RT Journal Article
SR Electronic
T1 BEAST 2.5: An Advanced Software Platform for Bayesian Evolutionary Analysis
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 474296
DO 10.1101/474296
A1 Remco Bouckaert
A1 Timothy G. Vaughan
A1 Joëlle Barido-Sottani
A1 Sebastián Duchêne
A1 Mathieu Fourment
A1 Alexandra Gavryushkina
A1 Joseph Heled
A1 Graham Jones
A1 Denise Kühnert
A1 Nicola De Maio
A1 Michael Matschiner
A1 Fábio K. Mendes
A1 Nicola F. Müller
A1 Huw Ogilvie
A1 Louis du Plessis
A1 Alex Popinga
A1 Andrew Rambaut
A1 David Rasmussen
A1 Igor Siveroni
A1 Marc A. Suchard
A1 Chieh-Hsi Wu
A1 Dong Xie
A1 Chi Zhang
A1 Tanja Stadler
A1 Alexei J. Drummond
YR 2018
UL http://biorxiv.org/content/early/2018/11/19/474296.abstract
AB Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments.Developing such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.Author summary Bayesian phylogenetic inference methods have undergone considerable development in recent years, and joint modelling of rich evolutionary data, including genomes, phenotypes and fossil occurrences is increasingly common. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing scientific software is increasingly crucial to advancement in many fields of biology. The challenges range from practical software development and engineering, distributed team coordination, conceptual development and statistical modelling, to validation and testing. BEAST 2 is one such computational software platform for phylogenetics, population genetics and phylodynamics, and was first announced over 4 years ago. Here we describe the full range of new tools and models available on the BEAST 2.5 platform, which expand joint evolutionary inference in many new directions, especially for joint inference over multiple data types, non-tree models and complex phylodynamics.