# ==================================================================== # # TITLE # # Antimicrobial Resistance (AMR) Analysis for R # # # # SOURCE # # https://github.com/msberends/AMR # # # # LICENCE # # (c) 2018-2021 Berends MS, Luz CF et al. # # Developed at the University of Groningen, the Netherlands, in # # collaboration with non-profit organisations Certe Medical # # Diagnostics & Advice, and University Medical Center Groningen. # # # # 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 the full manual and a complete tutorial about # # how to conduct AMR analysis: https://msberends.github.io/AMR/ # # ==================================================================== # #' Antibiotic class selectors #' #' These functions 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.) in the [antibiotics] data set. This means that a selector like e.g. [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. #' @rdname antibiotic_class_selectors #' @seealso [filter_ab_class()] for the `filter()` equivalent. #' @name antibiotic_class_selectors #' @export #' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @examples #' # `example_isolates` is a dataset available in the AMR package. #' # See ?example_isolates. #' #' # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem): #' example_isolates[, c(carbapenems())] #' # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB': #' example_isolates[, c("mo", aminoglycosides())] #' #' 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_is_gram_positive()) %>% #' select(mo, macrolides()) %>% #' bug_drug_combinations() %>% #' format() #' #' #' data.frame(some_column = "some_value", #' J01CA01 = "S") %>% # ATC code of ampicillin #' select(penicillins()) # only the 'J01CA01' column will be selected #' #' #' # with dplyr 1.0.0 and higher (that adds 'across()'), this is equal: #' # (though the row names on the first are more correct) #' example_isolates %>% filter_carbapenems("R", "all") #' example_isolates %>% filter(across(carbapenems(), ~. == "R")) #' } 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) { meet_criteria(ab_class, allow_class = "character", has_length = 1, .call_depth = 1) meet_criteria(function_name, allow_class = "character", has_length = 1, .call_depth = 1) for (i in seq_len(length(sys.frames()))) { # dplyr? if (".data" %in% names(sys.frames()[[i]])) { vars_df <- sys.frames()[[i]]$`.data` if (is.data.frame(vars_df)) { break } } # then try base R - an element `x` will be in the system call stack vars_df <- tryCatch(sys.frames()[[i]]$x, error = function(e) NULL) if (!is.null(vars_df) && is.data.frame(vars_df)) { # when using e.g. example_isolates[, carbapenems()] or example_isolates %>% select(carbapenems()) break } else if (!is.null(vars_df) && is.list(vars_df)) { # when using e.g. example_isolates %>% filter(across(carbapenems(), ~. == "R")) vars_df <- tryCatch(as.data.frame(vars_df, stringsAsFactors = FALSE), error = function(e) NULL) if (!is.null(vars_df)) { break } } } stop_ifnot(is.data.frame(vars_df), "this function must be used inside dplyr selection verbs or within a data.frame call.", call = -2) ab_in_data <- get_column_abx(vars_df, info = FALSE) if (length(ab_in_data) == 0) { message_("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 (message_not_thrown_before(function_name)) { if (length(agents) == 0) { message_("No antimicrobial agents of class ", ab_group, " found", examples, ".") } else { message_("Selecting ", ab_group, ": ", paste(paste0("column '", font_bold(agents, collapse = NULL), "' (", ab_name(names(agents), tolower = TRUE, language = NULL), ")"), collapse = ", "), as_note = FALSE, extra_indent = nchar(paste0("Selecting ", ab_group, ": "))) } remember_thrown_message(function_name) } unname(agents) }