PLoS ONE (Jan 2011)

MetaBinG: using GPUs to accelerate metagenomic sequence classification.

  • Peng Jia,
  • Liming Xuan,
  • Lei Liu,
  • Chaochun Wei

DOI
https://doi.org/10.1371/journal.pone.0025353
Journal volume & issue
Vol. 6, no. 11
p. e25353

Abstract

Read online

Metagenomic sequence classification is a procedure to assign sequences to their source genomes. It is one of the important steps for metagenomic sequence data analysis. Although many methods exist, classification of high-throughput metagenomic sequence data in a limited time is still a challenge. We present here an ultra-fast metagenomic sequence classification system (MetaBinG) using graphic processing units (GPUs). The accuracy of MetaBinG is comparable to the best existing systems and it can classify a million of 454 reads within five minutes, which is more than 2 orders of magnitude faster than existing systems. MetaBinG is publicly available at http://cbb.sjtu.edu.cn/~ccwei/pub/software/MetaBinG/MetaBinG.php.