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MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification

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...

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Detalles Bibliográficos
Autores principales: Jia, Peng, Xuan, Liming, Liu, Lei, Wei, Chaochun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3223155/
https://www.ncbi.nlm.nih.gov/pubmed/22132069
http://dx.doi.org/10.1371/journal.pone.0025353
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author Jia, Peng
Xuan, Liming
Liu, Lei
Wei, Chaochun
author_facet Jia, Peng
Xuan, Liming
Liu, Lei
Wei, Chaochun
author_sort Jia, Peng
collection PubMed
description 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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spelling pubmed-32231552011-11-30 MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification Jia, Peng Xuan, Liming Liu, Lei Wei, Chaochun PLoS One Research Article 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. Public Library of Science 2011-11-23 /pmc/articles/PMC3223155/ /pubmed/22132069 http://dx.doi.org/10.1371/journal.pone.0025353 Text en Jia et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Jia, Peng
Xuan, Liming
Liu, Lei
Wei, Chaochun
MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification
title MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification
title_full MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification
title_fullStr MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification
title_full_unstemmed MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification
title_short MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification
title_sort metabing: using gpus to accelerate metagenomic sequence classification
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3223155/
https://www.ncbi.nlm.nih.gov/pubmed/22132069
http://dx.doi.org/10.1371/journal.pone.0025353
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