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469 lines
18 KiB
469 lines
18 KiB
# ==================================================================== # |
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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 filter and select columns with antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. \strong{\Sexpr{ifelse(getRversion() < "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 ab_class an antimicrobial class, such as `"carbapenems"`. The columns `group`, `atc_group1` and `atc_group2` of the [antibiotics] data set will be searched (case-insensitive) for this value. |
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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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#' @details \strong{\Sexpr{ifelse(getRversion() < "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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#' |
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#' These functions can be used in data set calls for selecting columns and filtering rows, see *Examples*. They support base R, but work more convenient in dplyr functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()]. |
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#' |
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#' All columns in the data in which these functions are called 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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#' |
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#' The group of betalactams consists of all carbapenems, cephalosporins and penicillins. |
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#' @rdname antibiotic_class_selectors |
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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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#' # Base R ------------------------------------------------------------------ |
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#' |
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#' # select columns 'IPM' (imipenem) and 'MEM' (meropenem) |
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#' example_isolates[, carbapenems()] |
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#' |
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#' # 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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#' # filter using any() or all() |
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#' example_isolates[any(carbapenems() == "R"), ] |
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#' subset(example_isolates, any(carbapenems() == "R")) |
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#' |
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#' # filter on any or all results in the carbapenem columns (i.e., IPM, MEM): |
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#' example_isolates[any(carbapenems()), ] |
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#' example_isolates[all(carbapenems()), ] |
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#' |
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#' # filter with multiple antibiotic selectors using c() |
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#' example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ] |
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#' |
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#' # filter + select in one go: get penicillins in carbapenems-resistant strains |
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#' example_isolates[any(carbapenems() == "R"), penicillins()] |
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#' |
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#' |
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#' # dplyr ------------------------------------------------------------------- |
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#' \donttest{ |
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#' if (require("dplyr")) { |
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#' |
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#' # get AMR for all aminoglycosides e.g., per hospital: |
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#' example_isolates %>% |
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#' group_by(hospital_id) %>% |
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#' summarise(across(aminoglycosides(), resistance)) |
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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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#' # any() and all() work in dplyr's filter() too: |
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#' example_isolates %>% |
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#' filter(any(aminoglycosides() == "R"), |
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#' all(cephalosporins_2nd() == "R")) |
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#' |
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#' # also works with c(): |
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#' example_isolates %>% |
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#' filter(any(c(carbapenems(), aminoglycosides()) == "R")) |
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#' |
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#' # not setting any/all will automatically apply all(): |
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#' example_isolates %>% |
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#' filter(aminoglycosides() == "R") |
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#' #> i Assuming a filter on all 4 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 all equal: |
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#' # (though the row names on the first are more correct) |
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#' example_isolates[carbapenems() == "R", ] |
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#' example_isolates %>% filter(carbapenems() == "R") |
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#' example_isolates %>% filter(across(carbapenems(), ~.x == "R")) |
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#' } |
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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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betalactams <- function(only_rsi_columns = FALSE) { |
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ab_selector("carbapenem|cephalosporin|penicillin", function_name = "betalactams", 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 (getRversion() < "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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# to improve speed, get_current_data() and get_column_abx() only run once when e.g. in a select or group call |
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vars_df <- get_current_data(arg_name = NA, call = -3) |
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ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns, sort = FALSE) |
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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$ab] |
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if (message_not_thrown_before(function_name)) { |
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if (length(agents) == 0) { |
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message_("No antimicrobial agents of class ", ab_group, " found", examples, ".") |
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} else { |
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agents_formatted <- paste0("'", font_bold(agents, collapse = NULL), "'") |
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agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL) |
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need_name <- tolower(gsub("[^a-zA-Z]", "", agents)) != tolower(gsub("[^a-zA-Z]", "", agents_names)) |
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agents_formatted[need_name] <- paste0(agents_formatted[need_name], |
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" (", agents_names[need_name], ")") |
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message_("For `", function_name, "(", ifelse(function_name == "ab_class", paste0("\"", ab_class, "\""), ""), ")` using ", |
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ifelse(length(agents) == 1, "column: ", "columns: "), |
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vector_and(agents_formatted, quotes = FALSE)) |
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} |
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remember_thrown_message(function_name) |
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} |
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if (!is.null(attributes(vars_df)$type) && |
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attributes(vars_df)$type %in% c("dplyr_cur_data_all", "base_R") && |
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!any(as.character(sys.calls()) %like% paste0("(across|if_any|if_all)\\((c\\()?[a-z(), ]*", function_name))) { |
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structure(unname(agents), |
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class = c("ab_selector", "character")) |
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} else { |
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# don't return with "ab_selector" class if method is a dplyr selector, |
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# dplyr::select() will complain: |
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# > Subscript has the wrong type `ab_selector`. |
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# > It must be numeric or character. |
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unname(agents) |
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} |
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} |
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#' @method c ab_selector |
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#' @export |
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#' @noRd |
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c.ab_selector <- function(...) { |
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structure(unlist(lapply(list(...), as.character)), |
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class = c("ab_selector", "character")) |
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} |
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all_any_ab_selector <- function(type, ..., na.rm = TRUE) { |
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cols_ab <- c(...) |
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result <- cols_ab[toupper(cols_ab) %in% c("R", "S", "I")] |
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if (length(result) == 0) { |
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message_("Filtering ", type, " of columns ", vector_and(font_bold(cols_ab, collapse = NULL), quotes = "'"), ' to contain value "R", "S" or "I"') |
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result <- c("R", "S", "I") |
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} |
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cols_ab <- cols_ab[!cols_ab %in% result] |
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df <- get_current_data(arg_name = NA, call = -3) |
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if (type == "all") { |
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scope_fn <- all |
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} else { |
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scope_fn <- any |
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} |
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x_transposed <- as.list(as.data.frame(t(df[, cols_ab, drop = FALSE]), stringsAsFactors = FALSE)) |
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vapply(FUN.VALUE = logical(1), |
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X = x_transposed, |
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FUN = function(y) scope_fn(y %in% result, na.rm = na.rm), |
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USE.NAMES = FALSE) |
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} |
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#' @method all ab_selector |
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#' @export |
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#' @noRd |
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all.ab_selector <- function(..., na.rm = FALSE) { |
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# this is all() for |
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all_any_ab_selector("all", ..., na.rm = na.rm) |
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} |
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#' @method any ab_selector |
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#' @export |
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#' @noRd |
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any.ab_selector <- function(..., na.rm = FALSE) { |
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all_any_ab_selector("any", ..., na.rm = na.rm) |
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} |
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#' @method all ab_selector_any_all |
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#' @export |
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#' @noRd |
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all.ab_selector_any_all <- function(..., na.rm = FALSE) { |
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# this is all() on a logical vector from `==.ab_selector` or `!=.ab_selector` |
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# e.g., example_isolates %>% filter(all(carbapenems() == "R")) |
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# so just return the vector as is, only correcting for na.rm |
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out <- unclass(c(...)) |
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if (na.rm == TRUE) { |
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out <- out[!is.na(out)] |
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} |
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out |
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} |
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#' @method any ab_selector_any_all |
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#' @export |
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#' @noRd |
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any.ab_selector_any_all <- function(..., na.rm = FALSE) { |
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# this is any() on a logical vector from `==.ab_selector` or `!=.ab_selector` |
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# e.g., example_isolates %>% filter(any(carbapenems() == "R")) |
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# so just return the vector as is, only correcting for na.rm |
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out <- unclass(c(...)) |
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if (na.rm == TRUE) { |
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out <- out[!is.na(out)] |
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} |
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out |
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} |
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#' @method == ab_selector |
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#' @export |
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#' @noRd |
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`==.ab_selector` <- function(e1, e2) { |
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calls <- as.character(match.call()) |
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fn_name <- calls[2] |
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# keep only the ... in c(...) |
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fn_name <- gsub("^(c\\()(.*)(\\))$", "\\2", fn_name) |
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if (is_any(fn_name)) { |
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type <- "any" |
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} else if (is_all(fn_name)) { |
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type <- "all" |
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} else { |
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type <- "all" |
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if (length(e1) > 1) { |
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message_("Assuming a filter on ", type, " ", length(e1), " ", gsub("[\\(\\)]", "", fn_name), |
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". Wrap around `all()` or `any()` to prevent this note.") |
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} |
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} |
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structure(all_any_ab_selector(type = type, e1, e2), |
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class = c("ab_selector_any_all", "logical")) |
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} |
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#' @method != ab_selector |
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#' @export |
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#' @noRd |
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`!=.ab_selector` <- function(e1, e2) { |
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calls <- as.character(match.call()) |
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fn_name <- calls[2] |
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# keep only the ... in c(...) |
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fn_name <- gsub("^(c\\()(.*)(\\))$", "\\2", fn_name) |
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if (is_any(fn_name)) { |
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type <- "any" |
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} else if (is_all(fn_name)) { |
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type <- "all" |
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} else { |
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type <- "all" |
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if (length(e1) > 1) { |
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message_("Assuming a filter on ", type, " ", length(e1), " ", gsub("[\\(\\)]", "", fn_name), |
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". Wrap around `all()` or `any()` to prevent this note.") |
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} |
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} |
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# this is `!=`, so turn around the values |
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rsi <- c("R", "S", "I") |
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e2 <- rsi[rsi != e2] |
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structure(all_any_ab_selector(type = type, e1, e2), |
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class = c("ab_selector_any_all", "logical")) |
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} |
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is_any <- function(el1) { |
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syscall <- paste0(trimws(deparse(sys.calls()[[1]])), collapse = " ") |
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el1 <- gsub("(.*),.*", "\\1", el1) |
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syscall %like% paste0("[^_a-zA-Z0-9]any\\(", "(c\\()?", el1) |
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} |
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is_all <- function(el1) { |
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syscall <- paste0(trimws(deparse(sys.calls()[[1]])), collapse = " ") |
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el1 <- gsub("(.*),.*", "\\1", el1) |
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syscall %like% paste0("[^_a-zA-Z0-9]all\\(", "(c\\()?", el1) |
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} |
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find_ab_group <- function(ab_class) { |
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ab_class[ab_class == "carbapenem|cephalosporin|penicillin"] <- "betalactam" |
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ab_class <- gsub("[^a-zA-Z0-9]", ".*", ab_class) |
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ifelse(ab_class %in% c("aminoglycoside", |
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"betalactam", |
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"carbapenem", |
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"cephalosporin", |
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"fluoroquinolone", |
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"glycopeptide", |
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"macrolide", |
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"oxazolidinone", |
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"tetracycline"), |
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paste0(ab_class, "s"), |
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antibiotics %pm>% |
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subset(group %like% ab_class | |
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atc_group1 %like% ab_class | |
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atc_group2 %like% ab_class) %pm>% |
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pm_pull(group) %pm>% |
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unique() %pm>% |
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tolower() %pm>% |
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sort() %pm>% |
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paste(collapse = "/") |
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) |
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} |
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find_ab_names <- function(ab_group, n = 3) { |
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ab_group <- gsub("[^a-zA-Z|0-9]", ".*", ab_group) |
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# try popular first, they have DDDs |
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drugs <- antibiotics[which((!is.na(antibiotics$iv_ddd) | !is.na(antibiotics$oral_ddd)) & |
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antibiotics$name %unlike% " " & |
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antibiotics$group %like% ab_group & |
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antibiotics$ab %unlike% "[0-9]$"), ]$name |
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if (length(drugs) < n) { |
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# now try it all |
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drugs <- antibiotics[which((antibiotics$group %like% ab_group | |
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antibiotics$atc_group1 %like% ab_group | |
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antibiotics$atc_group2 %like% ab_group) & |
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antibiotics$ab %unlike% "[0-9]$"), ]$name |
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} |
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vector_or(ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE), |
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tolower = TRUE, |
|
language = NULL), |
|
quotes = FALSE) |
|
}
|
|
|