Parallel Inference of a 10.000-Taxon Phylogeny with Maximum Likelihood

  • Alexandros Stamatakis
  • Thomas Ludwig
  • Harald Meier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3149)


Inference of large phylogenetic trees with statistical methods is computationally intensive. We recently introduced simple heuristics which yield accurate trees for synthetic as well as real data and are implemented in a sequential program called RAxML. We have demonstrated that RAxML outperforms the currently fastest statistical phylogeny programs (MrBayes, PHYML) in terms of speed and likelihood values on real data. In this paper we present a non-deterministic parallel implementation of our algorithm which in some cases yields super-linear speedups for an analysis of 1.000 organisms on a LINUX cluster. In addition, we use RAxML to infer a 10.000-taxon phylogenetic tree containing representative organisms from the three domains: Eukarya, Bacteria and Archaea. Finally, we compare the sequential speed and accuracy of RAxML and PHYML on 8 synthetic alignments comprising 4.000 sequences.


Parallel Implementation Parallel Inference Good Likelihood Bayesian Phylogenetic Inference Rearrangement Step 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Feng, X., et al.: Parallel algorithms for Bayesian phylogenetic inference. J. Par. Dist. Comp. 63, 707–718 (2003)CrossRefGoogle Scholar
  2. 2.
    Felsenstein, J.: Evolutionary Trees from DNA Sequences: A Maximum Likelihood Approach. J. Mol. Evol. 17, 368–376 (1981)CrossRefGoogle Scholar
  3. 3.
    Guindon, S., et al.: A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood. Syst. Biol. 52(5), 696–704 (2003)CrossRefGoogle Scholar
  4. 4.
    Hasegawa, M., et al.: Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J. Mol. Evol. 22, 160–174 (1985)CrossRefGoogle Scholar
  5. 5.
    Huelsenbeck, J.P., et al.: MRBAYES: Bayesian inference of phylogenetic trees. Bioinf. 17(8), 754–755 (2001)CrossRefGoogle Scholar
  6. 6.
    Ludwig, W., et al.: ARB: A Software Environment for Sequence Data. Nucl. Acids Res. 32(4), 1363–1371 (2004)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Olsen, G., et al.: fastdnaml: A Tool for Construction of Phylogenetic Trees of DNA Sequences using Maximum Likelihood. Comput. Appl. Biosci. 10, 41–48 (1994)Google Scholar
  8. 8.
    PAUP: (visited May 2003)Google Scholar
  9. 9.
    PHYLIP: (visited November 2003) Google Scholar
  10. 10.
    RRZE, (visited October 2003)
  11. 11.
    Stamatakis, A., et al.: New Fast and Accurate Heuristics for Inference of Large Phylogenetic Trees. In: Proc. of IPDPS (2004)Google Scholar
  12. 12.
    Stamatakis, A., et al.: RAxML-III: A Fast Program for Maximum Likelihood-based Inference of Large Phylogenetic Trees. Bioinf. (to be published)Google Scholar
  13. 13.
    Stewart, C., et al.: Parallel Implementation and Performance of fastdnaml - a Program for Maximum Likelihood Phylogenetic Inference. In: Proc. of SC 2001 (2001)Google Scholar
  14. 14.
    Strimmer, K., et al.: Quartet Puzzling: A Maximum-Likelihood Method for Reconstructing Tree Toologies. Mol. Biol. Evol. 13, 964–969 (1996)Google Scholar
  15. 15.
    Williams, T.L., et al.: An Investigation of Phylogenetic Likelihood Methods. In: Proc. of BIBE 2003 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Alexandros Stamatakis
    • 1
  • Thomas Ludwig
    • 2
  • Harald Meier
    • 1
  1. 1.Department of Computer ScienceTechnische Universität MünchenGarching b. MünchenGermany
  2. 2.Department of Computer ScienceRuprecht-Karls-UniversitätHeidelbergGermany

Personalised recommendations