# ==================================================================== # # 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 #' @param combine_RI logical to indicate whether values R and I should be summed #' @inheritParams rsi_df #' @importFrom dplyr rename #' @importFrom tidyr spread #' @importFrom clean freq #' @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. #' @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(example_isolates) #' 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_RI = FALSE, add_ab_group = TRUE, ...) { if (combine_RI == FALSE) { x$isolates <- x$R } else { x$isolates <- x$R + x$I } y <- x %>% mutate(mo = mo_name(mo), txt = paste0(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.")) }