Package: AMRvalid 1.0.0

AMRvalid: Population-Aware Evaluation of Antimicrobial Resistance Predictions

Evaluates antimicrobial resistance phenotype predictions made by external models and rule-based tools against phenotypic reference results, accounting for the population structure of bacterial isolates. Provides a documented data contract and input validation; classification and probability metrics and antimicrobial susceptibility testing agreement metrics (categorical agreement, very major, major and minor errors, essential agreement) per species and antimicrobial; checks for overlap between training and test isolates; performance by genomic distance to the training data; cluster bootstrap intervals and paired model comparisons; calibration; prevalence-adjusted predictive values; and reports aligned with the TRIPOD+AI checklist (Collins et al. (2024) <doi:10.1136/bmj-2023-078378>). Organism and antimicrobial identifiers use the classes of the 'AMR' package. Models are not trained inside the package.

Authors:Md Omar Faruqe [aut, cre, cph]

AMRvalid_1.0.0.tar.gz
AMRvalid_1.0.0.zip(r-4.7-any)AMRvalid_1.0.0.zip(r-4.6-any)AMRvalid_1.0.0.zip(r-4.5-any)
AMRvalid_1.0.0.tgz(r-4.6-any)AMRvalid_1.0.0.tgz(r-4.5-any)
AMRvalid_1.0.0.tar.gz(r-4.7-any)AMRvalid_1.0.0.tar.gz(r-4.6-any)
AMRvalid_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
AMRvalid/json (API)

# Install 'AMRvalid' in R:
install.packages('AMRvalid', repos = c('https://omarfaruqe.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/omarfaruqe/amrvalid/issues

On CRAN:

Conda:

3.48 score 5 scripts 22 exports 1 dependencies

Last updated from:a39901ba95. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK118
source / vignettesOK228
linux-releaseOK124
macos-releaseOK125
macos-oldrelOK141
windows-develOK166
windows-releaseOK174
windows-oldrelOK193
wasm-releaseOK83

Exports:amr_ast_agreementamr_bootstrapamr_calibrationamr_contractamr_contract_schemaamr_data_summaryamr_distance_evalamr_evaluateamr_example_dataamr_import_predictionsamr_metricsamr_nearest_train_distanceamr_paired_compareamr_ppv_npvamr_prop_ciamr_provenanceamr_reportamr_simulateamr_species_evalamr_validateamr_validate_splitsvalidate_amr_data

Dependencies:AMR

Why population-aware evaluation matters
A simulated collection | Step 1: check the split | Step 2: internal versus external performance | Step 3: performance against distance to training | Step 4: intervals that respect clustering | Key points

Last update: 2026-11-03
Started: 2026-10-31

Evaluating rule-based predictors on public data
Step 1: what is in the data? | Step 2: performance per predictor | Step 3: do outbreak clones flatter the results? | Step 4: intervals that respect clustering | Step 5: comparing the two meropenem rules on the same isolates | Step 6: stability over time | Step 7: a report for the paper | Caveats

Last update: 2026-11-03
Started: 2026-11-03