BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis | |
Bouckaert, Remco1,2; Vaughan, Timothy G.3,4; Barido-Sottani, Joelle3,4; Duchene, Sebastian5; Fourment, Mathieu6; Gavryushkina, Alexandra7; Heled, Joseph; Jones, Graham8; Kuehnert, Denise2; De Maio, Nicola9 | |
刊名 | PLOS COMPUTATIONAL BIOLOGY |
2019-04-01 | |
卷号 | 15期号:4页码:28 |
DOI | 10.1371/journal.pcbi.1006650 |
通讯作者 | Bouckaert, Remco(r.bouckaert@auckland.ac.nz) ; Drummond, Alexei J.(alexei@cs.auckland.ac.nz) |
英文摘要 | 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. |
资助项目 | Royal Society of New Zealand Marsden award[UOA1611] ; Royal Society of New Zealand Marsden award[16-UOA-277] ; European Research Council under the Seventh Framework Programme of the European Commission (PATHPHYLODYN)[614725] ; NIH MIDAS[U01 GM110749] ; Swiss National Science foundation (SNF)[CR32I3 166258] ; European Research Council under the Seventh Framework Programme of the European Commission (PhyPD)[335529] ; Max Planck Society ; EMBL ; Swiss National Science Foundation (SNP)[PBBSP3-138680] |
WOS关键词 | NUCLEOTIDE SUBSTITUTION ; LIKELIHOOD-ESTIMATION ; SPECIES TREES ; GENE TREES ; INFERENCE ; MODELS ; TIME ; COALESCENT ; SPECIATION ; RADIATION |
WOS研究方向 | Biochemistry & Molecular Biology ; Mathematical & Computational Biology |
语种 | 英语 |
出版者 | PUBLIC LIBRARY SCIENCE |
WOS记录号 | WOS:000467530600013 |
资助机构 | Royal Society of New Zealand Marsden award ; European Research Council under the Seventh Framework Programme of the European Commission (PATHPHYLODYN) ; NIH MIDAS ; Swiss National Science foundation (SNF) ; European Research Council under the Seventh Framework Programme of the European Commission (PhyPD) ; Max Planck Society ; EMBL ; Swiss National Science Foundation (SNP) |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.205/handle/311034/9710] |
专题 | 古脊椎动物与古人类研究所_图书馆1 |
通讯作者 | Bouckaert, Remco; Drummond, Alexei J. |
作者单位 | 1.Univ Auckland, Ctr Computat Evolut, Auckland, New Zealand 2.Max Planck Inst Sci Human Hist, Jena, Germany 3.Swiss Fed Inst Technol, Dept Biosyst Sci & Engn, CH-4058 Basel, Switzerland 4.Swiss Inst Bioinformat, Lausanne, Switzerland 5.Univ Melbourne, Dept Biochem & Mol Biol, Melbourne, Vic, Australia 6.Univ Technol Sydney, Ithree Inst, Sydney, NSW, Australia 7.Univ Otago, Dept Biochem, Dunedin 9016, New Zealand 8.Univ Gothenburg, Dept Biol & Environm Sci, Box 461, SE-40530 Gothenburg, Sweden 9.European Bioinformat Inst EMBL EBI, European Mol Biol Lab, Hinxton, Cambs, England 10.Univ Basel, Dept Environm Sci, CH-4051 Basel, Switzerland |
推荐引用方式 GB/T 7714 | Bouckaert, Remco,Vaughan, Timothy G.,Barido-Sottani, Joelle,et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis[J]. PLOS COMPUTATIONAL BIOLOGY,2019,15(4):28. |
APA | Bouckaert, Remco.,Vaughan, Timothy G..,Barido-Sottani, Joelle.,Duchene, Sebastian.,Fourment, Mathieu.,...&Drummond, Alexei J..(2019).BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis.PLOS COMPUTATIONAL BIOLOGY,15(4),28. |
MLA | Bouckaert, Remco,et al."BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis".PLOS COMPUTATIONAL BIOLOGY 15.4(2019):28. |
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