mirror of https://github.com/msberends/AMR.git
234 lines
10 KiB
R
234 lines
10 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Data Analysis for R #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2021 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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#' Antibiotic Class Selectors
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#'
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#' 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. \strong{\Sexpr{ifelse(as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2, paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
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#' @inheritSection lifecycle Stable Lifecycle
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#' @param only_rsi_columns a logical to indicate whether only columns of class `<rsi>` must be selected (defaults to `FALSE`), see [as.rsi()]
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#' @inheritParams filter_ab_class
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#' @details \strong{\Sexpr{ifelse(as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2, paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
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#'
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#' 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.
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#' @rdname antibiotic_class_selectors
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#' @seealso [filter_ab_class()] for the `filter()` equivalent.
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#' @name antibiotic_class_selectors
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#' @export
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#' @inheritSection AMR Reference Data Publicly Available
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#' @inheritSection AMR Read more on Our Website!
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#' @examples
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#' # `example_isolates` is a data set available in the AMR package.
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#' # See ?example_isolates.
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#'
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#' # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
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#' example_isolates[, carbapenems()]
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#' # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
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#' example_isolates[, c("mo", aminoglycosides())]
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#'
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#' if (require("dplyr")) {
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#'
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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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#'
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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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#'
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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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#'
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#'
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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_is_gram_positive()) %>%
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#' select(mo, macrolides()) %>%
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#' bug_drug_combinations() %>%
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#' format()
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#'
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#'
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#' data.frame(some_column = "some_value",
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#' J01CA01 = "S") %>% # ATC code of ampicillin
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#' select(penicillins()) # only the 'J01CA01' column will be selected
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#'
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#'
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#' # with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:
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#' # (though the row names on the first are more correct)
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#' example_isolates %>% filter_carbapenems("R", "all")
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#' example_isolates %>% filter(across(carbapenems(), ~. == "R"))
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#' }
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ab_class <- function(ab_class,
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only_rsi_columns = FALSE) {
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ab_selector(ab_class, function_name = "ab_class", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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aminoglycosides <- function(only_rsi_columns = FALSE) {
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ab_selector("aminoglycoside", function_name = "aminoglycosides", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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carbapenems <- function(only_rsi_columns = FALSE) {
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ab_selector("carbapenem", function_name = "carbapenems", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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cephalosporins <- function(only_rsi_columns = FALSE) {
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ab_selector("cephalosporin", function_name = "cephalosporins", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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cephalosporins_1st <- function(only_rsi_columns = FALSE) {
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ab_selector("cephalosporins.*1", function_name = "cephalosporins_1st", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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cephalosporins_2nd <- function(only_rsi_columns = FALSE) {
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ab_selector("cephalosporins.*2", function_name = "cephalosporins_2nd", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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cephalosporins_3rd <- function(only_rsi_columns = FALSE) {
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ab_selector("cephalosporins.*3", function_name = "cephalosporins_3rd", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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cephalosporins_4th <- function(only_rsi_columns = FALSE) {
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ab_selector("cephalosporins.*4", function_name = "cephalosporins_4th", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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cephalosporins_5th <- function(only_rsi_columns = FALSE) {
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ab_selector("cephalosporins.*5", function_name = "cephalosporins_5th", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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fluoroquinolones <- function(only_rsi_columns = FALSE) {
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ab_selector("fluoroquinolone", function_name = "fluoroquinolones", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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glycopeptides <- function(only_rsi_columns = FALSE) {
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ab_selector("glycopeptide", function_name = "glycopeptides", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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macrolides <- function(only_rsi_columns = FALSE) {
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ab_selector("macrolide", function_name = "macrolides", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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oxazolidinones <- function(only_rsi_columns = FALSE) {
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ab_selector("oxazolidinone", function_name = "oxazolidinones", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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penicillins <- function(only_rsi_columns = FALSE) {
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ab_selector("penicillin", function_name = "penicillins", only_rsi_columns = only_rsi_columns)
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}
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#' @rdname antibiotic_class_selectors
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#' @export
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tetracyclines <- function(only_rsi_columns = FALSE) {
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ab_selector("tetracycline", function_name = "tetracyclines", only_rsi_columns = only_rsi_columns)
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}
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ab_selector <- function(ab_class,
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function_name,
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only_rsi_columns) {
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meet_criteria(ab_class, allow_class = "character", has_length = 1, .call_depth = 1)
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meet_criteria(function_name, allow_class = "character", has_length = 1, .call_depth = 1)
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meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1, .call_depth = 1)
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if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2) {
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warning_("antibiotic class selectors such as ", function_name,
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"() require R version 3.2 or later - you have ", R.version.string,
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call = FALSE)
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return(NULL)
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}
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vars_df <- get_current_data(arg_name = NA, call = -3)
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# improve speed here so it will only run once when e.g. in one select call
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if (!identical(pkg_env$ab_selector, unique_call_id())) {
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ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns)
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pkg_env$ab_selector <- unique_call_id()
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pkg_env$ab_selector_cols <- ab_in_data
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} else {
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ab_in_data <- pkg_env$ab_selector_cols
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}
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if (length(ab_in_data) == 0) {
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message_("No antimicrobial agents found.")
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return(NULL)
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}
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ab_reference <- subset(antibiotics,
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group %like% ab_class |
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atc_group1 %like% ab_class |
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atc_group2 %like% ab_class)
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ab_group <- find_ab_group(ab_class)
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if (ab_group == "") {
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ab_group <- paste0("'", ab_class, "'")
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examples <- ""
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} else {
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examples <- paste0(" (such as ", find_ab_names(ab_class, 2), ")")
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}
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# get the columns with a group names in the chosen ab class
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agents <- ab_in_data[names(ab_in_data) %in% ab_reference$ab]
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if (message_not_thrown_before(function_name)) {
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if (length(agents) == 0) {
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message_("No antimicrobial agents of class ", ab_group, " found", examples, ".")
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} else {
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agents_formatted <- paste0("'", font_bold(agents, collapse = NULL), "'")
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agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL)
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need_name <- tolower(gsub("[^a-zA-Z]", "", agents)) != tolower(gsub("[^a-zA-Z]", "", agents_names))
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agents_formatted[need_name] <- paste0(agents_formatted[need_name],
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" (", agents_names[need_name], ")")
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message_("Selecting ", ab_group, ": ",
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ifelse(length(agents) == 1, "column ", "columns "),
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vector_and(agents_formatted, quotes = FALSE),
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as_note = FALSE,
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extra_indent = 6)
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}
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remember_thrown_message(function_name)
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}
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unname(agents)
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}
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