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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...

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Autores principales: Saputra, Dhany, Rasmussen, Simon, Larsen, Mette V., Haddad, Nizar, Sperotto, Maria Maddalena, Aarestrup, Frank M., Lund, Ole, Sicheritz-Pontén, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
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.
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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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