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MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new v... Full description

Journal Title: Systematic Biology 2012-05-01, Vol.61 (3), p.539-542
Main Author: Ronquist, Fredrik
Other Authors: Teslenko, Maxim , van der Mark, Paul , Ayres, Daniel L , Darling, Aaron , Höhna, Sebastian , Larget, Bret , Liu, Liang , Suchard, Marc A , Huelsenbeck, John P
Format: Electronic Article Electronic Article
Language: English
Subjects:
Quelle: Alma/SFX Local Collection
Publisher: England: Oxford University Press
ID: ISSN: 1063-5157
Zum Text:
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recordid: cdi_swepub_primary_oai_DiVA_org_su_80768
title: MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space
format: Article
creator:
  • Ronquist, Fredrik
  • Teslenko, Maxim
  • van der Mark, Paul
  • Ayres, Daniel L
  • Darling, Aaron
  • Höhna, Sebastian
  • Larget, Bret
  • Liu, Liang
  • Suchard, Marc A
  • Huelsenbeck, John P
subjects:
  • Algorithms
  • Bayes factor
  • Bayesian inference
  • Bioinformatics
  • Biological Sciences
  • Biologiska vetenskaper
  • Classification - methods
  • Computer software
  • Convergence
  • Evolution
  • Evolutionary Biology
  • Evolutionsbiologi
  • Inference
  • Libraries
  • Markov analysis
  • Markov Chains
  • Matematik
  • matematisk statistik
  • Mathematical Statistics
  • Mathematics
  • MCMC
  • Metropolitan areas
  • model averaging
  • model choice
  • Modeling
  • Models, Biological
  • Monte Carlo Method
  • Monte Carlo simulation
  • Natural Sciences
  • Naturvetenskap
  • Phylogenetics
  • Phylogeny
  • Posadas
  • Software
  • Software for Systematics
  • Software for Systematics and Evolution
  • Trees
ispartof: Systematic Biology, 2012-05-01, Vol.61 (3), p.539-542
description: Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d^/dg rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
language: eng
source: Alma/SFX Local Collection
identifier: ISSN: 1063-5157
fulltext: fulltext
issn:
  • 1063-5157
  • 1076-836X
  • 1076-836X
url: Link


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descriptionSince its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d^/dg rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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subjectAlgorithms ; Bayes factor ; Bayesian inference ; Bioinformatics ; Biological Sciences ; Biologiska vetenskaper ; Classification - methods ; Computer software ; Convergence ; Evolution ; Evolutionary Biology ; Evolutionsbiologi ; Inference ; Libraries ; Markov analysis ; Markov Chains ; Matematik ; matematisk statistik ; Mathematical Statistics ; Mathematics ; MCMC ; Metropolitan areas ; model averaging ; model choice ; Modeling ; Models, Biological ; Monte Carlo Method ; Monte Carlo simulation ; Natural Sciences ; Naturvetenskap ; Phylogenetics ; Phylogeny ; Posadas ; Software ; Software for Systematics ; Software for Systematics and Evolution ; Trees
ispartofSystematic Biology, 2012-05-01, Vol.61 (3), p.539-542
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descriptionSince its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d^/dg rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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notesAssociate Editor: David Posada
abstractSince its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d^/dg rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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