The Effect of Branch Length Variation on the Selection of Models of Molecular Evolution |
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Authors: | David Posada |
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Institution: | (1) Department of Zoology, Brigham Young University, Provo, UT 84602-5255, USA, US |
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Abstract: | Models of sequence evolution play an important role in molecular evolutionary studies. The use of inappropriate models of
evolution may bias the results of the analysis and lead to erroneous conclusions. Several procedures for selecting the best-fit
model of evolution for the data at hand have been proposed, like the likelihood ratio test (LRT) and the Akaike (AIC) and
Bayesian (BIC) information criteria. The relative performance of these model-selecting algorithms has not yet been studied
under a range of different model trees. In this study, the influence of branch length variation upon model selection is characterized.
This is done by simulating sequence alignments under a known model of nucleotide substitution, and recording how often this
true model is recovered by different model-fitting strategies. Results of this study agree with previous simulations and suggest
that model selection is reasonably accurate. However, different model selection methods showed distinct levels of accuracy.
Some LRT approaches showed better performance than the AIC or BIC information criteria. Within the LRTs, model selection is
affected by the complexity of the initial model selected for the comparisons, and only slightly by the order in which different
parameters are added to the model. A specific hierarchy of LRTs, which starts from a simple model of evolution, performed
overall better than other possible LRT hierarchies, or than the AIC or BIC.
Received: 2 October 2000 / Accepted: 4 January 2001 |
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Keywords: | : Nucleotide substitution models — Model selection — Likelihood ratio test — Hierarchical likelihood ratio tests — Akaike information criterion — Bayesian information criterion — Mixed χ 2— Branch length variation — Phylogenetics |
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