This repository houses data and R code for the paper: "Ciprofloxacin resistance in Klebsiella pneumoniae: phenotype prediction from genotype and global distribution of resistance determinants", by the KlebNET-GSP AMR Genotype-Phenotype Group.
The primary input data is in supplementary Tables S2 and S3 of the paper, included here as tables/TableS2_genotypes.tsv (genotype data) and tables/TableS3_phenotypes_metadata.tsv (susceptibility phenotypes and metadata).
Each .Rmd file contains R code that uses these data files to generate figures, tables, or summary statistics presented in the paper. Executing an .Rmd file using knitR generates a corresponding .html file, where you can view the code itself and the outputs of each code block. Figures and tables shown in the paper are generated using these .Rmd files, and are written to the directories tables/ and figures/.
Public data downloaded from Pathogenwatch via this site, and corresponding code, is in the Pathogenwatch/ directory. Output figures are written to the main figures/ directory.
The ciprofloxacin resistance predictor can be used via:
- Kleborate v3.2.4 (command line tool)
- Pathogenwatch v23.4.4 (web-based tool)
Information about the four columns used to report ciprofloxacin resistance prediction results can be found here.
If you use the code in this repository, please cite this repository and its DOI: Tsang et al. "Ciprofloxacin resistance in Klebsiella pneumoniae". https://github.com/klebgenomics/cipropaper (2025). https://doi.org/10.5281/zenodo.17193872.
If you use any data, figures or tables from this repository, please cite the paper: Tsang et al. "Ciprofloxacin resistance in Klebsiella pneumoniae: phenotype prediction from genotype and global distribution of resistance determinants". BioRxiv (2025). https://doi.org/10.1101/2025.09.24.678318.
If you use Kleborate to analyse your own data and report the ciprofloxacin predictions, please cite the paper: Tsang et al. "Ciprofloxacin resistance in Klebsiella pneumoniae: phenotype prediction from genotype and global distribution of resistance determinants". BioRxiv (2025). https://doi.org/10.1101/2025.09.24.678318 as well as the primary Kleborate paper.
