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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
#'
#' 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 printable format, see Examples.
#' @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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#' @inheritParams rsi_df
#' @importFrom dplyr rename
#' @importFrom tidyr spread
#' @importFrom clean freq
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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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#' @export
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#' @rdname bug_drug_combinations
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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
#' format(x)
#' }
bug_drug_combinations <- function ( x , col_mo = NULL , minimum = 30 ) {
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 %>%
mutate ( col_mo = x %>% pull ( col_mo ) ) %>%
filter ( mo %in% ( clean :: freq ( mo ) %>%
filter ( count >= minimum ) %>%
pull ( item ) ) ) %>%
group_by ( mo ) %>%
AMR :: rsi_df ( translate_ab = FALSE , combine_SI = FALSE ) %>%
select ( - value ) %>%
spread ( interpretation , isolates ) %>%
mutate ( total = S + I + R ) %>%
filter ( total >= minimum ) %>%
rename ( ab = antibiotic )
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structure ( .Data = x , class = c ( " bug_drug_combinations" , class ( x ) ) )
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}
#' @importFrom dplyr everything rename
#' @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
format.bug_drug_combinations <- function ( x , combine_IR = FALSE , add_ab_group = TRUE ) {
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if ( combine_IR == FALSE ) {
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x $ isolates <- x $ R
} else {
x $ isolates <- x $ R + x $ I
}
y <- x %>%
mutate ( mo = mo_name ( mo ) ,
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txt = paste0 ( percent ( isolates / total , force_zero = TRUE ) ,
" (" , trimws ( format ( isolates , big.mark = " ," ) ) , " /" ,
trimws ( format ( total , big.mark = " ," ) ) , " )" ) ) %>%
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select ( ab , mo , txt ) %>%
spread ( mo , txt ) %>%
mutate_all ( ~ ifelse ( is.na ( .) , " " , .) ) %>%
mutate ( ab = paste0 ( ab_name ( ab ) , " (" , as.ab ( ab ) , " , " , ab_atc ( ab ) , " )" ) ,
ab_group = ab_group ( ab ) ) %>%
select ( ab_group , ab , everything ( ) ) %>%
arrange ( ab_group , ab ) %>%
mutate ( ab_group = ifelse ( ab_group != lag ( ab_group ) | is.na ( lag ( ab_group ) ) , ab_group , " " ) )
if ( add_ab_group == FALSE ) {
y <- y %>% select ( - ab_group )
}
y <- y %>% rename ( " Group" = ab_group ,
" Antibiotic" = ab )
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 ) )
message ( blue ( " NOTE: Use 'format()' on this result to get a format that is ready for export or printing." ) )
}