mirror of https://github.com/msberends/AMR.git
110 lines
4.7 KiB
R
110 lines
4.7 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
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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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# #
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# This R package was created for academic research and was publicly #
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# released in the hope that it will be useful, but it comes WITHOUT #
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# ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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#' Determine bug-drug combinations
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#'
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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 printable format, see Examples.
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#' @inheritParams eucast_rules
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#' @param combine_RI logical to indicate whether values R and I should be summed
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#' @inheritParams rsi_df
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#' @importFrom dplyr rename
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#' @importFrom tidyr spread
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#' @importFrom clean freq
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#' @details The function \code{format} calculated the resistance per bug-drug combination. Use \code{combine_RI = FALSE} (default) to test R vs. S+I and \code{combine_RI = TRUE} to test R+I vs. S.
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#' @export
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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/}.
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#' @inheritSection AMR Read more on our website!
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#' @examples
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#' \donttest{
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#' x <- bug_drug_combinations(example_isolates)
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#' x
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#' format(x)
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#' }
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bug_drug_combinations <- function(x, col_mo = NULL, minimum = 30) {
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if (!is.data.frame(x)) {
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stop("`x` must be a data frame.", call. = FALSE)
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}
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# try to find columns based on type
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# -- mo
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if (is.null(col_mo)) {
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col_mo <- search_type_in_df(x = x, type = "mo")
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}
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if (is.null(col_mo)) {
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stop("`col_mo` must be set.", call. = FALSE)
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}
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x <- x %>%
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mutate(col_mo = x %>% pull(col_mo)) %>%
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filter(mo %in% (clean::freq(mo) %>%
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filter(count >= minimum) %>%
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pull(item))) %>%
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group_by(mo) %>%
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AMR::rsi_df(translate_ab = FALSE, combine_SI = FALSE) %>%
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select(-value) %>%
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spread(interpretation, isolates) %>%
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mutate(total = S + I + R) %>%
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filter(total >= minimum) %>%
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rename(ab = antibiotic)
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structure(.Data = x, class = c("bugdrug", class(x)))
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}
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#' @importFrom dplyr everything rename
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#' @importFrom tidyr spread
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#' @exportMethod format.bugdrug
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#' @export
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format.bugdrug <- function(x, combine_RI = FALSE, add_ab_group = TRUE, ...) {
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if (combine_RI == FALSE) {
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x$isolates <- x$R
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} else {
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x$isolates <- x$R + x$I
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}
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y <- x %>%
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mutate(mo = mo_name(mo),
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txt = paste0(percent(isolates / total, force_zero = TRUE),
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" (", trimws(format(isolates, big.mark = ",")), "/",
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trimws(format(total, big.mark = ",")), ")")) %>%
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select(ab, mo, txt) %>%
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spread(mo, txt) %>%
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mutate_all(~ifelse(is.na(.), "", .)) %>%
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mutate(ab = paste0(ab_name(ab), " (", as.ab(ab), ", ", ab_atc(ab), ")"),
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ab_group = ab_group(ab)) %>%
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select(ab_group, ab, everything()) %>%
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arrange(ab_group, ab) %>%
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mutate(ab_group = ifelse(ab_group != lag(ab_group) | is.na(lag(ab_group)), ab_group, ""))
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if (add_ab_group == FALSE) {
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y <- y %>% select(-ab_group)
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}
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y <- y %>% rename("Group" = ab_group,
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"Antibiotic" = ab)
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y
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}
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#' @exportMethod print.bugdrug
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#' @export
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#' @importFrom crayon blue
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print.bugdrug <- 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 format that is ready for export or printing."))
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}
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