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

Author:

Kozlov Alexey M1ORCID,Darriba Diego1ORCID,Flouri Tomáš1,Morel Benoit1,Stamatakis Alexandros12

Affiliation:

1. Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany

2. Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany

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.

Funder

Klaus Tschira Foundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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