AMR-meta: a k-mer and metafeature approach to classify antimicrobial resistance from high-throughput short-read metagenomics data
High-throughput metagenomic sequencing of microbial samples enables profiling of AMR genes through comparison with curated AMR databases. However, the performance of current methods is often hampered by database incompleteness and the presence of homology/homoplasy with other non-AMR genes in sequenced samples.
AMR-meta is a fast, accurate classifier that exploits non-AMR negative sets to improve sensitivity and specificity. The differences in AMR ontologies and the high variance of all tools in classification outputs call for the deployment of standard benchmarking data and protocols, to fairly compare AMR prediction tools.
OUR UNDERWRITERS
Unrestricted financial support by:
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Antimicrobial Resistance Fighter Coalition |
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Bangalore Bioinnovation Centre |
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Evotec |
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JSS University |
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INTERNATIONAL FEDERATION PHARMACEUTICAL MANUFACTURERS & ASSOCIATIONS |
Global Ambassador Network
Welcome at the AMR Insights Ambassador Network!
The AMR Insights Ambassador Network is a growing, distinctive group of professionals who stand out for their commitment, willingness to cooperate and open attitude to combat Antimicrobial resistance (AMR).
