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A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
The effect of ambiguous data on phylogenetic estimates obtained by maximum likelihood and Bayesian inference
Alan R Lemmon1, Jeremy M Brown, Kathrin Stanger-Hall
1Section of Integrative Biology, University of Texas at Austin, 1 University Station C0930, Austin, TX 78712, USA. alemmon@evotutor.org
Systematic Biology
|June 8, 2010
Summary
Ambiguous data in phylogenetic analyses can mislead results by interacting with rate variation. This bias affects topology and branch length estimates in maximum likelihood and Bayesian frameworks, impacting various evolutionary studies.
Area of Science:
- Evolutionary Biology
- Computational Biology
- Bioinformatics
Background:
- Phylogenetic datasets often contain ambiguous data, such as missing characters or gaps.
- The impact of this ambiguous data on the accuracy of phylogenetic inference remains poorly understood.
Purpose of the Study:
- To investigate how ambiguous data affects phylogenetic accuracy in maximum likelihood and Bayesian frameworks.
- To elucidate the mechanisms by which ambiguous data can lead to misleading phylogenetic estimates.
Main Methods:
- Utilized 4-taxon simulations to isolate and study the effects of ambiguous data.
- Introduced ambiguous data while controlling for confounding factors.
- Evaluated phylogenetic inference under maximum likelihood and Bayesian frameworks, considering among-site rate variation and prior settings.
Main Results:
- Ambiguous data interacts with among-site rate variation to produce inaccurate topology and branch length estimates in both ML and Bayesian analyses.
- In Bayesian analyses, priors on branch lengths and rate heterogeneity can amplify the misleading effects of ambiguous data.
- The degree of bias is influenced by the amount and distribution of ambiguous characters, topological support, and model specification.
Conclusions:
- Ambiguous data poses a significant challenge to phylogenetic accuracy, particularly when combined with rate heterogeneity.
- The findings have broad implications for diverse evolutionary analyses, including divergence time estimation, ancestral state reconstruction, and phylogeography.
- Careful consideration of data ambiguity and model assumptions is crucial for reliable phylogenetic inference.
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