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- Erixon, Per, et al.
(author)
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Reliability of Bayesian Posterior Probabilities and Bootstrap Frequencies in Phylogenetics
- 2003
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In: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 52:5, s. 665-673
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Journal article (peer-reviewed)abstract
- Many empirical studies have revealed considerable differences between nonparametric bootstrapping and Bayesian posterior probabilities in terms of the support values for branches, despite claimed predictions about their approximate equivalence. We investigated this problem by simulating data, which were then analyzed by maximum likelihood bootstrapping and Bayesian phylogenetic analysis using identical models and reoptimization of parameter values. We show that Bayesian posterior probabilities are significantly higher than corresponding nonparametric bootstrap frequencies for true clades, but also that erroneous conclusions will be made more often. These errors are strongly accentuated when the models used for analyses are underparameterized. When data are analyzed under the correct model, nonparametric bootstrapping is conservative. Bayesian posterior probabilities are also conservative in this respect, but less so.
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| 2. |
- Erixon, P., Svennblad, B., Britton, T., and Oxelman, B.
(author)
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Reliability of Bayesian Posterior Probabilities and Bootstrap Frequencies in Phylogenetics
- 2003
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In: Systematic Biology. - : London, Taylor & Francis Group. - 1063-5157 .- 1076-836X. ; 52:5, s. 665-673
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Journal article (peer-reviewed)abstract
- Abstract.—Many empirical studies have revealed considerable differences between nonparametric bootstrapping and Bayesian posterior probabilities in terms of the support values for branches, despite claimed predictions about their approximate equivalence
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| 3. |
- Nylander, Johan A. A., et al.
(author)
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Bayesian phylogenetic analysis of combined data
- 2004
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In: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 53:1, s. 47-67
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Journal article (pop. science, debate, etc.)abstract
- The recent development of Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) techniques has facilitated the exploration of parameter-rich evolutionary models. At the same time, stochastic models have become more realistic (and complex) and have been extended to new types of data, such as morphology. Based on this foundation, we developed a Bayesian MCMC approach to the analysis of combined data sets and explored its utility in inferring relationships among gall wasps based on data from morphology and four genes (nuclear and mitochondrial, ribosomal and protein coding). Examined models range in complexity from those recognizing only a morphological and a molecular partition to those having complex substitution models with independent parameters for each gene. Bayesian MCMC analysis deals efficiently with complex models: convergence occurs faster and more predictably for complex models, mixing is adequate for all parameters even under very complex models, and the parameter update cycle is virtually unaffected by model partitioning across sites. Morphology contributed only 5% of the characters in the data set but nevertheless influenced the combined-data tree, supporting the utility of morphological data in multigene analyses. We used Bayesian criteria (Bayes factors) to show that process heterogeneity across data partitions is a significant model component, although not as important as among-site rate variation. More complex evolutionary models are associated with more topological uncertainty and less conflict between morphology and molecules. Bayes factors sometimes favor simpler models over considerably more parameter-rich models, but the best model overall is also the most complex and Bayes factors do not support exclusion of apparently weak parameters from this model. Thus, Bayes factors appear to be useful for selecting among complex models, but it is still unclear whether their use strikes a reasonable balance between model complexity and error in parameter estimates.
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| 4. |
- Popp, Magnus, et al.
(author)
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Evolution of a RNA polymerase gene family in Silene (Caryophyllaceae) - incomplete concerted evolution and topological congruence among paralogues
- 2004
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In: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 53:6, s. 914-932
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Journal article (peer-reviewed)abstract
- Four low-copy nuclear DNA intron regions from the second largest subunits of the RNA polymerase gene family (RPA2, RPB2, RPD2a, and RPD2b), the internal transcribed spacers (ITSs) from the nuclear ribosomal regions, and the rps16 intron from the chloroplast were sequenced and used in a phylogenetic analysis of 29 species from the tribe Sileneae (Caryophyllaceae). We used a low stringency nested polymerase chain reaction (PCR) approach to overcome the difficulties of constructing specific primers for amplification of the low copy nuclear DNA regions. Maximum parsimony analyses resulted in largely congruent phylogenetic trees for all regions. We tested overall model congruence in a likelihood context using the software PLATO and found that ITSs, RPA2, and RPB2 deviated from the maximum likelihood model for the combined data. The topology parameter was then isolated and topological congruence assessed by nonparametric bootstrapping. No strong topological incongruence was found. The analysis of the combined data sets resolves previously poorly known major relationships within Sileneae. Two paralogues of RPD2 were found, and several independent losses and incomplete concerted evolution were inferred. The among-site rate variation was significantly lower in the RNA polymerase introns than in the rps16 intron and ITSs, a property that is attractive in phylogenetic analyses.
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