Systematic Zoology Advance Access published online on May 22, 2009
Systematic Zoology, doi:10.1093/sysbio/syp017
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Copyright © Society of Systematic Biologists
The Effect of Ambiguous Data on Phylogenetic Estimates Obtained by Maximum Likelihood and Bayesian Inference
1 Section of Integrative Biology, University of Texas at Austin, 1 University Station C0930, Austin, TX 78712, USA
2 Present address: Department of Scientif ic Computing, Florida State University, Dirac Science Library, Tallahassee, FL 32306-4120, USA
3 Present address: Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA
4 Plant Biology Department, University of Georgia, 403 Biosciences Building, Athens, GA 30602, USA
* Correspondence to be sent to: Department of Scientif ic Computing, Florida State University, Dirac Science Library, Tallahassee, FL 32306-4120, USA; E-mail: alemmon{at}evotutor.org.
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Abstract |
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Although an increasing number of phylogenetic data sets are incomplete, the effect of ambiguous data on phylogenetic accuracy is not well understood. We use 4-taxon simulations to study the effects of ambiguous data (i.e., missing characters or gaps) in maximum likelihood (ML) and Bayesian frameworks. By introducing ambiguous data in a way that removes confounding factors, we provide the first clear understanding of 1 mechanism by which ambiguous data can mislead phylogenetic analyses. We find that in both ML and Bayesian frameworks, among-site rate variation can interact with ambiguous data to produce misleading estimates of topology and branch lengths. Furthermore, within a Bayesian framework, priors on branch lengths and rate heterogeneity parameters can exacerbate the effects of ambiguous data, resulting in strongly misleading bipartition posterior probabilities. The magnitude and direction of the ambiguous data bias are a function of the number and taxonomic distribution of ambiguous characters, the strength of topological support, and whether or not the model is correctly specified. The results of this study have major implications for all analyses that rely on accurate estimates of topology or branch lengths, including divergence time estimation, ancestral state reconstruction, tree-dependent comparative methods, rate variation analysis, phylogenetic hypothesis testing, and phylogeographic analysis.
Keywords: Ambiguous characters; ambiguous data; Bayesian; bias; maximum likelihood; missing data; model misspecification; phylogenetics; posterior probabilities; prior
Received October 8, 2007; Revised January 10, 2008; Accepted December 30, 2008
Associate Editor: Lars Jermiin
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