MODELTEST: testing the model of DNA substitution.
David Posada,Keith A. Crandall +1 more
TLDR
The program MODELTEST uses log likelihood scores to establish the model of DNA evolution that best fits the data.Abstract:
Summary: The program MODELTEST uses log likelihood scores to establish the model of DNA evolution that best fits the data. Availability: The MODELTEST package, including the source code and some documentation is available at http://bioag.byu.edu/zoology/crandall―lab/modeltest.html. Contact: dp47@email.byu.edu.read more
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MEGA5: Molecular Evolutionary Genetics Analysis using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods
Koichiro Tamura,Daniel S. Peterson,Nicholas Peterson,Glen Stecher,Masatoshi Nei,Sudhir Kumar +5 more
TL;DR: The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models, inferring ancestral states and sequences, and estimating evolutionary rates site-by-site.
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MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice across a Large Model Space
Fredrik Ronquist,Maxim Teslenko,Paul van der Mark,Daniel L. Ayres,Aaron E. Darling,Sebastian Höhna,Bret Larget,Liang Liu,Marc A. Suchard,John P. Huelsenbeck +9 more
TL;DR: The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly, and provides more output options than previously, including samples of ancestral states, site rates, site dN/dS rations, branch rates, and node dates.
Journal ArticleDOI
jModelTest 2: more models, new heuristics and parallel computing.
TL;DR: jModelTest 2: more models, new heuristics and parallel computing Diego Darriba, Guillermo L. Taboada, Ramón Doallo and David Posada.
Journal ArticleDOI
jModelTest: Phylogenetic Model Averaging
TL;DR: jModelTest is a new program for the statistical selection of models of nucleotide substitution based on "Phyml" that implements 5 different selection strategies, including "hierarchical and dynamical likelihood ratio tests," the "Akaike information criterion", the "Bayesian information criterion," and a "decision-theoretic performance-based" approach.
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ModelFinder: fast model selection for accurate phylogenetic estimates
Subha Kalyaanamoorthy,Subha Kalyaanamoorthy,Bui Quang Minh,Thomas K. F. Wong,Thomas K. F. Wong,Arndt von Haeseler,Arndt von Haeseler,Lars S. Jermiin,Lars S. Jermiin +8 more
TL;DR: ModelFinder is presented, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates by incorporating a model of rate heterogeneity across sites not previously considered in this context and by allowing concurrent searches of model space and tree space.
References
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TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
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A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences.
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