RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models

RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models Summary: RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Γ yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets ≥4000 taxa it also runs 2–3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25 057 (1463 bp) and 2182 (51 089 bp) taxa, respectively.Availability:Contact:Alexandros.Stamatakis@epfl.chSupplementary information: Supplementary data are available at Bioinformatics online. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bioinformatics Oxford University Press

RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models

Bioinformatics, Volume 22 (21) – Nov 1, 2006

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Publisher
Oxford University Press
Copyright
© Published by Oxford University Press.
ISSN
1367-4803
eISSN
1460-2059
DOI
10.1093/bioinformatics/btl446
pmid
16928733
Publisher site
See Article on Publisher Site

Abstract

Summary: RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Γ yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets ≥4000 taxa it also runs 2–3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25 057 (1463 bp) and 2182 (51 089 bp) taxa, respectively.Availability:Contact:Alexandros.Stamatakis@epfl.chSupplementary information: Supplementary data are available at Bioinformatics online.

Journal

BioinformaticsOxford University Press

Published: Nov 1, 2006

References

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