mirror of https://github.com/msberends/AMR.git
386 lines
14 KiB
R
386 lines
14 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) 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 analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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#' Filter isolates on result in antimicrobial class
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#'
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#' Filter isolates on results in specific antimicrobial classes. This makes it easy to filter on isolates that were tested for e.g. any aminoglycoside, or to filter on carbapenem-resistant isolates without the need to specify the drugs.
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#' @inheritSection lifecycle Stable lifecycle
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#' @param x a data set
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#' @param ab_class an antimicrobial class, like `"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 result an antibiotic result: S, I or R (or a combination of more of them)
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#' @param scope the scope to check which variables to check, can be `"any"` (default) or `"all"`
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#' @param ... previously used when this package still depended on the `dplyr` package, now ignored
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#' @details All columns of `x` will be searched for known antibiotic names, abbreviations, brand names and codes (ATC, EARS-Net, WHO, etc.). This means that a filter function like e.g. [filter_aminoglycosides()] will include column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
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#' @rdname filter_ab_class
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#' @seealso [antibiotic_class_selectors()] for the `select()` equivalent.
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#' @export
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#' @examples
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#' filter_aminoglycosides(example_isolates)
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#'
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#' \donttest{
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#' if (require("dplyr")) {
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#'
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#' # filter on isolates that have any result for any aminoglycoside
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#' example_isolates %>% filter_aminoglycosides()
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#' example_isolates %>% filter_ab_class("aminoglycoside")
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#'
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#' # this is essentially the same as (but without determination of column names):
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#' example_isolates %>%
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#' filter_at(.vars = vars(c("GEN", "TOB", "AMK", "KAN")),
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#' .vars_predicate = any_vars(. %in% c("S", "I", "R")))
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#'
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#'
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#' # filter on isolates that show resistance to ANY aminoglycoside
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#' example_isolates %>% filter_aminoglycosides("R", "any")
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#'
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#' # filter on isolates that show resistance to ALL aminoglycosides
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#' example_isolates %>% filter_aminoglycosides("R", "all")
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#'
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#' # filter on isolates that show resistance to
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#' # any aminoglycoside and any fluoroquinolone
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#' example_isolates %>%
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#' filter_aminoglycosides("R") %>%
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#' filter_fluoroquinolones("R")
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#'
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#' # filter on isolates that show resistance to
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#' # all aminoglycosides and all fluoroquinolones
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#' example_isolates %>%
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#' filter_aminoglycosides("R", "all") %>%
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#' filter_fluoroquinolones("R", "all")
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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 %>% filter_carbapenems("R", "all")
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#' example_isolates %>% filter(across(carbapenems(), ~. == "R"))
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#' example_isolates %>% filter(across(carbapenems(), function(x) x == "R"))
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#' }
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#' }
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filter_ab_class <- function(x,
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ab_class,
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result = NULL,
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scope = "any",
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...) {
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.call_depth <- list(...)$`.call_depth`
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if (is.null(.call_depth)) {
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.call_depth <- 0
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}
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meet_criteria(x, allow_class = "data.frame", .call_depth = .call_depth)
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meet_criteria(ab_class, allow_class = "character", has_length = 1, .call_depth = .call_depth)
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meet_criteria(result, allow_class = "character", has_length = c(1, 2, 3), allow_NULL = TRUE, .call_depth = .call_depth)
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meet_criteria(scope, allow_class = "character", has_length = 1, is_in = c("all", "any"), .call_depth = .call_depth)
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check_dataset_integrity()
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# save to return later
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x_class <- class(x)
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x.bak <- x
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x <- as.data.frame(x, stringsAsFactors = FALSE)
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if (is.null(result)) {
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result <- c("S", "I", "R")
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}
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# make result = "SI" works too:
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result <- unlist(strsplit(result, ""))
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stop_ifnot(all(result %in% c("S", "I", "R")), "`result` must be one or more of: 'S', 'I', 'R'")
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stop_ifnot(all(scope %in% c("any", "all")), "`scope` must be one of: 'any', 'all'")
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# get all columns in data with names that resemble antibiotics
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ab_in_data <- get_column_abx(x, info = FALSE)
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if (length(ab_in_data) == 0) {
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message_("No columns with class <rsi> found (see ?as.rsi), data left unchanged.")
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return(x.bak)
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}
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# get reference data
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ab_class.bak <- ab_class
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ab_class <- gsub("[^a-zA-Z0-9]+", ".*", ab_class)
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ab_class <- gsub("(ph|f)", "(ph|f)", ab_class)
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ab_class <- gsub("(t|th)", "(t|th)", ab_class)
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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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message_("Unknown antimicrobial class '", ab_class.bak, "', data left unchanged.")
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return(x.bak)
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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 (length(agents) == 0) {
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message_("no antimicrobial agents of class ", ab_group,
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" found (such as ", find_ab_names(ab_class, 2),
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"), data left unchanged.")
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return(x.bak)
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}
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if (length(result) == 1) {
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operator <- " is "
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} else {
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operator <- " is one of "
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}
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if (scope == "any") {
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scope_txt <- " or "
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scope_fn <- any
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} else {
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scope_txt <- " and "
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scope_fn <- all
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if (length(agents) > 1) {
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operator <- gsub("is", "are", operator)
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}
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}
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if (length(agents) > 1) {
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scope <- paste(scope, "of columns ")
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} else {
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scope <- "column "
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}
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# sort columns on official name
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agents <- agents[order(ab_name(names(agents), language = NULL))]
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message_("Filtering on ", ab_group, ": ", scope,
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paste(paste0("`", font_bold(agents, collapse = NULL),
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"` (", ab_name(names(agents), tolower = TRUE, language = NULL), ")"),
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collapse = scope_txt),
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operator, toString(result), as_note = FALSE)
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x_transposed <- as.list(as.data.frame(t(x[, agents, drop = FALSE]), stringsAsFactors = FALSE))
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filtered <- vapply(FUN.VALUE = logical(1), x_transposed, function(y) scope_fn(y %in% result, na.rm = TRUE))
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x <- x[which(filtered), , drop = FALSE]
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class(x) <- x_class
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x
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}
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#' @rdname filter_ab_class
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#' @export
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filter_aminoglycosides <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "aminoglycoside",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_carbapenems <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "carbapenem",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_cephalosporins <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "cephalosporin",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_1st_cephalosporins <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "cephalosporins (1st gen.)",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_2nd_cephalosporins <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "cephalosporins (2nd gen.)",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_3rd_cephalosporins <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "cephalosporins (3rd gen.)",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_4th_cephalosporins <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "cephalosporins (4th gen.)",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_5th_cephalosporins <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "cephalosporins (5th gen.)",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_fluoroquinolones <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "fluoroquinolone",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_glycopeptides <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "glycopeptide",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_macrolides <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "macrolide",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_penicillins <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "penicillin",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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#' @rdname filter_ab_class
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#' @export
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filter_tetracyclines <- function(x,
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result = NULL,
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scope = "any",
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...) {
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filter_ab_class(x = x,
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ab_class = "tetracycline",
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result = result,
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scope = scope,
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.call_depth = 1,
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...)
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}
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find_ab_group <- function(ab_class) {
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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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"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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"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-Z0-9]", ".*", ab_group)
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drugs <- antibiotics[which(antibiotics$group %like% ab_group & !antibiotics$ab %like% "[0-9]$"), ]$name
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paste0(sort(ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE),
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tolower = TRUE, language = NULL)),
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collapse = ", ")
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}
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