Determine bug-drug combinations

Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use format on the result to prettify it to a printable format, see Examples.

bug_drug_combinations(x, col_mo = NULL, minimum = 30,
  FUN = mo_shortname, ...)

# S3 method for bug_drug_combinations
format(x, combine_IR = FALSE,
  add_ab_group = TRUE, decimal.mark = getOption("OutDec"),
  big.mark = ifelse(decimal.mark == ",", ".", ","), ...)

Arguments

x	data with antibiotic columns, like e.g. AMX and AMC
col_mo	column name of the IDs of the microorganisms (see as.mo), defaults to the first column of class mo. Values will be coerced using as.mo.
minimum	the minimum allowed number of available (tested) isolates. Any isolate count lower than minimum will return NA with a warning. The default number of 30 isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.
FUN	the function to call on the mo column to transform the microorganism IDs, defaults to mo_shortname
...	argumments passed on to FUN
combine_IR	logical to indicate whether values R and I should be summed
add_ab_group	logical to indicate where the group of the antimicrobials must be included as a first column
decimal.mark	the character to be used to indicate the numeric decimal point.
big.mark	character; if not empty used as mark between every big.interval decimals before (hence big) the decimal point.

Source

M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition, 2014, Clinical and Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m39/.

Details

The function format calculates the resistance per bug-drug combination. Use combine_IR = FALSE (default) to test R vs. S+I and combine_IR = TRUE to test R+I vs. S.

The language of the output can be overwritten with options(AMR_locale), please see translate.

Read more on our website!

On our website https://msberends.gitlab.io/AMR you can find a tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

# NOT RUN {
x <- bug_drug_combinations(example_isolates)
x
format(x)

# Use FUN to change to transformation of microorganism codes
x <- bug_drug_combinations(example_isolates,
                           FUN = mo_gramstain)

x <- bug_drug_combinations(example_isolates,
                           FUN = function(x) ifelse(x == "B_ESCHR_COLI",
                                                    "E. coli",
                                                    "Others"))
# }