Phylogenetic Inference Using Rev Bayes

Sebastian Hohna; Michael J. Landis; Tracy A. Heath

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Phylogenetic Inference Using Rev Bayes

机译：Phylogenetic Inference Using Rev Bayes

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Bayesian phylogenetic inference aims to estimate the evolutionary relationships among different lineages (species, populations, gene families, viral strains, etc.) in a model-based statistical framework that uses the likelihood function for parameterestimates. In recent years, evolutionary models for Bayesian analysis have grown in number and complexity. RevBayes uses a probabilistic-graphical model framework and an interactive scripting language for model specification to accommodate and exploit model diversity and complexity within a single software package. In this unit we describe how to specify standard phylogenetic models and perform Bayesian phylogenetic analyses in RevBayes. The protocols focus on the basic analysis of inferring a phylogenyfrom single and multiple loci, describe a hypothesis-testing approach, and point to advanced topics. Thus, this unit is a starting point to illustrate the power and potential of Bayesian inference under complex phylogenetic models in RevBayes.

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来源
《Current Protocols in Bioinformatics》 |2017年第57期|6.16/1-6.16/34|共34页
作者
Sebastian Hohna; Michael J. Landis; Tracy A. Heath;
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作者单位

Department of Integrative Biology, University of California, Berkeley, California;

Department of Ecology & Evolutionary Biology, Yale University, New Haven, Connecticut;

Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, Iowa;

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正文语种英语
中图分类遗传学;
关键词
Bayesian phylogenetics; Markov chain Monte Carlo; posterior probabilities; probabilistic graphical models; substitution model;

Phylogenetic Inference Using Rev Bayes

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