105
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      BEAGLE: An Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.

          Related collections

          Most cited references3

          • Record: found
          • Abstract: found
          • Article: not found

          Many-core algorithms for statistical phylogenetics.

          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. 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. 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/).
            Bookmark
            • Record: found
            • Abstract: not found
            • Book: not found

            PAUP*: Phylogenetic Analysis Using Parsimony (* and Other Methods)

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Genetic algorithm approaches for the phylogenetic analyses of large biological sequence datasets under the maximum likelihood criterion. Ph.D. Dissertation

                Bookmark

                Author and article information

                Journal
                Syst Biol
                sysbio
                sysbio
                Systematic Biology
                Oxford University Press
                1063-5157
                1076-836X
                January 2012
                01 October 2011
                01 October 2011
                : 61
                : 1
                : 170-173
                Affiliations
                [1 ]Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
                [2 ]Genome Center, University of California, Davis, CA 95616, USA
                [3 ]Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA
                [4 ]Department of Scientific Computing, Florida State University, Tallahassee, FL 32306, USA
                [5 ]Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT 06269, USA
                [6 ]Department of Integrative Biology, University of California, Berkeley, CA 94720, USA
                [7 ]Swedish Museum of Natural History, 114 18 Stockholm, Sweden
                [8 ]Center for Evolutionary Genomics, Institute for Genome Sciences & Policy, Duke University, Durham, NC 27708, USA
                [9 ]Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK; E-mail: a.rambaut@ 123456ed.ac.uk
                [10 ]Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA
                [11 ]Department of Biomathematics
                [12 ]Department of Biostatistics
                [13 ]Department of Human Genetics, University of California, Los Angeles, CA 90095, USA; E-mail: msuchard@ 123456ucla.edu
                Author notes
                [* ]Correspondence to be sent to Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA; E-mail: ayres@ 123456umiacs.umd.edu .

                Associate Editor: David Posada

                Article
                10.1093/sysbio/syr100
                3243739
                21963610
                f5778ceb-2434-48bc-aa5c-5bb38b745a41
                © The Author(s) 2011. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 July 2011
                : 6 September 2011
                : 26 September 2011
                Categories
                Software for Systematics and Evolution

                Animal science & Zoology
                maximum likelihood,bayesian phylogenetics,parallel computing,gpu
                Animal science & Zoology
                maximum likelihood, bayesian phylogenetics, parallel computing, gpu

                Comments

                Comment on this article