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PLoS Comput Biol. 2019 Apr 8;15(4):e1006650. doi: 10.1371/journal.pcbi.1006650. eCollection 2019 Apr.

BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis.

Author information

1
Centre of Computational Evolution, University of Auckland, Auckland, New Zealand.
2
Max Planck Institute for the Science of Human History, Jena, Germany.
3
ETH Zürich, Department of Biosystems Science and Engineering, 4058 Basel, Switzerland.
4
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
5
Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, Victoria, Australia.
6
ithree institute, University of Technology Sydney, Sydney, Australia.
7
Department of Biochemistry, University of Otago, Dunedin 9016, New Zealand.
8
Independent researcher, Auckland, New Zealand.
9
Department of Biological and Environmental Sciences, University of Gothenburg, Box 461, SE 405 30 Göteborg, Sweden.
10
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridgeshire, UK.
11
Department of Environmental Sciences, University of Basel, 4051 Basel, Switzerland.
12
Department of Computer Science, Rice University, Houston, TX 77005-1892, USA.
13
Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK.
14
Institute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Edinburgh, EH9 3FL UK.
15
Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC 27695, USA.
16
Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, W2 1PG, UK.
17
Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
18
Department of Statistics, University of Oxford, OX1 3LB, UK.
19
Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China.

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.

PMID:
30958812
PMCID:
PMC6472827
DOI:
10.1371/journal.pcbi.1006650
[Indexed for MEDLINE]
Free PMC Article

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