AMR/R/bug_drug_combinations.R

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2019-08-25 22:53:22 +02:00
# ==================================================================== #
# 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
#' @inheritParams rsi_df
#' @importFrom dplyr rename
#' @importFrom tidyr spread
#' @importFrom clean freq
#' @export
#' @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{
#' x <- bug_drug_combinations(septic_patients)
#' 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)
structure(.Data = x, class = c("bugdrug", class(x)))
}
#' @importFrom dplyr everything rename
#' @importFrom tidyr spread
#' @exportMethod format.bugdrug
#' @export
format.bugdrug <- function(x, combine_SI = TRUE, add_ab_group = TRUE, ...) {
if (combine_SI == TRUE) {
x$isolates <- x$R
} else {
x$isolates <- x$R + x$I
}
y <- x %>%
mutate(mo = mo_name(mo),
txt = paste0(AMR:::percent(isolates / total, force_zero = TRUE),
" (", trimws(format(isolates, big.mark = ",")), "/",
trimws(format(total, big.mark = ",")), ")")) %>%
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
}
#' @exportMethod print.bugdrug
#' @export
#' @importFrom crayon blue
print.bugdrug <- function(x, ...) {
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."))
}