title: MetaBinG: using GPUs to accelerate metagenomic sequence classification.
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.
authors: Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
authors: Peng
authors: P
authors: Jia
authors: Liming
authors: L
authors: Xuan
authors: Lei
authors: L
authors: Liu
authors: Chaochun
authors: C
authors: Wei
mesh_terms: D001483:Base Sequence; D056804:Biofuels; D003196:Computer Graphics; D008390:Markov Chains; D054892:Metagenome / Q000235:genetics; D056186:Metagenomics / Q000379:methods*; D008957:Models, Genetic; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
chemical_list: D056804:Biofuels