Title
Phylogenetics, likelihood, evolution and complexity
Abstract
Summary: Phylogenetics, likelihood, evolution and complexity (PLEX) is a flexible and fast Bayesian Markov chain Monte Carlo software program for large-scale analysis of nucleotide and amino acid data using complex evolutionary models in a phylogenetic framework. The program gains large speed improvements over standard approaches by implementing ‘partial sampling of substitution histories’, a data augmentation approach that can reduce data analysis times from months to minutes on large comparative datasets. A variety of nucleotide and amino acid substitution models are currently implemented, including non-reversible and site-heterogeneous mixture models. Due to efficient algorithms that scale well with data size and model complexity, PLEX can be used to make inferences from hundreds to thousands of taxa in only minutes on a desktop computer. It also performs probabilistic ancestral sequence reconstruction. Future versions will support detection of co-evolutionary interactions between sites, probabilistic tests of convergent evolution and rigorous testing of evolutionary hypotheses in a Bayesian framework. Availability and implementation:PLEX v1.0 is licensed under GPL. Source code and documentation will be available for download at www.evolutionarygenomics.com/ProgramsData/PLEX. PLEX is implemented in C++ and supported on Linux, Mac OS X and other platforms supporting standard C++ compilers. Example data, control files, documentation and accessory Perl scripts are available from the website. Contact: David.Pollock@UCDenver.edu Supplementary information:Supplementary data are available at Bioinformatics online.
Year
DOI
Venue
2012
10.1093/bioinformatics/bts555
Bioinformatics
Keywords
Field
DocType
algorithms,probability,bayes theorem,markov chains,monte carlo method,phylogeny
Data mining,Markov chain Monte Carlo,Source code,Computer science,Markov chain,Software,Bioinformatics,Probabilistic logic,Mixture model,Perl,Bayesian probability
Journal
Volume
Issue
ISSN
28
22
1367-4803
Citations 
PageRank 
References 
1
0.36
3
Authors
4
Name
Order
Citations
PageRank
A. P. Jason de Koning121.04
Wanjun Gu2123.34
Todd A. Castoe322.00
David D. Pollock4493.27