Centrifuge: Rapid and sensitive classification of metagenomic sequences

Daehwan Kim, Li Song, Florian P. Breitwieser, Steven L. Salzberg

Research output: Contribution to journalArticlepeer-review

248 Scopus citations

Abstract

Centrifuge is a novel microbial classification engine that enables rapid, accurate, and sensitive labeling of reads and quantification of species on desktop computers. The system uses an indexing scheme based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini (FM) index, optimized specifically for the metagenomic classification problem. Centrifuge requires a relatively small index (4.2 GB for 4078 bacterial and 200 archaeal genomes) and classifies sequences at very high speed, allowing it to process the millions of reads from a typical high-throughput DNA sequencing run within a few minutes. Together, these advances enable timely and accurate analysis of large metagenomics data sets on conventional desktop computers. Because of its space-optimized indexing schemes, Centrifuge also makes it possible to index the entire NCBI nonredundant nucleotide sequence database (a total of 109 billion bases) with an index size of 69 GB, in contrast to k-mer-based indexing schemes, which require far more extensive space.

Original languageEnglish (US)
Pages (from-to)1721-1729
Number of pages9
JournalGenome Research
Volume26
Issue number12
DOIs
StatePublished - Dec 2016

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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