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.

Conclusion: 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.

Figure 1

Consensus tree of 17 dengue 4 env sequences The consensus tree for the example analysis of Dengue 4 sequences under the strict clock analysis with a GTR + CP substitution model. Each internal node is labeled with the posterior probability of monophyly of the corresponding clade. The gray bars illustrated the extent of the 95% highest posterior density intervals for each divergence time. The scale is in years.