AMR/R/ab_class_selectors.R

182 lines
6.9 KiB
R

# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2020 Berends MS, Luz CF et al. #
# #
# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
# Visit our website for more info: https://msberends.github.io/AMR. #
# ==================================================================== #
#' Antibiotic class selectors
#'
#' Use these selection helpers inside any function that allows [Tidyverse selections](https://tidyselect.r-lib.org/reference/language.html), like `dplyr::select()` or `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.
#' @inheritParams filter_ab_class
#' @details 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. [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
#'
#' These functions only work if the `tidyselect` package is installed, that comes with the `dplyr` package. An error will be thrown if `tidyselect` package is not installed, or if the functions are used outside a function that allows Tidyverse selections like `select()` or `pivot_longer()`.
#' @rdname antibiotic_class_selectors
#' @seealso [filter_ab_class()] for the `filter()` equivalent.
#' @name antibiotic_class_selectors
#' @export
#' @inheritSection AMR Read more on our website!
#' @examples
#' \dontrun{
#' library(dplyr)
#'
#' # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
#' example_isolates %>%
#' select(carbapenems())
#'
#' # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
#' example_isolates %>%
#' select(mo, aminoglycosides())
#'
#' # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
#' example_isolates %>%
#' select(mo, ab_class("mycobact"))
#'
#'
#' # get bug/drug combinations for only macrolides in Gram-positives:
#' example_isolates %>%
#' filter(mo_gramstain(mo) %like% "pos") %>%
#' select(mo, macrolides()) %>%
#' bug_drug_combinations() %>%
#' format()
#'
#'
#' data.frame(irrelevant = "value",
#' J01CA01 = "S") %>% # ATC code of ampicillin
#' select(penicillins()) # so the 'J01CA01' column is selected
#'
#' }
ab_class <- function(ab_class) {
ab_selector(ab_class, function_name = "ab_class")
}
#' @rdname antibiotic_class_selectors
#' @export
aminoglycosides <- function() {
ab_selector("aminoglycoside", function_name = "aminoglycosides")
}
#' @rdname antibiotic_class_selectors
#' @export
carbapenems <- function() {
ab_selector("carbapenem", function_name = "carbapenems")
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins <- function() {
ab_selector("cephalosporin", function_name = "cephalosporins")
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_1st <- function() {
ab_selector("cephalosporins.*1", function_name = "cephalosporins_1st")
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_2nd <- function() {
ab_selector("cephalosporins.*2", function_name = "cephalosporins_2nd")
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_3rd <- function() {
ab_selector("cephalosporins.*3", function_name = "cephalosporins_3rd")
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_4th <- function() {
ab_selector("cephalosporins.*4", function_name = "cephalosporins_4th")
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_5th <- function() {
ab_selector("cephalosporins.*5", function_name = "cephalosporins_5th")
}
#' @rdname antibiotic_class_selectors
#' @export
fluoroquinolones <- function() {
ab_selector("fluoroquinolone", function_name = "fluoroquinolones")
}
#' @rdname antibiotic_class_selectors
#' @export
glycopeptides <- function() {
ab_selector("glycopeptide", function_name = "glycopeptides")
}
#' @rdname antibiotic_class_selectors
#' @export
macrolides <- function() {
ab_selector("macrolide", function_name = "macrolides")
}
#' @rdname antibiotic_class_selectors
#' @export
penicillins <- function() {
ab_selector("penicillin", function_name = "penicillins")
}
#' @rdname antibiotic_class_selectors
#' @export
tetracyclines <- function() {
ab_selector("tetracycline", function_name = "tetracyclines")
}
ab_selector <- function(ab_class, function_name) {
peek_vars_tidyselect <- import_fn("peek_vars", "tidyselect")
vars_vct <- peek_vars_tidyselect(fn = function_name)
vars_df <- data.frame(as.list(vars_vct))[0, , drop = FALSE]
colnames(vars_df) <- vars_vct
ab_in_data <- suppressMessages(get_column_abx(vars_df))
if (length(ab_in_data) == 0) {
message(font_blue("NOTE: no antimicrobial agents found."))
return(NULL)
}
ab_reference <- subset(antibiotics,
group %like% ab_class |
atc_group1 %like% ab_class |
atc_group2 %like% ab_class)
ab_group <- find_ab_group(ab_class)
if (ab_group == "") {
ab_group <- paste0("'", ab_class, "'")
examples <- ""
} else {
examples <- paste0(" (such as ", find_ab_names(ab_class, 2), ")")
}
# get the columns with a group names in the chosen ab class
agents <- ab_in_data[names(ab_in_data) %in% ab_reference$ab]
if (length(agents) == 0) {
message(font_blue(paste0("NOTE: No antimicrobial agents of class ", ab_group,
" found", examples, ".")))
} else {
message(font_blue(paste0("Selecting ", ab_group, ": ",
paste(paste0("`", font_bold(agents, collapse = NULL),
"` (", ab_name(names(agents), tolower = TRUE, language = NULL), ")"),
collapse = ", "))))
}
unname(agents)
}