MEGARes

MEGARes is a hand-curated antibiotic resistance database which incorporates previously published resistance sequences for antimicrobial drugs, while also expanding to include published sequences for metal and biocide resistance determinants. In MEGARes 2.0, the nodes of the acyclic hierarchical ontology include four antimicrobial compound types, 57 classes, 220 mechanisms of resistance, and 1,345 gene groups that classify the 7,868 accessions. [1][2] This works in conjunction with the AmrPlusPlus (AMR ++ version 2.0) pipeline to classify resistome sequences directly from FASTA.

MEGARes
Content
DescriptionMEGARes is an antimicrobial resistance database made for high throughput sequencing based at Colorado State University
Data types
captured		Antimicrobial resistance genes and phenotypes
OrganismsBacteria
Contact
Research centerColorado State University
Primary citationPMID 27899569
Access
Websitehttp://megares.meglab.org
Download URLDownload
Miscellaneous
Bookmarkable
entities		yes

The database focuses on the analysis of large-scale, ecological sequence datasets with an annotation structure that allows for the development of high throughput acyclical classfiers and hierarchical statistical analysis of big data. MEGARes annotation consists of three hierarchical levels when looking at AMR genes: drug class, mechanism, and group. The MEGARes content was compiled from various other databases: Resfinder, ARG-ANNOT, Comprehensive Antibiotic Resistance Database (CARD), and the National Center for Biotechnology Information (NCBI) Lahey Clinic beta-lactamase archive.

MEGARes allows users to analyze antimicrobial resistance on a population-level, similar to a microbiome analysis, from a FASTA sequence or keywords in their search bar. Furthermore, users can access AmrPlusplus, a pipeline for resistome analysis of metagenomic datasets that can be integrated with the MEGARes database.

See also

References
  1. , Lakin, S.M., Dean, C., Noyes, N.R., Dettenwanger, A., Spencer Ross, A., Doster, E., Rovira, P., Abdo, Z., Jones, K.L., Ruiz, J., Belk, K.E., Morley, P.S., Boucher, C. (2016) MEGARes: an antimicrobial database for high throughput sequencing. Nucleic Acids Res., 45. DOI: 10.1093/nar/gkw1009
  2. Enrique Doster, Steven M Lakin, Christopher J Dean, Cory Wolfe, Jared G Young, Christina Boucher, Keith E Belk, Noelle R Noyes, Paul S Morley (2020) MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data. https://doi.org/10.1093/nar/gkz1010
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