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MEGARes: an antimicrobial resistance database for high throughput sequencing
Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data ar...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210519/ https://www.ncbi.nlm.nih.gov/pubmed/27899569 http://dx.doi.org/10.1093/nar/gkw1009 |
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author | Lakin, Steven M. Dean, Chris Noyes, Noelle R. Dettenwanger, Adam Ross, Anne Spencer Doster, Enrique Rovira, Pablo Abdo, Zaid Jones, Kenneth L. Ruiz, Jaime Belk, Keith E. Morley, Paul S. Boucher, Christina |
author_facet | Lakin, Steven M. Dean, Chris Noyes, Noelle R. Dettenwanger, Adam Ross, Anne Spencer Doster, Enrique Rovira, Pablo Abdo, Zaid Jones, Kenneth L. Ruiz, Jaime Belk, Keith E. Morley, Paul S. Boucher, Christina |
author_sort | Lakin, Steven M. |
collection | PubMed |
description | Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database. |
format | Online Article Text |
id | pubmed-5210519 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-52105192017-01-05 MEGARes: an antimicrobial resistance database for high throughput sequencing Lakin, Steven M. Dean, Chris Noyes, Noelle R. Dettenwanger, Adam Ross, Anne Spencer Doster, Enrique Rovira, Pablo Abdo, Zaid Jones, Kenneth L. Ruiz, Jaime Belk, Keith E. Morley, Paul S. Boucher, Christina Nucleic Acids Res Database Issue Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database. Oxford University Press 2017-01-04 2016-11-24 /pmc/articles/PMC5210519/ /pubmed/27899569 http://dx.doi.org/10.1093/nar/gkw1009 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Lakin, Steven M. Dean, Chris Noyes, Noelle R. Dettenwanger, Adam Ross, Anne Spencer Doster, Enrique Rovira, Pablo Abdo, Zaid Jones, Kenneth L. Ruiz, Jaime Belk, Keith E. Morley, Paul S. Boucher, Christina MEGARes: an antimicrobial resistance database for high throughput sequencing |
title | MEGARes: an antimicrobial resistance database for high throughput sequencing |
title_full | MEGARes: an antimicrobial resistance database for high throughput sequencing |
title_fullStr | MEGARes: an antimicrobial resistance database for high throughput sequencing |
title_full_unstemmed | MEGARes: an antimicrobial resistance database for high throughput sequencing |
title_short | MEGARes: an antimicrobial resistance database for high throughput sequencing |
title_sort | megares: an antimicrobial resistance database for high throughput sequencing |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210519/ https://www.ncbi.nlm.nih.gov/pubmed/27899569 http://dx.doi.org/10.1093/nar/gkw1009 |
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