Import phenotype predictions from AMRrules output

This imports antimicrobial phenotype predictions (S/I/R and WT/NWT) generated from genotype data using AMRrules.

Usage

import_amrrules_predictions(
  input,
  sample_col = "sample",
  species_col = "organism",
  ab_col = "drug",
  sir_col = "clinical category",
  ecoff_col = "phenotype",
  method = "genotyping",
  platform = "AMRFinderPlus + AMRrules"
)

Arguments

input

A string representing a dataframe, or a path to an input file, containing the AMRrules output "genome_summary" file, which should be a long-form TSV file with one row per sample and drug.

sample_col

(optional, default "sample") String indicating the name of the input data column that provides the sample name.

species_col

(optional, default "organism") String indicating the name of the input data column that provides a species name. If provided, this column will be converted to micro-organism class mo via AMR::as.mo(). If the rename_cols parameter is set to TRUE, this column will also be renamed as spp_pheno. If interpretation is switched on, this column will be used to identify the appropriate breakpoints for interpretation of each row in the data table.

ab_col

(optional, default "drug") String indicating the name of the input data column that provides a drug name.

sir_col

(optional, default "clinical category") String indicating the name of the input data column that indicates the S/I/R prediction.

ecoff_col

(optional, default "phenotype") String indicating the name of the input data column that indicates the WT/NWT prediction.

method

(optional, default "genotyping") String indicating the value to record in a new method field added to the output table.

platform

(optional, default "AMRFinderPlus + AMRrules") String indicating the value to record in a new platform field added to the output table.

Value

A data frame with the processed AST data, including additional columns:

Examples

if (FALSE) { # \dontrun{
# import and process AST data from EBI, write formatted data to file for later use
predictions <- import_amrrules_predictions("Ecoli_genome_summary.tsv")
} # }