skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

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

Bioinformatics, 2019-11, Vol.35 (21), p.4453-4455 [Peer Reviewed Journal]

The Author(s) 2019. Published by Oxford University Press. 2019 ;The Author(s) 2019. Published by Oxford University Press. ;ISSN: 1367-4803 ;EISSN: 1460-2059 ;EISSN: 1367-4811 ;DOI: 10.1093/bioinformatics/btz305 ;PMID: 31070718

Full text available

Citations Cited by
  • Title:
    RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference
  • Author: Kozlov, Alexey M ; Darriba, Diego ; Flouri, Tomáš ; Morel, Benoit ; Stamatakis, Alexandros
  • Wren, Jonathan
  • Subjects: Applications Notes
  • Is Part Of: Bioinformatics, 2019-11, Vol.35 (21), p.4453-4455
  • Description: 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.
  • Publisher: England: Oxford University Press
  • Language: English
  • Identifier: ISSN: 1367-4803
    EISSN: 1460-2059
    EISSN: 1367-4811
    DOI: 10.1093/bioinformatics/btz305
    PMID: 31070718
  • Source: Journals@Ovid Open Access Journal Collection Rolling
    Geneva Foundation Free Medical Journals at publisher websites
    PubMed Central
    Open Access: Oxford University Press Open Journals
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait