title: Scalable metagenomic taxonomy classification using a reference genome database.
abstract: BACKGROUND
  Deep metagenomic sequencing of biological samples has the potential to recover otherwise difficult-to-detect microorganisms and accurately characterize biological samples with limited prior knowledge of sample contents. Existing metagenomic taxonomic classification algorithms, however, do not scale well to analyze large metagenomic datasets, and balancing classification accuracy with computational efficiency presents a fundamental challenge.
  
  
  RESULTS
  A method is presented to shift computational costs to an off-line computation by creating a taxonomy/genome index that supports scalable metagenomic classification. Scalable performance is demonstrated on real and simulated data to show accurate classification in the presence of novel organisms on samples that include viruses, prokaryotes, fungi and protists. Taxonomic classification of the previously published 150 giga-base Tyrolean Iceman dataset was found to take <20 h on a single node 40 core large memory machine and provide new insights on the metagenomic contents of the sample.
  
  
  BACKGROUND
  Software was implemented in C++ and is freely available at http://sourceforge.net/projects/lmat
  
  
  BACKGROUND
  allen99@llnl.gov
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Center for Applied Scientific Computing, Lawrence Livermore National Laboratory and Global Security Directorate, P. O. Box 808, Livermore, CA 94551, USA.
authors.forename: Sasha K
authors.initials: SK
authors.lastname: Ames
authors.forename: David A
authors.initials: DA
authors.lastname: Hysom
authors.forename: Shea N
authors.initials: SN
authors.lastname: Gardner
authors.forename: G Scott
authors.initials: GS
authors.lastname: Lloyd
authors.forename: Maya B
authors.initials: MB
authors.lastname: Gokhale
authors.forename: Jonathan E
authors.initials: JE
authors.lastname: Allen
mesh_terms: D000465:Algorithms; D002965:Classification / Q000379:methods; D030561:Databases, Nucleic Acid; D016678:Genome; D059014:High-Throughput Nucleotide Sequencing; D056186:Metagenomics / Q000379:methods*; D010802:Phylogeny; D012984:Software