Many-core algorithms for statistical phylogenetics

Marc A. Suchard, Andrew Rambaut

Research output: Contribution to journalArticlepeer-review

Abstract

Motivation
Statistical phylogenetics is computationally intensive, resulting in considerable attention meted on techniques for parallelization. Codon-based models allow for independent rates of synonymous and replacement substitutions and have the potential to more adequately model the process of protein-coding sequence evolution with a resulting increase in phylogenetic accuracy. Unfortunately, due to the high number of codon states, computational burden has largely thwarted phylogenetic reconstruction under codon models, particularly at the genomic-scale. Here, we describe novel algorithms and methods for evaluating phylogenies under arbitrary molecular evolutionary models on graphics processing units (GPUs), making use of the large number of processing cores to efficiently parallelize calculations even for large state-size models.

Results
We implement the approach in an existing Bayesian framework and apply the algorithms to estimating the phylogeny of 62 complete mitochondrial genomes of carnivores under a 60-state codon model. We see a near 90-fold speed increase over an optimized CPU-based computation and a > 140-fold increase over the currently available implementation, making this the first practical use of codon models for phylogenetic inference over whole mitochondrial or microorganism genomes.

Availability and implementation
Source code provided in BEAGLE: Broad-platform Evolutionary Analysis General Likelihood Evaluator, a cross-platform/processor library for phylogenetic likelihood computation (http://beagle-lib.googlecode.com/). We employ a BEAGLE-implementation using the Bayesian phylogenetics framework BEAST (http://beast.bio.ed.ac.uk/).

Contact
msuchard@ucla.edu; a.rambaut@ed.ac.uk

Original languageEnglish
Pages (from-to)1370-1376
Number of pages7
JournalBioinformatics
Volume25
Issue number11
DOIs
Publication statusPublished - 1 Jun 2009

Keywords

  • CODON-SUBSTITUTION MODELS
  • MAXIMUM-LIKELIHOOD
  • NUCLEOTIDE SUBSTITUTION
  • DNA-SEQUENCES
  • RECONSTRUCTION
  • INFERENCE
  • TREES
  • GENES
  • RATES

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