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Reads2Type: a web application for rapid microbial taxonomy identification
BACKGROUND: Identification of bacteria may be based on sequencing and molecular analysis of a specific locus such as 16S rRNA, or a set of loci such as in multilocus sequence typing. In the near future, healthcare institutions and routine diagnostic microbiology laboratories may need to sequence the...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4659212/ https://www.ncbi.nlm.nih.gov/pubmed/26608174 http://dx.doi.org/10.1186/s12859-015-0829-0 |
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author | Saputra, Dhany Rasmussen, Simon Larsen, Mette V. Haddad, Nizar Sperotto, Maria Maddalena Aarestrup, Frank M. Lund, Ole Sicheritz-Pontén, Thomas |
author_facet | Saputra, Dhany Rasmussen, Simon Larsen, Mette V. Haddad, Nizar Sperotto, Maria Maddalena Aarestrup, Frank M. Lund, Ole Sicheritz-Pontén, Thomas |
author_sort | Saputra, Dhany |
collection | PubMed |
description | BACKGROUND: Identification of bacteria may be based on sequencing and molecular analysis of a specific locus such as 16S rRNA, or a set of loci such as in multilocus sequence typing. In the near future, healthcare institutions and routine diagnostic microbiology laboratories may need to sequence the entire genome of microbial isolates. Therefore we have developed Reads2Type, a web-based tool for taxonomy identification based on whole bacterial genome sequence data. RESULTS: Raw sequencing data provided by the user are mapped against a set of marker probes that are derived from currently available bacteria complete genomes. Using a dataset of 1003 whole genome sequenced bacteria from various sequencing platforms, Reads2Type was able to identify the species with 99.5 % accuracy and on the minutes time scale. CONCLUSIONS: In comparison with other tools, Reads2Type offers the advantage of not needing to transfer sequencing files, as the entire computational analysis is done on the computer of whom utilizes the web application. This also prevents data privacy issues to arise. The Reads2Type tool is available at http://www.cbs.dtu.dk/~dhany/reads2type.html. |
format | Online Article Text |
id | pubmed-4659212 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46592122015-11-26 Reads2Type: a web application for rapid microbial taxonomy identification Saputra, Dhany Rasmussen, Simon Larsen, Mette V. Haddad, Nizar Sperotto, Maria Maddalena Aarestrup, Frank M. Lund, Ole Sicheritz-Pontén, Thomas BMC Bioinformatics Methodology Article BACKGROUND: Identification of bacteria may be based on sequencing and molecular analysis of a specific locus such as 16S rRNA, or a set of loci such as in multilocus sequence typing. In the near future, healthcare institutions and routine diagnostic microbiology laboratories may need to sequence the entire genome of microbial isolates. Therefore we have developed Reads2Type, a web-based tool for taxonomy identification based on whole bacterial genome sequence data. RESULTS: Raw sequencing data provided by the user are mapped against a set of marker probes that are derived from currently available bacteria complete genomes. Using a dataset of 1003 whole genome sequenced bacteria from various sequencing platforms, Reads2Type was able to identify the species with 99.5 % accuracy and on the minutes time scale. CONCLUSIONS: In comparison with other tools, Reads2Type offers the advantage of not needing to transfer sequencing files, as the entire computational analysis is done on the computer of whom utilizes the web application. This also prevents data privacy issues to arise. The Reads2Type tool is available at http://www.cbs.dtu.dk/~dhany/reads2type.html. BioMed Central 2015-11-25 /pmc/articles/PMC4659212/ /pubmed/26608174 http://dx.doi.org/10.1186/s12859-015-0829-0 Text en © Saputra et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Saputra, Dhany Rasmussen, Simon Larsen, Mette V. Haddad, Nizar Sperotto, Maria Maddalena Aarestrup, Frank M. Lund, Ole Sicheritz-Pontén, Thomas Reads2Type: a web application for rapid microbial taxonomy identification |
title | Reads2Type: a web application for rapid microbial taxonomy identification |
title_full | Reads2Type: a web application for rapid microbial taxonomy identification |
title_fullStr | Reads2Type: a web application for rapid microbial taxonomy identification |
title_full_unstemmed | Reads2Type: a web application for rapid microbial taxonomy identification |
title_short | Reads2Type: a web application for rapid microbial taxonomy identification |
title_sort | reads2type: a web application for rapid microbial taxonomy identification |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4659212/ https://www.ncbi.nlm.nih.gov/pubmed/26608174 http://dx.doi.org/10.1186/s12859-015-0829-0 |
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