BioinformaticsBioinformaticsPeer-reviewed journal article
RAxML-NG: A fast, scalable, and user-friendly tool for maximum likelihood phylogenetic inference
Alexey M. KozloviD, Diego DarribaiD, Tomáš FlouriiD, Benoit MoreliD, Alexandros StamatakisiD
Abstract
MotivationPhylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture, and medicine. Finding the optimal tree under the popular maximum like-lihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets.\n\nResultsWe 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 to 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 a the recently introduced transfer bootstrap support metric.\n\nAvailabilityThe 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/.\n\nContactalexey.kozlov@h-its.org
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