MrBayes 3: Bayesian phylogenetic inference under mixed models
TLDR
MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models to analyze heterogeneous data sets and explore a wide variety of structured models mixing partition-unique and shared parameters.Abstract:
Summary: MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types—e.g. morphological, nucleotide, and protein— and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.read more
Citations
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Journal ArticleDOI
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
RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models
TL;DR: UNLABELLED RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML) that has been used to compute ML trees on two of the largest alignments to date.
Journal ArticleDOI
New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0
Stéphane Guindon,Jean-François Dufayard,Vincent Lefort,Maria Anisimova,Wim Hordijk,Olivier Gascuel +5 more
TL;DR: A new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves and a new test to assess the support of the data for internal branches of a phylogeny are introduced.
Journal ArticleDOI
PAML 4: Phylogenetic Analysis by Maximum Likelihood
TL;DR: PAML, currently in version 4, is a package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML), which can be used to estimate parameters in models of sequence evolution and to test interesting biological hypotheses.
Proceedings ArticleDOI
Creating the CIPRES Science Gateway for inference of large phylogenetic trees
TL;DR: Development of the CIPRES Science Gateway is described, a web portal designed to provide researchers with transparent access to the fastest available community codes for inference of phylogenetic relationships, and implementation of these codes on scalable computational resources.
References
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TreeView : an application to display phylogenetic trees on personal computers
TL;DR: TreeView is a simple, easy to use phylogenetic tree viewing utility that runs under both MacOS (on Apple Macintosh computers) and under Microsoft Windows on Intel based computers, the two most common personal computers used by biologists.
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Bayesian inference of phylogeny and its impact on evolutionary biology
TL;DR: Bayesian inference of phylogeny brings a new perspective to a number of outstanding issues in evolutionary biology, including the analysis of large phylogenetic trees and complex evolutionary models and the detection of the footprint of natural selection in DNA sequences.
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Markov Chasin Monte Carlo Algorithms for the Bayesian Analysis of Phylogenetic Trees
Bret Larget,DL Simon +1 more
TL;DR: The Bayesian framework for analyzing aligned nucleotide sequence data to reconstruct phylogenies, assess uncertainty in the reconstructions, and perform other statistical inferences is developed and a Markov chain Monte Carlo sampler is employed to sample trees and model parameter values from their joint posterior distribution.
Journal ArticleDOI
Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference
TL;DR: The proposed parallel algorithm retains the ability to explore multiple peaks in the posterior distribution of trees while maintaining a fast execution time, and performance results indicate nearly linear speed improvement in both programming models for small and large data sets.