MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification

Peng Jia, Liming Xuan, Lei Liu and Chaochun Wei

PLOS ONE, 2011, vol. 6, issue 11, 1-5

Abstract: 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.

Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0025353

DOI: 10.1371/journal.pone.0025353

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