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317 lines
14 KiB
317 lines
14 KiB
# ==================================================================== # |
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# TITLE # |
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# Antimicrobial Resistance (AMR) Data Analysis for R # |
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# # |
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# SOURCE # |
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# https://github.com/msberends/AMR # |
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# # |
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# LICENCE # |
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# (c) 2018-2022 Berends MS, Luz CF et al. # |
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# Developed at the University of Groningen, the Netherlands, in # |
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# collaboration with non-profit organisations Certe Medical # |
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# Diagnostics & Advice, and University Medical Center Groningen. # |
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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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# We created this package for both routine data analysis and academic # |
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# research and it was publicly released in the hope that it will be # |
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # |
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# # |
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# Visit our website for the full manual and a complete tutorial about # |
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# how to conduct AMR data analysis: https://msberends.github.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 [format()] on the result to prettify it to a publishable/printable format, see *Examples*. |
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#' @inheritSection lifecycle Stable Lifecycle |
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#' @inheritParams eucast_rules |
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#' @param combine_IR a [logical] to indicate whether values R and I should be summed |
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#' @param add_ab_group a [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 and columns 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 `mo` column to transform the microorganism codes, defaults to [mo_shortname()] |
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#' @param translate_ab a [character] of length 1 containing column names of the [antibiotics] data set |
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#' @param ... arguments passed on to `FUN` |
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#' @inheritParams rsi_df |
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#' @inheritParams base::formatC |
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#' @details The function [format()] calculates the resistance per bug-drug combination. Use `combine_IR = FALSE` (default) to test R vs. S+I and `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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#' @return The function [bug_drug_combinations()] returns a [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, *Clinical and Laboratory Standards Institute (CLSI)*. <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, translate_ab = "name (atc)") |
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#' |
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#' # Use FUN to change to transformation of microorganism codes |
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#' bug_drug_combinations(example_isolates, |
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#' FUN = mo_gramstain) |
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#' |
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#' bug_drug_combinations(example_isolates, |
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#' FUN = function(x) ifelse(x == as.mo("E. coli"), |
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#' "E. coli", |
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#' "Others")) |
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#' } |
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bug_drug_combinations <- function(x, |
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col_mo = NULL, |
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FUN = mo_shortname, |
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...) { |
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meet_criteria(x, allow_class = "data.frame", contains_column_class = "rsi") |
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meet_criteria(col_mo, allow_class = "character", is_in = colnames(x), has_length = 1, allow_NULL = TRUE) |
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meet_criteria(FUN, allow_class = "function", has_length = 1) |
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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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stop_if(is.null(col_mo), "`col_mo` must be set") |
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} else { |
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stop_ifnot(col_mo %in% colnames(x), "column '", col_mo, "' (`col_mo`) not found") |
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} |
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x.bak <- x |
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x <- as.data.frame(x, stringsAsFactors = FALSE) |
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x[, col_mo] <- FUN(x[, col_mo, drop = TRUE], ...) |
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unique_mo <- sort(unique(x[, col_mo, drop = TRUE])) |
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# select only groups and antibiotics |
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if (is_null_or_grouped_tbl(x.bak)) { |
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data_has_groups <- TRUE |
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groups <- setdiff(names(attributes(x.bak)$groups), ".rows") |
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x <- x[, c(groups, col_mo, colnames(x)[vapply(FUN.VALUE = logical(1), x, is.rsi)]), drop = FALSE] |
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} else { |
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data_has_groups <- FALSE |
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x <- x[, c(col_mo, names(which(vapply(FUN.VALUE = logical(1), x, is.rsi)))), drop = FALSE] |
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} |
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run_it <- function(x) { |
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out <- data.frame(mo = character(0), |
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ab = character(0), |
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S = integer(0), |
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I = integer(0), |
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R = integer(0), |
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total = integer(0), |
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stringsAsFactors = FALSE) |
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if (data_has_groups) { |
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group_values <- unique(x[, which(colnames(x) %in% groups), drop = FALSE]) |
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rownames(group_values) <- NULL |
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x <- x[, which(!colnames(x) %in% groups), drop = FALSE] |
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} |
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for (i in seq_len(length(unique_mo))) { |
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# filter on MO group and only select R/SI columns |
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x_mo_filter <- x[which(x[, col_mo, drop = TRUE] == unique_mo[i]), names(which(vapply(FUN.VALUE = logical(1), x, is.rsi))), drop = FALSE] |
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# turn and merge everything |
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pivot <- lapply(x_mo_filter, function(x) { |
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m <- as.matrix(table(x)) |
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data.frame(S = m["S", ], I = m["I", ], R = m["R", ], stringsAsFactors = FALSE) |
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}) |
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merged <- do.call(rbind, pivot) |
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out_group <- data.frame(mo = rep(unique_mo[i], NROW(merged)), |
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ab = rownames(merged), |
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S = merged$S, |
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I = merged$I, |
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R = merged$R, |
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total = merged$S + merged$I + merged$R, |
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stringsAsFactors = FALSE) |
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if (data_has_groups) { |
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if (nrow(group_values) < nrow(out_group)) { |
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# repeat group_values for the number of rows in out_group |
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repeated <- rep(seq_len(nrow(group_values)), |
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each = nrow(out_group) / nrow(group_values)) |
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group_values <- group_values[repeated, , drop = FALSE] |
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} |
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out_group <- cbind(group_values, out_group) |
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} |
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out <- rbind(out, out_group, stringsAsFactors = FALSE) |
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} |
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out |
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} |
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# based on pm_apply_grouped_function |
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apply_group <- function(.data, fn, groups, drop = FALSE, ...) { |
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grouped <- pm_split_into_groups(.data, groups, drop) |
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res <- do.call(rbind, unname(lapply(grouped, fn, ...))) |
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if (any(groups %in% colnames(res))) { |
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class(res) <- c("grouped_data", class(res)) |
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res <- pm_set_groups(res, groups[groups %in% colnames(res)]) |
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} |
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res |
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} |
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if (data_has_groups) { |
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out <- apply_group(x, "run_it", groups) |
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rownames(out) <- NULL |
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set_clean_class(out, |
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new_class = c("grouped", "bug_drug_combinations", "data.frame")) |
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} else { |
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out <- run_it(x) |
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rownames(out) <- NULL |
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set_clean_class(out, |
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new_class = c("bug_drug_combinations", "data.frame")) |
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} |
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} |
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#' @method 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, |
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translate_ab = "name (ab, atc)", |
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language = get_AMR_locale(), |
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minimum = 30, |
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combine_SI = TRUE, |
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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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...) { |
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meet_criteria(x, allow_class = "data.frame") |
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meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE) |
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meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE) |
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meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE) |
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meet_criteria(combine_SI, allow_class = "logical", has_length = 1) |
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meet_criteria(combine_IR, allow_class = "logical", has_length = 1) |
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meet_criteria(add_ab_group, allow_class = "logical", has_length = 1) |
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meet_criteria(remove_intrinsic_resistant, allow_class = "logical", has_length = 1) |
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meet_criteria(decimal.mark, allow_class = "character", has_length = 1) |
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meet_criteria(big.mark, allow_class = "character", has_length = 1) |
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if (inherits(x, "grouped")) { |
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# bug_drug_combinations() has been run on groups, so de-group here |
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warning_("formatting the output of `bug_drug_combinations()` does not support grouped variables, they are ignored", call = FALSE) |
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idx <- split(seq_len(nrow(x)), paste0(x$mo, "%%", x$ab)) |
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x <- data.frame(mo = gsub("(.*)%%(.*)", "\\1", names(idx)), |
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ab = gsub("(.*)%%(.*)", "\\2", names(idx)), |
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S = sapply(idx, function(i) sum(y$S[i], na.rm = TRUE)), |
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I = sapply(idx, function(i) sum(y$I[i], na.rm = TRUE)), |
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R = sapply(idx, function(i) sum(y$R[i], na.rm = TRUE)), |
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total = sapply(idx, function(i) sum(y$S[i], na.rm = TRUE) + |
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sum(y$I[i], na.rm = TRUE) + |
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sum(y$R[i], na.rm = TRUE)), |
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stringsAsFactors = FALSE) |
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} |
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x <- as.data.frame(x, stringsAsFactors = FALSE) |
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x <- subset(x, total >= minimum) |
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if (remove_intrinsic_resistant == TRUE) { |
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x <- subset(x, R != total) |
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} |
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if (combine_SI == TRUE | combine_IR == FALSE) { |
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x$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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give_ab_name <- function(ab, format, language) { |
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format <- tolower(format) |
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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", as.character(as.ab(ab[i])), ab_txt[i]) |
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ab_txt[i] <- gsub("cid", ab_cid(ab[i]), ab_txt[i]) |
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ab_txt[i] <- gsub("group", ab_group(ab[i], language = language), ab_txt[i]) |
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ab_txt[i] <- gsub("atc_group1", ab_atc_group1(ab[i], language = language), ab_txt[i]) |
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ab_txt[i] <- gsub("atc_group2", ab_atc_group2(ab[i], language = language), ab_txt[i]) |
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ab_txt[i] <- gsub("atc", ab_atc(ab[i], only_first = TRUE), ab_txt[i]) |
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ab_txt[i] <- gsub("name", ab_name(ab[i], language = language), ab_txt[i]) |
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ab_txt[i] |
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} |
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ab_txt |
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} |
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remove_NAs <- function(.data) { |
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cols <- colnames(.data) |
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.data <- as.data.frame(lapply(.data, function(x) ifelse(is.na(x), "", x)), |
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stringsAsFactors = FALSE) |
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colnames(.data) <- cols |
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.data |
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} |
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create_var <- function(.data, ...) { |
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dots <- list(...) |
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for (i in seq_len(length(dots))) { |
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.data[, names(dots)[i]] <- dots[[i]] |
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} |
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.data |
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} |
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y <- x %pm>% |
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create_var(ab = as.ab(x$ab), |
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ab_txt = give_ab_name(ab = x$ab, format = translate_ab, language = language)) %pm>% |
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pm_group_by(ab, ab_txt, mo) %pm>% |
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pm_summarise(isolates = sum(isolates, na.rm = TRUE), |
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total = sum(total, na.rm = TRUE)) %pm>% |
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pm_ungroup() |
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y <- y %pm>% |
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create_var(txt = paste0(percentage(y$isolates / y$total, decimal.mark = decimal.mark, big.mark = big.mark), |
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" (", trimws(format(y$isolates, big.mark = big.mark)), "/", |
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trimws(format(y$total, big.mark = big.mark)), ")")) %pm>% |
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pm_select(ab, ab_txt, mo, txt) %pm>% |
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pm_arrange(mo) |
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# replace tidyr::pivot_wider() from here |
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for (i in unique(y$mo)) { |
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mo_group <- y[which(y$mo == i), c("ab", "txt")] |
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colnames(mo_group) <- c("ab", i) |
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rownames(mo_group) <- NULL |
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y <- y %pm>% |
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pm_left_join(mo_group, by = "ab") |
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} |
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y <- y %pm>% |
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pm_distinct(ab, .keep_all = TRUE) %pm>% |
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pm_select(-mo, -txt) %pm>% |
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# replace tidyr::pivot_wider() until here |
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remove_NAs() |
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select_ab_vars <- function(.data) { |
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.data[, c("ab_group", "ab_txt", colnames(.data)[!colnames(.data) %in% c("ab_group", "ab_txt", "ab")])] |
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} |
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y <- y %pm>% |
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create_var(ab_group = ab_group(y$ab, language = language)) %pm>% |
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select_ab_vars() %pm>% |
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pm_arrange(ab_group, ab_txt) |
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y <- y %pm>% |
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create_var(ab_group = ifelse(y$ab_group != pm_lag(y$ab_group) | is.na(pm_lag(y$ab_group)), y$ab_group, "")) |
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if (add_ab_group == FALSE) { |
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y <- y %pm>% |
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pm_select(-ab_group) %pm>% |
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pm_rename("Drug" = ab_txt) |
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colnames(y)[1] <- translate_AMR(colnames(y)[1], language, only_unknown = FALSE) |
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} else { |
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y <- y %pm>% |
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pm_rename("Group" = ab_group, |
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"Drug" = ab_txt) |
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} |
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if (!is.null(language)) { |
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colnames(y) <- translate_AMR(colnames(y), language, only_unknown = FALSE) |
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} |
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if (remove_intrinsic_resistant == TRUE) { |
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y <- y[, !vapply(FUN.VALUE = logical(1), y, function(col) all(col %like% "100", na.rm = TRUE) & !any(is.na(col))), drop = FALSE] |
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} |
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rownames(y) <- NULL |
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y |
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} |
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#' @method print bug_drug_combinations |
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#' @export |
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print.bug_drug_combinations <- function(x, ...) { |
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x_class <- class(x) |
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print(set_clean_class(x, |
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new_class = x_class[!x_class %in% c("bug_drug_combinations", "grouped")]), |
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...) |
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message_("Use 'format()' on this result to get a publishable/printable format.", |
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ifelse(inherits(x, "grouped"), " Note: The grouping variable(s) will be ignored.", ""), |
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as_note = FALSE) |
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}
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