mirror of https://github.com/msberends/AMR.git
291 lines
11 KiB
R
Executable File
291 lines
11 KiB
R
Executable File
# ==================================================================== #
|
|
# TITLE #
|
|
# Antimicrobial Resistance (AMR) Analysis #
|
|
# #
|
|
# SOURCE #
|
|
# https://gitlab.com/msberends/AMR #
|
|
# #
|
|
# LICENCE #
|
|
# (c) 2018-2020 Berends MS, Luz CF et al. #
|
|
# #
|
|
# 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. #
|
|
# #
|
|
# We created this package for both routine data analysis and academic #
|
|
# research and it 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. #
|
|
# ==================================================================== #
|
|
|
|
dots2vars <- function(...) {
|
|
# this function is to give more informative output about
|
|
# variable names in count_* and proportion_* functions
|
|
dots <- substitute(list(...))
|
|
paste(as.character(dots)[2:length(dots)], collapse = ", ")
|
|
}
|
|
|
|
rsi_calc <- function(...,
|
|
ab_result,
|
|
minimum = 0,
|
|
as_percent = FALSE,
|
|
only_all_tested = FALSE,
|
|
only_count = FALSE) {
|
|
|
|
data_vars <- dots2vars(...)
|
|
|
|
if (!is.numeric(minimum)) {
|
|
stop("`minimum` must be numeric", call. = FALSE)
|
|
}
|
|
if (!is.logical(as_percent)) {
|
|
stop("`as_percent` must be logical", call. = FALSE)
|
|
}
|
|
if (!is.logical(only_all_tested)) {
|
|
stop("`only_all_tested` must be logical", call. = FALSE)
|
|
}
|
|
|
|
dots_df <- switch(1, ...)
|
|
dots <- base::eval(base::substitute(base::alist(...)))
|
|
if ("also_single_tested" %in% names(dots)) {
|
|
stop("`also_single_tested` was replaced by `only_all_tested`. Please read Details in the help page (`?proportion`) as this may have a considerable impact on your analysis.", call. = FALSE)
|
|
}
|
|
ndots <- length(dots)
|
|
|
|
if ("data.frame" %in% class(dots_df)) {
|
|
# data.frame passed with other columns, like: example_isolates %>% proportion_S(AMC, GEN)
|
|
dots <- as.character(dots)
|
|
dots <- dots[dots != "."]
|
|
if (length(dots) == 0 | all(dots == "df")) {
|
|
# for complete data.frames, like example_isolates %>% select(AMC, GEN) %>% proportion_S()
|
|
# and the old rsi function, which has "df" as name of the first parameter
|
|
x <- dots_df
|
|
} else {
|
|
x <- dots_df[, dots[dots %in% colnames(dots_df)]]
|
|
}
|
|
} else if (ndots == 1) {
|
|
# only 1 variable passed (can also be data.frame), like: proportion_S(example_isolates$AMC) and example_isolates$AMC %>% proportion_S()
|
|
x <- dots_df
|
|
} else {
|
|
# multiple variables passed without pipe, like: proportion_S(example_isolates$AMC, example_isolates$GEN)
|
|
x <- NULL
|
|
try(x <- as.data.frame(dots), silent = TRUE)
|
|
if (is.null(x)) {
|
|
# support for example_isolates %>% group_by(hospital_id) %>% summarise(amox = susceptibility(GEN, AMX))
|
|
x <- as.data.frame(list(...))
|
|
}
|
|
}
|
|
|
|
if (is.null(x)) {
|
|
warning("argument is NULL (check if columns exist): returning NA", call. = FALSE)
|
|
return(NA)
|
|
}
|
|
|
|
print_warning <- FALSE
|
|
|
|
ab_result <- as.rsi(ab_result)
|
|
|
|
if (is.data.frame(x)) {
|
|
rsi_integrity_check <- character(0)
|
|
for (i in seq_len(ncol(x))) {
|
|
# check integrity of columns: force rsi class
|
|
if (!is.rsi(x %>% pull(i))) {
|
|
rsi_integrity_check <- c(rsi_integrity_check, x %>% pull(i) %>% as.character())
|
|
x[, i] <- suppressWarnings(x %>% pull(i) %>% as.rsi()) # warning will be given later
|
|
print_warning <- TRUE
|
|
}
|
|
}
|
|
if (length(rsi_integrity_check) > 0) {
|
|
# this will give a warning for invalid results, of all input columns (so only 1 warning)
|
|
rsi_integrity_check <- as.rsi(rsi_integrity_check)
|
|
}
|
|
|
|
if (only_all_tested == TRUE) {
|
|
# THE NUMBER OF ISOLATES WHERE *ALL* ABx ARE S/I/R
|
|
x <- apply(X = as.data.frame(lapply(x, as.integer), stringsAsFactors = FALSE),
|
|
MARGIN = 1,
|
|
FUN = base::min)
|
|
numerator <- sum(as.integer(x) %in% as.integer(ab_result), na.rm = TRUE)
|
|
denominator <- length(x) - sum(is.na(x))
|
|
|
|
} else {
|
|
# THE NUMBER OF ISOLATES WHERE *ANY* ABx IS S/I/R
|
|
other_values <- base::setdiff(c(NA, levels(ab_result)), ab_result)
|
|
other_values_filter <- base::apply(x, 1, function(y) {
|
|
base::all(y %in% other_values) & base::any(is.na(y))
|
|
})
|
|
numerator <- sum(as.logical(by(x, seq_len(nrow(x)), function(row) any(unlist(row) %in% ab_result, na.rm = TRUE))))
|
|
denominator <- nrow(x[!other_values_filter, ])
|
|
}
|
|
} else {
|
|
# x is not a data.frame
|
|
if (!is.rsi(x)) {
|
|
x <- as.rsi(x)
|
|
print_warning <- TRUE
|
|
}
|
|
numerator <- sum(x %in% ab_result, na.rm = TRUE)
|
|
denominator <- sum(x %in% levels(ab_result), na.rm = TRUE)
|
|
}
|
|
|
|
if (print_warning == TRUE) {
|
|
warning("Increase speed by transforming to class <rsi> on beforehand: your_data %>% mutate_if(is.rsi.eligible, as.rsi)",
|
|
call. = FALSE)
|
|
}
|
|
|
|
if (only_count == TRUE) {
|
|
return(numerator)
|
|
}
|
|
|
|
if (denominator < minimum) {
|
|
if (data_vars != "") {
|
|
data_vars <- paste(" for", data_vars)
|
|
}
|
|
warning("Introducing NA: only ", denominator, " results available", data_vars, " (`minimum` was set to ", minimum, ").", call. = FALSE)
|
|
fraction <- NA
|
|
} else {
|
|
fraction <- numerator / denominator
|
|
}
|
|
|
|
if (as_percent == TRUE) {
|
|
percentage(fraction, digits = 1)
|
|
} else {
|
|
fraction
|
|
}
|
|
}
|
|
|
|
rsi_calc_df <- function(type, # "proportion", "count" or "both"
|
|
data,
|
|
translate_ab = "name",
|
|
language = get_locale(),
|
|
minimum = 30,
|
|
as_percent = FALSE,
|
|
combine_SI = TRUE,
|
|
combine_IR = FALSE,
|
|
combine_SI_missing = FALSE) {
|
|
|
|
check_dataset_integrity()
|
|
|
|
if (!"data.frame" %in% class(data)) {
|
|
stop(paste0("`", type, "_df` must be called on a data.frame"), call. = FALSE)
|
|
}
|
|
|
|
if (isTRUE(combine_IR) & isTRUE(combine_SI_missing)) {
|
|
combine_SI <- FALSE
|
|
}
|
|
if (isTRUE(combine_SI) & isTRUE(combine_IR)) {
|
|
stop("either `combine_SI` or `combine_IR` can be TRUE, not both", call. = FALSE)
|
|
}
|
|
|
|
if (!any(sapply(data, is.rsi), na.rm = TRUE)) {
|
|
stop("No columns with class <rsi> found. See ?as.rsi.", call. = FALSE)
|
|
}
|
|
|
|
if (as.character(translate_ab) %in% c("TRUE", "official")) {
|
|
translate_ab <- "name"
|
|
}
|
|
|
|
# select only groups and antibiotics
|
|
if (has_groups(data)) {
|
|
data_has_groups <- TRUE
|
|
groups <- setdiff(names(get_groups(data)), ".rows") # get_groups is from poorman.R
|
|
data <- data[, c(groups, colnames(data)[sapply(data, is.rsi)]), drop = FALSE]
|
|
} else {
|
|
data_has_groups <- FALSE
|
|
data <- data[, colnames(data)[sapply(data, is.rsi)], drop = FALSE]
|
|
}
|
|
|
|
data <- as.data.frame(data, stringsAsFactors = FALSE)
|
|
if (isTRUE(combine_SI) | isTRUE(combine_IR)) {
|
|
for (i in seq_len(ncol(data))) {
|
|
if (is.rsi(data[, i, drop = TRUE])) {
|
|
data[, i] <- as.character(data[, i, drop = TRUE])
|
|
if (isTRUE(combine_SI)) {
|
|
data[, i] <- gsub("(I|S)", "SI", data[, i, drop = TRUE])
|
|
} else if (isTRUE(combine_IR)) {
|
|
data[, i] <- gsub("(I|R)", "IR", data[, i, drop = TRUE])
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
sum_it <- function(.data) {
|
|
out <- data.frame(antibiotic = character(0),
|
|
interpretation = character(0),
|
|
value = double(0),
|
|
isolates <- integer(0),
|
|
stringsAsFactors = FALSE)
|
|
if (data_has_groups) {
|
|
group_values <- unique(.data[, which(colnames(.data) %in% groups), drop = FALSE])
|
|
rownames(group_values) <- NULL
|
|
.data <- .data[, which(!colnames(.data) %in% groups), drop = FALSE]
|
|
}
|
|
for (i in seq_len(ncol(.data))) {
|
|
col_results <- as.data.frame(as.matrix(table(.data[, i, drop = TRUE])))
|
|
col_results$interpretation <- rownames(col_results)
|
|
col_results$isolates <- col_results[, 1, drop = TRUE]
|
|
if (nrow(col_results) > 0) {
|
|
if (sum(col_results$isolates, na.rm = TRUE) >= minimum) {
|
|
col_results$value <- col_results$isolates / sum(col_results$isolates, na.rm = TRUE)
|
|
} else {
|
|
col_results$value <- rep(NA_real_, NROW(col_results))
|
|
}
|
|
out_new <- data.frame(antibiotic = ifelse(isFALSE(translate_ab),
|
|
colnames(.data)[i],
|
|
ab_property(colnames(.data)[i], property = translate_ab, language = language)),
|
|
interpretation = col_results$interpretation,
|
|
value = col_results$value,
|
|
isolates = col_results$isolates,
|
|
stringsAsFactors = FALSE)
|
|
if (data_has_groups) {
|
|
out_new <- cbind(group_values, out_new)
|
|
}
|
|
out <- rbind(out, out_new)
|
|
}
|
|
}
|
|
out
|
|
}
|
|
|
|
# support dplyr groups
|
|
apply_group <- function(.data, fn, groups, ...) {
|
|
grouped <- split(x = .data, f = lapply(groups, function(x, .data) as.factor(.data[, x]), .data))
|
|
res <- do.call(rbind, unname(lapply(grouped, fn, ...)))
|
|
if (any(groups %in% colnames(res))) {
|
|
class(res) <- c("grouped_data", class(res))
|
|
attr(res, "groups") <- groups[groups %in% colnames(res)]
|
|
}
|
|
res
|
|
}
|
|
|
|
if (data_has_groups) {
|
|
out <- apply_group(data, "sum_it", groups)
|
|
} else {
|
|
out <- sum_it(data)
|
|
}
|
|
|
|
# apply factors for right sorting in interpretation
|
|
if (isTRUE(combine_SI)) {
|
|
out$interpretation <- factor(out$interpretation, levels = c("SI", "R"), ordered = TRUE)
|
|
} else if (isTRUE(combine_IR)) {
|
|
out$interpretation <- factor(out$interpretation, levels = c("S", "IR"), ordered = TRUE)
|
|
} else {
|
|
out$interpretation <- as.rsi(out$interpretation)
|
|
}
|
|
|
|
if (data_has_groups) {
|
|
# ordering by the groups and two more: "antibiotic" and "interpretation"
|
|
out <- out[do.call("order", out[, seq_len(length(groups) + 2)]), ]
|
|
} else {
|
|
out <- out[order(out$antibiotic, out$interpretation), ]
|
|
}
|
|
|
|
if (type == "proportion") {
|
|
out <- subset(out, select = -c(isolates))
|
|
} else if (type == "count") {
|
|
out$value <- out$isolates
|
|
out <- subset(out, select = -c(isolates))
|
|
}
|
|
|
|
rownames(out) <- NULL
|
|
out
|
|
}
|