DPRml: distributed phylogeny reconstruction by maximum likelihood

• Published in: Bioinformatics 2005-04, Vol.21 (7), p.969-974
• Main Authors: Keane, T. M., Naughton, T. J., Travers, S. A. A., McInerney, J. O., McCormack, G. P.
• Format: Article
• Language: English
• Subjects: Algorithms; Biological and medical sciences; Computer Simulation; Evolution, Molecular; Fundamental and applied biological sciences. Psychology; General aspects; Likelihood Functions; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Models, Genetic; Models, Statistical; Phylogeny; Sequence Alignment - methods; Sequence Analysis, DNA - methods; Software
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/bti100

Motivation: In recent years there has been increased interest in producing large and accurate phylogenetic trees using statistical approaches. However for a large number of taxa, it is not feasible to construct large and accurate trees using only a single processor. A number of specialized parallel programs have been produced in an attempt to address the huge computational requirements of maximum likelihood. We express a number of concerns about the current set of parallel phylogenetic programs which are currently severely limiting the widespread availability and use of parallel computing in maximum likelihood-based phylogenetic analysis. Results: We have identified the suitability of phylogenetic analysis to large-scale heterogeneous distributed computing. We have completed a distributed and fully cross-platform phylogenetic tree building program called distributed phylogeny reconstruction by maximum likelihood. It uses an already proven maximum likelihood-based tree building algorithm and a popular phylogenetic analysis library for all its likelihood calculations. It offers one of the most extensive sets of DNA substitution models currently available. We are the first, to our knowledge, to report the completion of a distributed phylogenetic tree building program that can achieve near-linear speedup while only using the idle clock cycles of machines. For those in an academic or corporate environment with hundreds of idle desktop machines, we have shown how distributed computing can deliver a ‘free’ ML supercomputer. Availability: The software (and user manual) is publicly available under the terms of the GNU general public licence from the system webpage at http://www.cs.may.ie/distributed Contact: [e-mail]