RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference.
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ABSTRACT: Motivation
Phylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture and medicine. Finding the optimal tree under the popular maximum likelihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets.Results
We present RAxML-NG, a from-scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML. RAxML-NG offers improved accuracy, flexibility, speed, scalability, and usability compared with RAxML/ExaML. On taxon-rich datasets, RAxML-NG typically finds higher-scoring trees than IQTree, an increasingly popular recent tool for ML-based phylogenetic inference (although IQ-Tree shows better stability). Finally, RAxML-NG introduces several new features, such as the detection of terraces in tree space and the recently introduced transfer bootstrap support metric.Availability and implementation
The code is available under GNU GPL at https://github.com/amkozlov/raxml-ng. RAxML-NG web service (maintained by Vital-IT) is available at https://raxml-ng.vital-it.ch/.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Kozlov AM
PROVIDER: S-EPMC6821337 | biostudies-literature | 2019 Nov
REPOSITORIES: biostudies-literature
Publications
RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference.
Kozlov Alexey M AM Darriba Diego D Flouri Tomáš T Morel Benoit B Stamatakis Alexandros A
Bioinformatics (Oxford, England) 20191101 21
<h4>Motivation</h4>Phylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture and medicine. Finding the optimal tree under the popular maximum likelihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets.<h4>Results</h4>We present RAxML-NG, a from-scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML. R ...[more]
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