TY - JOUR
T1 - BEAST 2.5
T2 - An advanced software platform for Bayesian evolutionary analysis
AU - Bouckaert, Remco
AU - Vaughan, Timothy G.
AU - Barido-Sottani, Joëlle
AU - Duchêne, Sebastián
AU - Fourment, Mathieu
AU - Gavryushkina, Alexandra
AU - Heled, Joseph
AU - Jones, Graham
AU - Kühnert, Denise
AU - De Maio, Nicola
AU - Matschiner, Michael
AU - Mendes, Fábio K.
AU - Müller, Nicola F.
AU - Ogilvie, Huw A.
AU - Du Plessis, Louis
AU - Popinga, Alex
AU - Rambaut, Andrew
AU - Rasmussen, David
AU - Siveroni, Igor
AU - Suchard, Marc A.
AU - Wu, Chieh Hsi
AU - Xie, Dong
AU - Zhang, Chi
AU - Stadler, Tanja
AU - Drummond, Alexei J.
N1 - Publisher Copyright:
© 2019 Bouckaert et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2019
Y1 - 2019
N2 - 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.
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.
UR - https://www.scopus.com/pages/publications/85065051451
U2 - 10.1371/journal.pcbi.1006650
DO - 10.1371/journal.pcbi.1006650
M3 - Article
C2 - 30958812
AN - SCOPUS:85065051451
SN - 1553-734X
VL - 15
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 4
M1 - e1006650
ER -