# ==================================================================== # # TITLE # # Antimicrobial Resistance (AMR) Analysis # # # # SOURCE # # https://gitlab.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.gitlab.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 #' @examples #' if (require("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) }