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BEAST: Bayesian evolutionary analysis by sampling trees
BEAST is a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree that 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.
Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data
Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types.
Bayesian Phylogenetics with BEAUti and the BEAST 1.7
The Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7 is presented, which implements a family of Markov chain Monte Carlo algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography and related molecular evolutionary analyses.
BEAST 2: A Software Platform for Bayesian Evolutionary Analysis
BEAST 2 now has a fully developed package management system that allows third party developers to write additional functionality that can be directly installed to the BEAST 2 analysis platform via a package manager without requiring a new software release of the platform.
Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7
- A. Rambaut, A. Drummond, Dong Xie, G. Baele, M. Suchard
- Biology, Computer ScienceSystematic Biology
- 27 April 2018
The software package Tracer is presented, for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference, which provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more.
Relaxed Phylogenetics and Dating with Confidence
This work describes how it can be used to estimate phylogenies and divergence times in the face of uncertainty in evolutionary rates and calibration times and provides a means for measuring the clocklikeness of datasets and comparing this measure between different genes and phylogenies.
Bayesian Inference of Species Trees from Multilocus Data
It is demonstrated that both BEST and the new Bayesian Markov chain Monte Carlo method for the multispecies coalescent have much better estimation accuracy for species tree topology than concatenation, and the method outperforms BEST in divergence time and population size estimation.
Bayesian coalescent inference of past population dynamics from molecular sequences.
We introduce the Bayesian skyline plot, a new method for estimating past population dynamics through time from a sample of molecular sequences without dependence on a prespecified parametric model of…
Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10
- M. Suchard, P. Lemey, G. Baele, Daniel L. Ayres, A. Drummond, A. Rambaut
- BiologyVirus Evolution
- 1 January 2018
The BEAST software package unifies molecular phylogenetic reconstruction with complex discrete and continuous trait evolution, divergence-time dating, and coalescent demographic models in an efficient statistical inference engine using Markov chain Monte Carlo integration.
BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis
The full range of new tools and models available on the BEAST 2.5 platform are described, which expand joint evolutionary inference in many new directions, especially for joint inference over multiple data types, non-tree models and complex phylodynamics.