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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
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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. |
format | Online Article Text |
id | pubmed-3223155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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