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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3329765/ https://www.ncbi.nlm.nih.gov/pubmed/22357727 http://dx.doi.org/10.1093/sysbio/sys029 |
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author | 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. |
author_facet | 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. |
author_sort | Ronquist, Fredrik |
collection | PubMed |
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(N)/d(S) 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. |
format | Online Article Text |
id | pubmed-3329765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-33297652012-04-19 MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space 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. Syst Biol Software for Systematics and Evolution 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(N)/d(S) 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. Oxford University Press 2012-05 2012-02-22 /pmc/articles/PMC3329765/ /pubmed/22357727 http://dx.doi.org/10.1093/sysbio/sys029 Text en © The Author(s) 2012. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software for Systematics and Evolution 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. MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space |
title | MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space |
title_full | MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space |
title_fullStr | MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space |
title_full_unstemmed | MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space |
title_short | MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space |
title_sort | mrbayes 3.2: efficient bayesian phylogenetic inference and model choice across a large model space |
topic | Software for Systematics and Evolution |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3329765/ https://www.ncbi.nlm.nih.gov/pubmed/22357727 http://dx.doi.org/10.1093/sysbio/sys029 |
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