demonstrates superior statistical accuracy and power compared to the older Slowinski-Guyer test for analyzing taxonomic diversification rates. This improved method offers more reliable insights into evolutionary patterns and rate heterogeneity across diverse clades.
Area of Science:
- Evolutionary Biology
- Phylogenetics
- Biostatistics
Background:
- Observed variations in taxonomic diversification rates are often attributed to biological, ecological, and environmental factors.
- Accurate assessment of these variations requires distinguishing genuine rate heterogeneity from stochastic processes.
- Relative rate tests are crucial for evaluating species richness asymmetry in sister taxa, especially when paleontological data is scarce.
Purpose of the Study:
- To critically evaluate the statistical performance of the Slowinski-Guyer relative rates test, particularly when combined with Fisher's procedure for multiple taxon pairs.
- To introduce and detail a recently developed likelihood-based relative rates test.
- To compare the accuracy, statistical power, and sensitivity of both tests under various biologically plausible scenarios.
Main Methods:
- Description of pragmatic difficulties encountered with the Slowinski-Guyer test.
- Presentation of the development of a likelihood-based relative rates test.
- Extensive simulations were conducted to assess Type I error rates, statistical power, and sensitivity to dataset composition (e.g., inclusion of small taxon pairs, number of pairs) and violations of null model assumptions for both tests.
Main Results:
- The likelihood-based test demonstrated superior statistical properties, exhibiting more accurate Type I error rates and higher statistical power across most tested scenarios compared to the Slowinski-Guyer test.
- The Slowinski-Guyer test was found to be overly conservative, especially with datasets containing numerous small taxon pairs, leading to inaccurate rejection of null hypotheses.
- Both tests showed improved performance when excluding small taxon pairs, but this came at the cost of reduced power and accuracy due to fewer included pairs. Performance degraded significantly when taxon size distributions violated null model assumptions.
Conclusions:
- The Slowinski-Guyer test's limitations in accuracy and power, particularly with small taxon pairs, can lead to misleading conclusions regarding taxonomic rate heterogeneity.
- The likelihood-based relative rates test offers a more accurate and powerful alternative for detecting rate heterogeneity in evolutionary studies.
- Researchers should carefully consider the statistical properties of relative rate tests and dataset characteristics to ensure reliable inferences about diversification patterns.
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