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      Model Selection and Model Averaging in Phylogenetics: Advantages of Akaike Information Criterion and Bayesian Approaches Over Likelihood Ratio Tests

      1 , 2

      Systematic Biology

      Informa UK Limited

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          Abstract

          Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental concepts and techniques of model selection in the context of phylogenetics. We start by reviewing different aspects of the selection of substitution models in phylogenetics from a theoretical, philosophical and practical point of view, and summarize this comparison in table format. We argue that the most commonly implemented model selection approach, the hierarchical likelihood ratio test, is not the optimal strategy for model selection in phylogenetics, and that approaches like the Akaike Information Criterion (AIC) and Bayesian methods offer important advantages. In particular, the latter two methods are able to simultaneously compare multiple nested or nonnested models, assess model selection uncertainty, and allow for the estimation of phylogenies and model parameters using all available models (model-averaged inference or multimodel inference). We also describe how the relative importance of the different parameters included in substitution models can be depicted. To illustrate some of these points, we have applied AIC-based model averaging to 37 mitochondrial DNA sequences from the subgenus Ohomopterus(genus Carabus) ground beetles described by Sota and Vogler (2001).

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          Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses

           Quang Vuong (1989)
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            Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in hominoidea.

            A maximum likelihood method for inferring evolutionary trees from DNA sequence data was developed by Felsenstein (1981). In evaluating the extent to which the maximum likelihood tree is a significantly better representation of the true tree, it is important to estimate the variance of the difference between log likelihood of different tree topologies. Bootstrap resampling can be used for this purpose (Hasegawa et al. 1988; Hasegawa and Kishino 1989), but it imposes a great computation burden. To overcome this difficulty, we developed a new method for estimating the variance by expressing it explicitly. The method was applied to DNA sequence data from primates in order to evaluate the maximum likelihood branching order among Hominoidea. It was shown that, although the orangutan is convincingly placed as an outgroup of a human and African apes clade, the branching order among human, chimpanzee, and gorilla cannot be determined confidently from the DNA sequence data presently available when the evolutionary rate constancy is not assumed.
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              Comparison of phylogenetic trees

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                Author and article information

                Journal
                Systematic Biology
                Informa UK Limited
                1076-836X
                1063-5157
                October 2004
                October 01 2004
                October 2004
                October 2004
                October 01 2004
                October 2004
                : 53
                : 5
                : 793-808
                Affiliations
                [1 ]Departamento de Bioquímica, Genética e Inmunología, Facultad de Biología, Universidad de Vigo Vigo 36200, Spain; E-mail: dposada@uvigo.es
                [2 ]Landcare Research Private Bag 92170, Auckland, New Zealand; E-mail: BuckleyT@LandcareResearch.co.nz
                Article
                10.1080/10635150490522304
                15545256
                © 2004

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