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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2011-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22132069/?tool=EBI |
| _version_ | 1818435507764330496 |
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| author | Peng Jia Liming Xuan Lei Liu Chaochun Wei |
| author_facet | Peng Jia Liming Xuan Lei Liu Chaochun Wei |
| author_sort | Peng Jia |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-14T16:53:59Z |
| format | Article |
| id | doaj.art-08fd6aa9f1404db6bdb92b3fd966313f |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-14T16:53:59Z |
| publishDate | 2011-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-08fd6aa9f1404db6bdb92b3fd966313f2022-12-21T22:54:00ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-01611e2535310.1371/journal.pone.0025353MetaBinG: using GPUs to accelerate metagenomic sequence classification.Peng JiaLiming XuanLei LiuChaochun WeiMetagenomic 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.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22132069/?tool=EBI |
| spellingShingle | Peng Jia Liming Xuan Lei Liu Chaochun Wei MetaBinG: using GPUs to accelerate metagenomic sequence classification. PLoS ONE |
| 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 |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22132069/?tool=EBI |
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