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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
# SOURCE #
# https://gitlab.com/msberends/AMR #
# #
# LICENCE #
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
# #
# 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. #
# #
# This R package was created for academic research and was publicly #
# released in the hope that it will be useful, but it comes WITHOUT #
# ANY WARRANTY OR LIABILITY. #
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
# ==================================================================== #
#' Determine bug-drug combinations
#'
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#' Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use \code{format} on the result to prettify it to a publicable/printable format, see Examples.
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#' @inheritParams eucast_rules
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#' @param combine_IR logical to indicate whether values R and I should be summed
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#' @param add_ab_group logical to indicate where the group of the antimicrobials must be included as a first column
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#' @param remove_intrinsic_resistant logical to indicate that rows with 100\% resistance for all tested antimicrobials must be removed from the table
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#' @param FUN the function to call on the \code{mo} column to transform the microorganism IDs, defaults to \code{\link{mo_shortname}}
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#' @param translate_ab a character of length 1 containing column names of the \code{\link{antibiotics}} data set
#' @param ... arguments passed on to \code{FUN}
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#' @inheritParams rsi_df
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#' @inheritParams base::formatC
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#' @importFrom dplyr %>% rename group_by select mutate filter summarise ungroup
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#' @importFrom tidyr spread
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# @importFrom clean freq percentage
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#' @details The function \code{format} calculates the resistance per bug-drug combination. Use \code{combine_IR = FALSE} (default) to test R vs. S+I and \code{combine_IR = TRUE} to test R+I vs. S.
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#'
#' The language of the output can be overwritten with \code{options(AMR_locale)}, please see \link{translate}.
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#' @export
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#' @rdname bug_drug_combinations
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#' @return The function \code{bug_drug_combinations} returns a \code{data.frame} with columns "mo", "ab", "S", "I", "R" and "total".
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#' @source \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
#' @inheritSection AMR Read more on our website!
#' @examples
#' \donttest{
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#' x <- bug_drug_combinations(example_isolates)
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#' x
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#' format(x, translate_ab = "name (atc)")
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#'
#' # Use FUN to change to transformation of microorganism codes
#' x <- bug_drug_combinations(example_isolates,
#' FUN = mo_gramstain)
#'
#' x <- bug_drug_combinations(example_isolates,
#' FUN = function(x) ifelse(x == "B_ESCHR_COLI",
#' "E. coli",
#' "Others"))
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#' }
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bug_drug_combinations <- function ( x ,
col_mo = NULL ,
FUN = mo_shortname ,
... ) {
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if ( ! is.data.frame ( x ) ) {
stop ( " `x` must be a data frame." , call. = FALSE )
}
# try to find columns based on type
# -- mo
if ( is.null ( col_mo ) ) {
col_mo <- search_type_in_df ( x = x , type = " mo" )
}
if ( is.null ( col_mo ) ) {
stop ( " `col_mo` must be set." , call. = FALSE )
}
x <- x %>%
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as.data.frame ( stringsAsFactors = FALSE ) %>%
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mutate ( mo = x %>%
pull ( col_mo ) %>%
FUN ( ... ) ) %>%
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group_by ( mo ) %>%
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select_if ( is.rsi ) %>%
gather ( " ab" , " value" , - mo ) %>%
group_by ( mo , ab ) %>%
summarise ( S = sum ( value == " S" , na.rm = TRUE ) ,
I = sum ( value == " I" , na.rm = TRUE ) ,
R = sum ( value == " R" , na.rm = TRUE ) ) %>%
ungroup ( ) %>%
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mutate ( total = S + I + R ) %>%
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as.data.frame ( stringsAsFactors = FALSE )
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structure ( .Data = x , class = c ( " bug_drug_combinations" , class ( x ) ) )
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}
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#' @importFrom dplyr everything rename %>% ungroup group_by summarise mutate_all arrange everything lag
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#' @importFrom tidyr spread
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#' @exportMethod format.bug_drug_combinations
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#' @export
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#' @rdname bug_drug_combinations
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format.bug_drug_combinations <- function ( x ,
translate_ab = " name (ab, atc)" ,
language = get_locale ( ) ,
minimum = 30 ,
combine_SI = TRUE ,
combine_IR = FALSE ,
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add_ab_group = TRUE ,
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remove_intrinsic_resistant = FALSE ,
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decimal.mark = getOption ( " OutDec" ) ,
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big.mark = ifelse ( decimal.mark == " ," , " ." , " ," ) ,
... ) {
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x <- x %>% filter ( total >= minimum )
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if ( remove_intrinsic_resistant == TRUE ) {
x <- x %>% filter ( R != total )
}
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if ( combine_SI == TRUE | combine_IR == FALSE ) {
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x $ isolates <- x $ R
} else {
x $ isolates <- x $ R + x $ I
}
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give_ab_name <- function ( ab , format , language ) {
format <- tolower ( format )
ab_txt <- rep ( format , length ( ab ) )
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for ( i in seq_len ( length ( ab_txt ) ) ) {
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ab_txt [i ] <- gsub ( " ab" , ab [i ] , ab_txt [i ] )
ab_txt [i ] <- gsub ( " cid" , ab_cid ( ab [i ] ) , ab_txt [i ] )
ab_txt [i ] <- gsub ( " group" , ab_group ( ab [i ] , language = language ) , ab_txt [i ] )
ab_txt [i ] <- gsub ( " atc_group1" , ab_atc_group1 ( ab [i ] , language = language ) , ab_txt [i ] )
ab_txt [i ] <- gsub ( " atc_group2" , ab_atc_group2 ( ab [i ] , language = language ) , ab_txt [i ] )
ab_txt [i ] <- gsub ( " atc" , ab_atc ( ab [i ] ) , ab_txt [i ] )
ab_txt [i ] <- gsub ( " name" , ab_name ( ab [i ] , language = language ) , ab_txt [i ] )
ab_txt [i ]
}
ab_txt
}
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y <- x %>%
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mutate ( ab = as.ab ( ab ) ,
ab_txt = give_ab_name ( ab = ab , format = translate_ab , language = language ) ) %>%
group_by ( ab , ab_txt , mo ) %>%
summarise ( isolates = sum ( isolates , na.rm = TRUE ) ,
total = sum ( total , na.rm = TRUE ) ) %>%
ungroup ( ) %>%
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mutate ( txt = paste0 ( percentage ( isolates / total , decimal.mark = decimal.mark , big.mark = big.mark ) ,
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" (" , trimws ( format ( isolates , big.mark = big.mark ) ) , " /" ,
trimws ( format ( total , big.mark = big.mark ) ) , " )" ) ) %>%
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select ( ab , ab_txt , mo , txt ) %>%
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spread ( mo , txt ) %>%
mutate_all ( ~ ifelse ( is.na ( .) , " " , .) ) %>%
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mutate ( ab_group = ab_group ( ab , language = language ) ,
ab_txt ) %>%
select ( ab_group , ab_txt , everything ( ) , - ab ) %>%
arrange ( ab_group , ab_txt ) %>%
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mutate ( ab_group = ifelse ( ab_group != lag ( ab_group ) | is.na ( lag ( ab_group ) ) , ab_group , " " ) )
if ( add_ab_group == FALSE ) {
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y <- y %>% select ( - ab_group ) %>% rename ( " Drug" = ab_txt )
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colnames ( y ) [1 ] <- translate_AMR ( colnames ( y ) [1 ] , language = get_locale ( ) , only_unknown = FALSE )
} else {
y <- y %>% rename ( " Group" = ab_group ,
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" Drug" = ab_txt )
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colnames ( y ) [1 : 2 ] <- translate_AMR ( colnames ( y ) [1 : 2 ] , language = get_locale ( ) , only_unknown = FALSE )
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}
y
}
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#' @exportMethod print.bug_drug_combinations
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#' @export
#' @importFrom crayon blue
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print.bug_drug_combinations <- function ( x , ... ) {
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print ( as.data.frame ( x , stringsAsFactors = FALSE ) )
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message ( blue ( " NOTE: Use 'format()' on this result to get a publicable/printable format." ) )
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}