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Phycas: Software for Bayesian Phylogenetic Analysis
by
Swofford, David L.
, Holder, Mark T.
, Lewis, Paul O.
in
Algorithms
/ Bayes Theorem
/ Bayesian analysis
/ Chlorophyta - classification
/ Chlorophyta - genetics
/ Classification - methods
/ Interfaces
/ Mathematical models
/ Open source software
/ Phylogenetics
/ Phylogeny
/ Software
/ SOFTWARE FOR SYSTEMATICS AND EVOLUTION
/ Systematic biology
/ Topology
2015
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Phycas: Software for Bayesian Phylogenetic Analysis
by
Swofford, David L.
, Holder, Mark T.
, Lewis, Paul O.
in
Algorithms
/ Bayes Theorem
/ Bayesian analysis
/ Chlorophyta - classification
/ Chlorophyta - genetics
/ Classification - methods
/ Interfaces
/ Mathematical models
/ Open source software
/ Phylogenetics
/ Phylogeny
/ Software
/ SOFTWARE FOR SYSTEMATICS AND EVOLUTION
/ Systematic biology
/ Topology
2015
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Do you wish to request the book?
Phycas: Software for Bayesian Phylogenetic Analysis
by
Swofford, David L.
, Holder, Mark T.
, Lewis, Paul O.
in
Algorithms
/ Bayes Theorem
/ Bayesian analysis
/ Chlorophyta - classification
/ Chlorophyta - genetics
/ Classification - methods
/ Interfaces
/ Mathematical models
/ Open source software
/ Phylogenetics
/ Phylogeny
/ Software
/ SOFTWARE FOR SYSTEMATICS AND EVOLUTION
/ Systematic biology
/ Topology
2015
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Journal Article
Phycas: Software for Bayesian Phylogenetic Analysis
2015
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Overview
Phycas is open source, freely available Bayesian phylogenetics software written primarily in C++ but with Python interface. Phycas specializes in Bayesian model selection for nucleotide sequence data, particularly the estimation of marginal likelihoods, central to computing Bayes Factors. Marginal likelihoods can be estimated using newer methods (Thermodynamic Integration and Generalized Steppingstone) that are more accurate than the widely used Harmonic Mean estimator. In addition, Phycas supports two posterior predictive approaches to model selection: Gelfand—Ghosh and Conditional Predictive Ordinates. The General Time Reversible family of substitution models, as well as a codon model, are available, and data can be partitioned with all parameters unlinked except tree topology and edge lengths. Phycas provides for analyses in which the prior on tree topologies allows polytomous trees as well as fully resolved trees, and provides for several choices for edge length priors, including a hierarchical model as well as the recently described compound Dirichlet prior, which helps avoid overly informative induced priors on tree length.
Publisher
Oxford University Press
Subject
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