BEAST

BEAST performs Bayesian analysis of molecular sequence data using Markov chain Monte Carlo (MCMC) to infer rooted, time‑measured phylogenies and estimate divergence times under strict and relaxed molecular clock models.

Key Features:

• Bayesian phylogenetic inference: Performs Bayesian phylogenetic inference via MCMC sampling of tree space.
• MCMC methods: Implements Markov chain Monte Carlo (MCMC) algorithms for posterior sampling of model parameters and trees.
• Divergence time dating: Estimates divergence times and produces time‑measured phylogenies.
• Molecular clock models: Supports both strict and relaxed molecular clock models for rate variation among branches.
• Coalescent analysis: Provides highly parametric coalescent models for population-level demographic inference.
• Phylogeography: Enables phylogeographic analyses integrating spatial trait evolution with phylogenies.
• Trait evolution models: Integrates models for discrete and continuous trait evolution with molecular phylogenetic reconstruction.
• Phylodynamics: Supports phylodynamic analyses linking genetic sequence data to population dynamics.
• Heterochronous data handling: Handles non-contemporaneous (heterochronous) sequence data.
• Statistical alignment: Includes statistical alignment tools for sequence data.
• Model and prior options: Offers a broad selection of stochastic models of sequence evolution and prior distributions.
• BEAUti integration: Includes BEAUti for configuring complex models of molecular sequence and phenotypic trait evolution.
• Java implementation and architecture: Implemented in Java with an object-oriented, modular design; source code comprises over 81,000 lines across 779 classes and 81 packages.

Scientific Applications:

• Evolutionary history reconstruction: Reconstructs rooted, time‑scaled evolutionary histories from molecular sequence data.
• Divergence dating: Conducts molecular dating and divergence time estimation across taxa.
• Hypothesis testing: Tests evolutionary hypotheses using Bayesian model comparison and posterior inference.
• Population genetics: Performs coalescent-based population genetic inference and demographic history estimation.
• Phylodynamics and phylogeography: Integrates genetic, temporal, and spatial data for phylodynamic and phylogeographic studies.

Methodology:

Bayesian analysis of molecular sequences via MCMC sampling to infer rooted, time‑measured phylogenies using strict and relaxed molecular clocks, parametric coalescent models, discrete and continuous trait evolution models, statistical alignment, and handling of non-contemporaneous sequence data.