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99 lines
3.5 KiB
R
99 lines
3.5 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/ab_class_selectors.R
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\name{antibiotic_class_selectors}
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\alias{antibiotic_class_selectors}
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\alias{ab_class}
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\alias{aminoglycosides}
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\alias{carbapenems}
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\alias{cephalosporins}
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\alias{cephalosporins_1st}
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\alias{cephalosporins_2nd}
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\alias{cephalosporins_3rd}
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\alias{cephalosporins_4th}
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\alias{cephalosporins_5th}
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\alias{fluoroquinolones}
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\alias{glycopeptides}
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\alias{macrolides}
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\alias{penicillins}
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\alias{tetracyclines}
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\title{Antibiotic class selectors}
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\usage{
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ab_class(ab_class)
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aminoglycosides()
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carbapenems()
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cephalosporins()
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cephalosporins_1st()
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cephalosporins_2nd()
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cephalosporins_3rd()
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cephalosporins_4th()
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cephalosporins_5th()
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fluoroquinolones()
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glycopeptides()
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macrolides()
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penicillins()
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tetracyclines()
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}
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\arguments{
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\item{ab_class}{an antimicrobial class, like \code{"carbapenems"}. The columns \code{group}, \code{atc_group1} and \code{atc_group2} of the \link{antibiotics} data set will be searched (case-insensitive) for this value.}
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}
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\description{
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Use these selection helpers inside any function that allows \href{https://tidyselect.r-lib.org/reference/language.html}{Tidyverse selections}, like \code{dplyr::select()} or \code{tidyr::pivot_longer()}. They help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
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}
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\details{
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All columns will be searched for known antibiotic names, abbreviations, brand names and codes (ATC, EARS-Net, WHO, etc.). This means that a selector like e.g. \code{\link[=aminoglycosides]{aminoglycosides()}} will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
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These functions only work if the \code{tidyselect} package is installed, that comes with the \code{dplyr} package. An error will be thrown if \code{tidyselect} package is not installed, or if the functions are used outside a function that allows Tidyverse selections like \code{select()} or \code{pivot_longer()}.
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}
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\section{Read more on our website!}{
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On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
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}
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\examples{
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\dontrun{
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library(dplyr)
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# this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
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example_isolates \%>\%
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select(carbapenems())
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# this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
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example_isolates \%>\%
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select(mo, aminoglycosides())
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# this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
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example_isolates \%>\%
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select(mo, ab_class("mycobact"))
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# get bug/drug combinations for only macrolides in Gram-positives:
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example_isolates \%>\%
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filter(mo_gramstain(mo) \%like\% "pos") \%>\%
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select(mo, macrolides()) \%>\%
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bug_drug_combinations() \%>\%
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format()
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data.frame(irrelevant = "value",
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J01CA01 = "S") \%>\% # ATC code of ampicillin
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select(penicillins()) # so the 'J01CA01' column is selected
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}
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}
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\seealso{
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\code{\link[=filter_ab_class]{filter_ab_class()}} for the \code{filter()} equivalent.
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}
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