mirror of https://github.com/msberends/AMR.git
173 lines
7.9 KiB
R
Executable File
173 lines
7.9 KiB
R
Executable File
# ==================================================================== #
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# TITLE #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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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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# CITE AS #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
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# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
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# Data. Journal of Statistical Software, 104(3), 1-31. #
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# doi:10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen and the University Medical #
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# Center Groningen in The Netherlands, in collaboration with many #
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# colleagues from around the world, see our website. #
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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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#' Add Custom Antimicrobials
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#'
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#' With [add_custom_antimicrobials()] you can add your own custom antimicrobial drug names and codes.
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#' @param x a [data.frame] resembling the [antibiotics] data set, at least containing columns "ab" and "name"
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#' @details **Important:** Due to how \R works, the [add_custom_antimicrobials()] function has to be run in every \R session - added antimicrobials are not stored between sessions and are thus lost when \R is exited.
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#'
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#' There are two ways to circumvent this and automate the process of adding antimicrobials:
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#'
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#' **Method 1:** Using the [package option][AMR-options] [`AMR_custom_ab`][AMR-options], which is the preferred method. To use this method:
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#'
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#' 1. Create a data set in the structure of the [antibiotics] data set (containing at the very least columns "ab" and "name") and save it with [saveRDS()] to a location of choice, e.g. `"~/my_custom_ab.rds"`, or any remote location.
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#'
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#' 2. Set the file location to the [package option][AMR-options] [`AMR_custom_ab`][AMR-options]: `options(AMR_custom_ab = "~/my_custom_ab.rds")`. This can even be a remote file location, such as an https URL. Since options are not saved between \R sessions, it is best to save this option to the `.Rprofile` file so that it will be loaded on start-up of \R. To do this, open the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`, add this text and save the file:
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#'
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#' ```r
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#' # Add custom antimicrobial codes:
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#' options(AMR_custom_ab = "~/my_custom_ab.rds")
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#' ```
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#'
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#' Upon package load, this file will be loaded and run through the [add_custom_antimicrobials()] function.
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#'
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#' **Method 2:** Loading the antimicrobial additions directly from your `.Rprofile` file. Note that the definitions will be stored in a user-specific \R file, which is a suboptimal workflow. To use this method:
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#'
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#' 1. Edit the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`.
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#'
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#' 2. Add a text like below and save the file:
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#'
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#' ```r
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#' # Add custom antibiotic drug codes:
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#' AMR::add_custom_antimicrobials(
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#' data.frame(ab = "TESTAB",
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#' name = "Test Antibiotic",
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#' group = "Test Group")
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#' )
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#' ```
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#'
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#' Use [clear_custom_antimicrobials()] to clear the previously added antimicrobials.
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#' @seealso [add_custom_microorganisms()] to add custom microorganisms.
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#' @rdname add_custom_antimicrobials
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#' @export
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#' @examples
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#' \donttest{
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#'
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#' # returns NA and throws a warning (which is suppressed here):
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#' suppressWarnings(
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#' as.ab("testab")
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#' )
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#'
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#' # now add a custom entry - it will be considered by as.ab() and
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#' # all ab_*() functions
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#' add_custom_antimicrobials(
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#' data.frame(
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#' ab = "TESTAB",
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#' name = "Test Antibiotic",
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#' # you can add any property present in the
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#' # 'antibiotics' data set, such as 'group':
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#' group = "Test Group"
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#' )
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#' )
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#'
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#' # "testab" is now a new antibiotic:
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#' as.ab("testab")
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#' ab_name("testab")
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#' ab_group("testab")
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#'
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#' ab_info("testab")
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#'
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#'
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#' # Add Co-fluampicil, which is one of the many J01CR50 codes, see
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#' # https://www.whocc.no/ddd/list_of_ddds_combined_products/
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#' add_custom_antimicrobials(
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#' data.frame(
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#' ab = "COFLU",
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#' name = "Co-fluampicil",
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#' atc = "J01CR50",
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#' group = "Beta-lactams/penicillins"
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#' )
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#' )
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#' ab_atc("Co-fluampicil")
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#' ab_name("J01CR50")
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#'
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#' # even antibiotic selectors work
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#' x <- data.frame(
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#' random_column = "some value",
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#' coflu = as.sir("S"),
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#' ampicillin = as.sir("R")
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#' )
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#' x
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#' x[, betalactams()]
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#' }
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add_custom_antimicrobials <- function(x) {
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meet_criteria(x, allow_class = "data.frame")
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stop_ifnot(
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all(c("ab", "name") %in% colnames(x)),
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"`x` must contain columns \"ab\" and \"name\"."
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)
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stop_if(
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any(x$ab %in% AMR_env$AB_lookup$ab),
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"Antimicrobial drug code(s) ", vector_and(x$ab[x$ab %in% AMR_env$AB_lookup$ab]), " already exist in the internal `antibiotics` data set."
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)
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# remove any extra class/type, such as grouped tbl, or data.table:
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x <- as.data.frame(x, stringsAsFactors = FALSE)
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# keep only columns available in the antibiotics data set
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x <- x[, colnames(AMR_env$AB_lookup)[colnames(AMR_env$AB_lookup) %in% colnames(x)], drop = FALSE]
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x$generalised_name <- generalise_antibiotic_name(x$name)
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x$generalised_all <- as.list(x$generalised_name)
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for (col in colnames(x)) {
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if (is.list(AMR_env$AB_lookup[, col, drop = TRUE]) & !is.list(x[, col, drop = TRUE])) {
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x[, col] <- as.list(x[, col, drop = TRUE])
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}
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}
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AMR_env$custom_ab_codes <- c(AMR_env$custom_ab_codes, x$ab)
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class(AMR_env$AB_lookup$ab) <- "character"
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new_df <- AMR_env$AB_lookup[0, , drop = FALSE][seq_len(NROW(x)), , drop = FALSE]
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rownames(new_df) <- NULL
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list_cols <- vapply(FUN.VALUE = logical(1), new_df, is.list)
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for (l in which(list_cols)) {
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# prevent binding NULLs in lists, replace with NA
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new_df[, l] <- as.list(NA_character_)
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}
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for (col in colnames(x)) {
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# assign new values
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new_df[, col] <- x[, col, drop = TRUE]
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}
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AMR_env$AB_lookup <- unique(rbind_AMR(AMR_env$AB_lookup, new_df))
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AMR_env$ab_previously_coerced <- AMR_env$ab_previously_coerced[which(!AMR_env$ab_previously_coerced$ab %in% x$ab), , drop = FALSE]
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class(AMR_env$AB_lookup$ab) <- c("ab", "character")
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message_("Added ", nr2char(nrow(x)), " record", ifelse(nrow(x) > 1, "s", ""), " to the internal `antibiotics` data set.")
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}
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#' @rdname add_custom_antimicrobials
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#' @export
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clear_custom_antimicrobials <- function() {
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n <- nrow(AMR_env$AB_lookup)
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AMR_env$AB_lookup <- cbind(AMR::antibiotics, AB_LOOKUP)
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n2 <- nrow(AMR_env$AB_lookup)
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AMR_env$custom_ab_codes <- character(0)
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AMR_env$ab_previously_coerced <- AMR_env$ab_previously_coerced[which(AMR_env$ab_previously_coerced$ab %in% AMR_env$AB_lookup$ab), , drop = FALSE]
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message_("Cleared ", nr2char(n - n2), " custom record", ifelse(n - n2 > 1, "s", ""), " from the internal `antibiotics` data set.")
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}
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