R Package for Genetic and Phenotypic Resistance Interpretation
Overview
AMRgen is an open-source R package designed to bridge the gap between genotypic and phenotypic antimicrobial resistance (AMR) data. Developed as an extension to the AMR R package, it provides tools to interpret AMR genes, integrate these findings with antimicrobial susceptibility test (AST) data, and calculate genotype-phenotype associations.
This package is developed in collaboration with the ESGEM-AMR Working Group and is tailored for researchers and healthcare professionals tackling AMR globally.
The AMRgen website has full function documentation and a Vignette working through analysing geno/pheno data using key functions.
Key Features
- Import Genotype and Phenotype Data: Import from common formats (NCBI AST for phenotypes; AMRfinderplus and hAMRonization for genotypes
- Genotype-Phenotype Integration: Links AMR gene presence with phenotypic resistance profiles, enabling deeper insights into resistance mechanisms.
- Automated EUCAST MIC Distribution Integration: Fetch MIC distribution data directly from EUCAST for seamless comparison with local susceptibility data.
- Visualisation: Generate powerful UpSet plots to identify intersections of AMR gene presence and phenotypic resistance, highlighting multidrug resistance patterns.
- Modular and Extensible: Leverages the robust foundation of the AMR package, including antibiotic selectors and clinical breakpoint interpretations.
Planned for development - NCBI-Compliant Export: Export phenotype data to NCBI-compliant antibiogram format. - Expanded Data Import: Import and parse phenotype data from other tools (e.g. CARD, ResFinder).
Getting Started
To install and explore the package, follow the instructions below:
Installation
Note that this package requires the latest version of the AMR package (still in beta).
Install the latest version of the AMR package with:
install.packages("remotes") # if you haven't already
remotes::install_github("msberends/AMR")Then install this package
# Install from GitHub
remotes::install_github("interpretAMR/AMRgen")It is best to restart R before running the installation. If you didn’t do this and/or you encounter issues with the examples below after install, it may help to also restart after the install and start fresh with the examples below.
Quick Usage Examples
Investigate ciprofloxacin resistance vs quinolone genotype markers, via solo PPV and upset plots
# Example public E. coli AST data from NCBI
# (already imported via import_ncbi_ast() and re-interpreted with as.sir())
ecoli_ast
# Import matching E. coli AMRfinderplus data from AllTheBacteria
ecoli_geno <- import_amrfp(ecoli_geno_raw, "Name")
# Calculate positive predictive value for ciprofloxacin resistance
# (for all quinolone-associated genotype markers)
soloPPV_cipro <- solo_ppv_analysis(ecoli_geno, ecoli_ast, antibiotic="Ciprofloxacin", drug_class_list=c("Quinolones"), sir_col="pheno")
# Do upset plot of ciprofloxacin MIC vs quinolone genotype marker combinations
# (for combinations observed at least 5 times)
cip_upset <- amr_upset(soloPPV_cipro$amr_binary, min_set_size=5, assay="mic", order="value")
# Do logistic regression of ciprofloxacin resistance as a function of presence/absence of quinolone-associated markers
# (for markers observed at least 10 times)
models <- amr_logistic(geno_table = import_amrfp(ecoli_geno_raw, "Name"), pheno_table = ecoli_ast,
antibiotic = "Ciprofloxacin", drug_class_list = c("Quinolones"), maf=10)Download reference MIC distribution from eucast.org and compare to example data
# Get MIC reference distribution for ciprofloxacin in E. coli
ecoli_cip_mic_data <- get_eucast_mic_distribution("cipro", "E. coli")
# Plot the reference distribution
mics <- rep(ecoli_cip_mic_data$mic, ecoli_cip_mic_data$count)
ggplot2::autoplot(mics, ab = "cipro", mo = "E. coli", title = "E. coli cipro reference distribution")
# Compare reference distribution to example E. coli data
ecoli_cip <- ecoli_ast$mic[ecoli_ast$drug_agent=="CIP"]
comparison <- compare_mic_with_eucast(ecoli_cip, ab = "cipro", mo = "E. coli")
comparison
ggplot2::autoplot(comparison)For more see the Vignette.