MBE Advance Access originally published online on October 31, 2003
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Mol. Biol. Evol. 21(1):188-199. 2004
DOI: 10.1093/molbev/msh014
© 2004 by the Society for Molecular Biology and Evolution. ISSN: 0737-4038
How Meaningful Are Bayesian Support Values?
,1
* Department of Biology, Colorado State University, Fort Collins
Department of Entomology, The Ohio State University, Columbus
Department of Zoology, Natural History Museum and Institute, Chiba, Japan
E-mail: psimmons{at}lamar.colostate.edu.
In this study, we used an empirical example based on 100 mitochondrial genomes from higher teleost fishes to compare the accuracy of parsimony-based jackknife values with Bayesian support values. Phylogenetic analyses of 366 partitions, using differential taxon and character sampling from the entire data matrix of 100 taxa and 7,990 characters, were performed for both phylogenetic methods. The tree topology and branch-support values from each partition were compared with the tree inferred from all taxa and characters. Using this approach, we quantified the accuracy of the branch-support values assigned by the jackknife and Bayesian methods, with respect to each of 15 basal clades. In comparing the jackknife and Bayesian methods, we found that (1) both measures of support differ significantly from an ideal support index; (2) the jackknife underestimated support values; (3) the Bayesian method consistently overestimated support; (4) the magnitude by which Bayesian values overestimate support exceeds the magnitude by which the jackknife underestimates support; and (5) both methods performed poorly when taxon sampling was increased and character sampling was not increases. These results indicate that (1) the higher Bayesian support values are inappropriate (in magnitude), and (2) Bayesian support values should not be interpreted as probabilities that clades are correctly resolved. We advocate the continued use of the relatively conservative bootstrap and jackknife approaches to estimating branch support rather than the more extreme overestimates provided by the Markov Chain Monte Carlo–based Bayesian methods.
Key Words: branch support • bootstrap support • jackknife support • posterior probabilities • ayesian phylogenetic inference • parsimony
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