Antimicrobial resistance (AMR) genome annotation and variants data were generated using the Resistance Gene Identifier (RGI), a tool for putative AMR gene detection from submitted sequence data using the AMR detection models available in CARD. To generate these data, RGI was used to analyze molecular sequence data available in NCBI Genomes for 82 pathogens of interest (see Sampling). For each of these pathogens, complete chromosome sequences, complete plasmid sequences, and whole genome shotgun (WGS) assemblies were analyzed individually by RGI.
Genome and variants data is available under both the Perfect and Strict paradigms of RGI, the former tracking perfect matches to the curated reference sequences and mutations in the CARD, while the latter detects previously unknown variants of known AMR genes, including secondary screen for key mutations, using detection models with curated similarity cut-offs to ensure the detected variant is likely a functional AMR gene. For more information, see the Resistance Gene Identifier.
The reported results are entirely dependant upon the curated AMR detection models in CARD, the algorithms available in RGI (recently expanded to include rRNA mutations and efflux over-expression models, see the Resistance Gene Identifier), and the sequence data available at NCBI. These data will change over time as CARD curation, RGI software, and NCBI data evolve.
CARD Resistomes & Variants 3.0.4 is based on sequence data acquired from NCBI on Feb 28, 2019, analyzed using RGI 4.2.2 (DIAMOND homolog detection) and CARD 3.0.1.
Pathogen, NCBI accession, data type, percent identity between the sequence(s) detected and the CARD reference sequence, and RGI detection criteria.
The search box can be used to filter results by gene names (e.g. TEM-), pathogens (e.g. Pseudomonas), or drug class (e.g. macrolide). Multiple search terms will search for entries containing all given terms. For more complex queries, please Download the full data set.
|Accession||Pathogen||Data Type||Perfect Hits||Strict Hits||Drug Classes|