RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference

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ID: 289833
2019
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Abstract
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.
Reference Key
openalex_W2949867654 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Alexey M. Kozlov, Diego Darriba, Tomáš Flouri, Benoît Morel, Alexandros Stamatakis
Journal BMC Bioinformatics
Year 2019
DOI
10.1093/bioinformatics/btz305
URL
https://doi.org/10.1093/bioinformatics/btz305
Keywords Keywords not found

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