MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification

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

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.

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MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification
Syndicated from:PLoS ONE

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