BEAST 2.5: An Advanced Software Platform for Bayesian Evolutionary Analysis

Bouckaert, R; Vaughan, T; Barido-Sottani, J; Duchene, S; Fourment, M; Gavryushkina, A; Heled, J; Jones, G; Kuhnert, D; de Maio, N; Matschiner, M; Mendes, F; Muller, N; Ogilvie, H; du Plessis, L; Popinga, A; Rambaut, A; Rasmussen, D; Siveroni, I; Suchard, M; Wu, C-H; Xie, D; Zhang, C; Stadler, T; Drummond, A

BEAST 2.5: An Advanced Software Platform for Bayesian Evolutionary Analysis

Bouckaert, R Vaughan, T Barido-Sottani, J Duchene, S Fourment, M

Gavryushkina, A Heled, J

Jones, G Kuhnert, D

de Maio, N

Matschiner, M Mendes, F Muller, N Ogilvie, H du Plessis, L Popinga, A Rambaut, A

Rasmussen, D Siveroni, I Suchard, M Wu, C-H Xie, D Zhang, C Stadler, T Drummond, A

Permalink

Publication Type:: Journal Article
Citation:: 2019
Issue Date:: 2019-01-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Accepted Manuscript VersionAdobe PDF (1.03 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Bouckaert, R	en_US
dc.contributor.author	Vaughan, T	en_US
dc.contributor.author	Barido-Sottani, J	en_US
dc.contributor.author	Duchene, S	en_US
dc.contributor.author	Fourment, M https://orcid.org/0000-0001-8153-9822	en_US
dc.contributor.author	Gavryushkina, A	en_US
dc.contributor.author	Heled, J https://orcid.org/0000-0002-2403-7997	en_US
dc.contributor.author	Jones, G	en_US
dc.contributor.author	Kuhnert, D https://orcid.org/0000-0002-5657-018X	en_US
dc.contributor.author	de Maio, N https://orcid.org/0000-0002-1776-8564	en_US
dc.contributor.author	Matschiner, M	en_US
dc.contributor.author	Mendes, F	en_US
dc.contributor.author	Muller, N	en_US
dc.contributor.author	Ogilvie, H	en_US
dc.contributor.author	du Plessis, L	en_US
dc.contributor.author	Popinga, A	en_US
dc.contributor.author	Rambaut, A https://orcid.org/0000-0002-1278-598X	en_US
dc.contributor.author	Rasmussen, D	en_US
dc.contributor.author	Siveroni, I	en_US
dc.contributor.author	Suchard, M	en_US
dc.contributor.author	Wu, C-H	en_US
dc.contributor.author	Xie, D	en_US
dc.contributor.author	Zhang, C	en_US
dc.contributor.author	Stadler, T	en_US
dc.contributor.author	Drummond, A	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	2019	en_US
dc.identifier.uri	http://hdl.handle.net/10453/129447
dc.description.abstract	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.	en_US
dc.relation.isbasedon	10.1101/474296	en_US
dc.title	BEAST 2.5: An Advanced Software Platform for Bayesian Evolutionary Analysis	en_US
dc.type	Journal Article
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - ithree - Institute of Infection, Immunity and Innovation
utslib.copyright.status	open_access
pubs.declined	2019-01-10T16:28:00.24+1100
pubs.consider-herdc	false	en_US
pubs.publication-status	Published	en_US

Abstract:

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.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/129447