MEGARes: An antimicrobial resistance database for high throughput sequencing

Steven M. Lakin, Chris Dean, Noelle R. Noyes, Adam Dettenwanger, Anne Spencer Ross, Enrique Doster, Pablo Rovira, Zaid Abdo, Kenneth L. Jones, Jaime Ruiz, Keith E. Belk, Paul S. Morley, Christina Boucher

Research output: Contribution to journalArticlepeer-review

228 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)D574-D580
JournalNucleic acids research
Volume45
Issue numberD1
DOIs
StatePublished - Jan 1 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s) 2016.

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