title: BEAST: Bayesian evolutionary analysis by sampling trees.
abstract: BACKGROUND
  The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented.
  
  
  RESULTS
  BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at http://beast-mcmc.googlecode.com/ under the GNU LGPL license.
  
  
  CONCLUSIONS
  BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.
authors.affiliation: Bioinformatics Institute, University of Auckland, Auckland, New Zealand. alexei@cs.auckland.ac.nz
authors.forename: Alexei J
authors.initials: AJ
authors.lastname: Drummond
authors.forename: Andrew
authors.initials: A
authors.lastname: Rambaut
mesh_terms: D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D019143:Evolution, Molecular; D008957:Models, Genetic; D015233:Models, Statistical; D010802:Phylogeny; D017422:Sequence Analysis, DNA; D012984:Software