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# ==================================================================== #
# TITLE #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# CITE AS #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. #
# doi:10.18637/jss.v104.i03 #
# #
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# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
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# #
# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
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#' Add Custom Antimicrobials to This Package
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#'
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#' With [add_custom_antimicrobials()] you can add your own custom antimicrobial drug codes to the `AMR` package.
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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.
#'
#' There are two ways to automate this process:
#'
#' **Method 1:** Save the antimicrobials to a local or remote file (can even be the internet). To use this method:
#'
#' 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.
#'
#' 2. Set the file location to the `AMR_custom_ab` \R option: `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 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
#' # Add custom antibiotic drug codes:
#' options(AMR_custom_ab = "~/my_custom_ab.rds")
#' ```
#'
#' Upon package load, this file will be loaded and run through the [add_custom_antimicrobials()] function.
#'
#' **Method 2:** Save the antimicrobial additions directly to your `.Rprofile` file. An important downside is that this requires to load the `AMR` package at every start-up. To use this method:
#'
#' 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:
#'
#' ```r
#' # Add custom antibiotic drug codes:
#' library(AMR)
#' add_custom_antimicrobials(
#' data.frame(ab = "TESTAB",
#' name = "Test Antibiotic",
#' group = "Test Group")
#' )
#' ```
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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 to this package.
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#' @rdname add_custom_antimicrobials
#' @export
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#' @examples
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#' \donttest{
#'
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#' # returns NA and throws a warning (which is now suppressed):
#' 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
#' add_custom_antimicrobials(
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#' data.frame(
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#' ab = "TESTAB",
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#' name = "Test Antibiotic",
#' # you can add any property present in the
#' # 'antibiotics' data set, such as 'group':
#' group = "Test Group"
#' )
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#' )
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#'
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#' # "testab" is now a new antibiotic:
#' as.ab("testab")
#' ab_name("testab")
#' ab_group("testab")
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#'
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#' ab_info("testab")
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#'
#'
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#' # Add Co-fluampicil, which is one of the many J01CR50 codes, see
#' # https://www.whocc.no/ddd/list_of_ddds_combined_products/
#' add_custom_antimicrobials(
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#' data.frame(
#' ab = "COFLU",
#' name = "Co-fluampicil",
#' atc = "J01CR50",
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#' group = "Beta-lactams/penicillins"
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#' )
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#' )
#' ab_atc("Co-fluampicil")
#' 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.rsi("S"),
#' ampicillin = as.rsi("R")
#' )
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#' x
#' x[, betalactams()]
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#' }
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add_custom_antimicrobials <- function ( x ) {
meet_criteria ( x , allow_class = " data.frame" )
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stop_ifnot (
all ( c ( " ab" , " name" ) %in% colnames ( x ) ) ,
" `x` must contain columns \"ab\" and \"name\"."
)
stop_if (
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:
x <- as.data.frame ( x , stringsAsFactors = FALSE )
# 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 )
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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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 ]
rownames ( new_df ) <- NULL
list_cols <- vapply ( FUN.VALUE = logical ( 1 ) , new_df , is.list )
for ( l in which ( list_cols ) ) {
# prevent binding NULLs in lists, replace with NA
new_df [ , l ] <- as.list ( NA_character_ )
}
for ( col in colnames ( x ) ) {
# assign new values
new_df [ , col ] <- x [ , col , drop = TRUE ]
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}
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AMR_env $ AB_lookup <- unique ( rbind ( 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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}
#' @rdname add_custom_antimicrobials
#' @export
clear_custom_antimicrobials <- function ( ) {
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n <- nrow ( AMR_env $ AB_lookup )
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AMR_env $ AB_lookup <- create_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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}