MBE Advance Access published online on November 17, 2004
Molecular Biology and Evolution, doi:10.1093/molbev/msi050
Molecular Biology and Evolution © Society for Molecular Biology and Evolution 2004; all rights reserved
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1 Initiative in Bioinformatics and Evolutionary Studies (IBEST, University of Idaho), Moscow, Idaho, USA; Program of Bioinformatics and Computational Biology, University of Idaho, Moscow, Idaho, USA; Department of Mathematics, University of Idaho, Moscow, Idaho, USA
* To whom correspondence should be addressed. Currently available methods for model selection used in phylogenetic analysis are based on an initial fixed tree topology. Once a model is picked based on this topology a rigorous search of the tree space is run under that model to find the maximum likelihood estimate of the tree (topology and branch lengths) and the maximum likelihood estimates of the model parameters. In this paper we propose two extensions to Minin et al's (2003) decision theoretic (DT) approach that relax the fixed topology restriction. We also relax the fixed topology restriction for the BIC and the AIC methods. We compare the performance of the different methods (the relaxed, restricted and the likelihood ratio test (LRT)) using simulated data. This comparison is done by evaluating the relative complexity of the models resulting from each method and by comparing the performance of the chosen models in estimating the true tree. We also compare the methods relative to one another by measuring the closeness of the estimated trees corresponding to the different chosen models under these methods. We show that varying the topology does not have a major impact on model choice. We also show that the outcome of the two proposed extensions is identical and is comparable to that of the BIC, Extended-BIC and DT. Hence, using the simpler methods in choosing a model for analyzing the data is more computationally feasible with results comparable to the more computationally intensive methods. Another outcome of this study is that the same conclusions of Minin et. al. (2003) are reinforced. That is, likelihood ratio test (LRT), Extended-AIC, and AIC result in more complicated models that do not contribute to the performance of the phylogenetic inference yet cause a significant increase in the time required for data analysis.
Research Article
Accounting for Uncertainty in the Tree Topology has Little Effect on the Decision Theoretic Approach to Model Selection in Phylogeny Estimation
2 Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, USA
3 Initiative in Bioinformatics and Evolutionary Studies (IBEST, University of Idaho), Moscow, Idaho, USA; Program of Bioinformatics and Computational Biology, University of Idaho, Moscow, Idaho, USA; Department of Biological Science, University of Idaho, Moscow, Idaho, USA
Zaid Abdo, E-mail: abdo9538{at}uidaho.edu
Abstract 
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