ExaML version 3: a tool for phylogenomic analyses on supercomputers

doi:10.1093/bioinformatics/btv184

. 2015 Aug 1;31(15):2577-9.

doi: 10.1093/bioinformatics/btv184. Epub 2015 Mar 29.

ExaML version 3: a tool for phylogenomic analyses on supercomputers

Alexey M Kozlov¹, Andre J Aberer¹, Alexandros Stamatakis²

Affiliations

¹ Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany and.
² Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany and Department of informatics, Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany.

PMID: 25819675
PMCID: PMC4514929
DOI: 10.1093/bioinformatics/btv184

ExaML version 3: a tool for phylogenomic analyses on supercomputers

Alexey M Kozlov et al. Bioinformatics. 2015.

. 2015 Aug 1;31(15):2577-9.

doi: 10.1093/bioinformatics/btv184. Epub 2015 Mar 29.

Authors

Alexey M Kozlov¹, Andre J Aberer¹, Alexandros Stamatakis²

Affiliations

¹ Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany and.
² Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany and Department of informatics, Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany.

PMID: 25819675
PMCID: PMC4514929
DOI: 10.1093/bioinformatics/btv184

Abstract

Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Because of the next generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. We present ExaML version 3, a dedicated production-level code for inferring phylogenies on whole-transcriptome and whole-genome alignments using supercomputers.

Results: We introduce several improvements and extensions to ExaML: Extensions of substitution models and supported data types, the integration of a novel load balance algorithm as well as a parallel I/O optimization that significantly improve parallel efficiency, and a production-level implementation for Intel MIC-based hardware platforms.

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References

1. Felsenstein, J. (2004) Inferring Phylogenies . Sinauer Associates Sunderland, Sunderland, MA.
1. Jarvis E.D., et al. . (2014) Whole-genome analyses resolve early branches in the tree of life of modern birds. Science, 346, 1320–1331. - PMC - PubMed
1. Kobert K., et al. . (2014) The divisible load balance problem and its application to phylogenetic inference. In: Brown D., Morgenstern B. (eds.) Algorithms in Bioinformatics, Vol. 8701 of Lecture Notes in Computer Science. Springer, Berlin, pp. 204– 216.
1. Kozlov A.M., et al. . (2014) Efficient computation of the phylogenetic likelihood function on the Intel MIC architecture. In: Parallel Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International, IEEE Computer Society Washington, DC, Phoenix, Arizona, pp. 518–527.
1. Le S.Q., et al. . (2012) Modeling protein evolution with several amino acid replacement matrices depending on site rates. Mol. Biol. Evol., 29, 2921–2936. - PubMed

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[1] Felsenstein, J. (2004) Inferring Phylogenies . Sinauer Associates Sunderland, Sunderland, MA.

[2] Felsenstein, J. (2004) Inferring Phylogenies . Sinauer Associates Sunderland, Sunderland, MA.

[3] Jarvis E.D., et al. . (2014) Whole-genome analyses resolve early branches in the tree of life of modern birds. Science, 346, 1320–1331. - PMC - PubMed

[4] Jarvis E.D., et al. . (2014) Whole-genome analyses resolve early branches in the tree of life of modern birds. Science, 346, 1320–1331. - PMC - PubMed

[5] Kobert K., et al. . (2014) The divisible load balance problem and its application to phylogenetic inference. In: Brown D., Morgenstern B. (eds.) Algorithms in Bioinformatics, Vol. 8701 of Lecture Notes in Computer Science. Springer, Berlin, pp. 204– 216.

[6] Kobert K., et al. . (2014) The divisible load balance problem and its application to phylogenetic inference. In: Brown D., Morgenstern B. (eds.) Algorithms in Bioinformatics, Vol. 8701 of Lecture Notes in Computer Science. Springer, Berlin, pp. 204– 216.

[7] Kozlov A.M., et al. . (2014) Efficient computation of the phylogenetic likelihood function on the Intel MIC architecture. In: Parallel Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International, IEEE Computer Society Washington, DC, Phoenix, Arizona, pp. 518–527.

[8] Kozlov A.M., et al. . (2014) Efficient computation of the phylogenetic likelihood function on the Intel MIC architecture. In: Parallel Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International, IEEE Computer Society Washington, DC, Phoenix, Arizona, pp. 518–527.

[9] Le S.Q., et al. . (2012) Modeling protein evolution with several amino acid replacement matrices depending on site rates. Mol. Biol. Evol., 29, 2921–2936. - PubMed

[10] Le S.Q., et al. . (2012) Modeling protein evolution with several amino acid replacement matrices depending on site rates. Mol. Biol. Evol., 29, 2921–2936. - PubMed

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ExaML version 3: a tool for phylogenomic analyses on supercomputers

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ExaML version 3: a tool for phylogenomic analyses on supercomputers

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