BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis

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 evidenc...

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Veröffentlicht in:PLoS computational biology Jg. 15; H. 4; S. e1006650
Hauptverfasser: Bouckaert, Remco, Vaughan, Timothy G., Barido-Sottani, Joëlle, Duchêne, Sebastián, Fourment, Mathieu, Gavryushkina, Alexandra, Heled, Joseph, Jones, Graham, Kühnert, Denise, De Maio, Nicola, Matschiner, Michael, Mendes, Fábio K., Müller, Nicola F., Ogilvie, Huw A., du Plessis, Louis, Popinga, Alex, Rambaut, Andrew, Rasmussen, David, Siveroni, Igor, Suchard, Marc A., Wu, Chieh-Hsi, Xie, Dong, Zhang, Chi, Stadler, Tanja, Drummond, Alexei J.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Public Library of Science 08.04.2019
Public Library of Science (PLoS)
Schlagworte:
Bayesian analysis
Biochemistry
Bioinformatics
Biological research
Computation
Computer applications
Computer programming
Computer programs
Engineering
Environmental science
Evolution
Evolutionary biology
Gene sequencing
Genomes
Genomics
Laboratories
Markov analysis
Mathematical models
Molecular biology
Phylogenetics
Phylogeny
Scientific software
Software
Software engineering
Software industry
Software packages
Systematic biology
Technology application
Trees
New Zealand
United States > US
Switzerland
Germany
ISSN:1553-7358, 1553-734X, 1553-7358
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Beschreibung
Zusammenfassung: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.
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The authors have declared that no competing interests exist.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1006650