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AMR/R/rsi.R

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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
# AUTHORS #
# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
# #
# LICENCE #
# This package is free software; you can redistribute it and/or modify #
# it under the terms of the GNU General Public License version 2.0, #
# as published by the Free Software Foundation. #
# #
# This R package is distributed in the hope that it will be useful, #
# but WITHOUT ANY WARRANTY; without even the implied warranty of #
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
# GNU General Public License version 2.0 for more details. #
# ==================================================================== #
#' Class 'rsi'
#'
#' This transforms a vector to a new class \code{rsi}, which is an ordered factor with levels \code{S < I < R}. Invalid antimicrobial interpretations will be translated as \code{NA} with a warning.
#' @rdname as.rsi
#' @param x vector
#' @details The function \code{is.rsi.eligible} returns \code{TRUE} when a columns contains only valid antimicrobial interpretations (S and/or I and/or R), and \code{FALSE} otherwise.
#' @return Ordered factor with new class \code{rsi}
#' @keywords rsi
#' @export
#' @importFrom dplyr %>%
#' @seealso \code{\link{as.mic}}
#' @examples
#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370), "A", "B", "C"))
#' is.rsi(rsi_data)
#'
#' # this can also coerce combined MIC/RSI values:
#' as.rsi("<= 0.002; S") # will return S
#'
#' plot(rsi_data) # for percentages
#' barplot(rsi_data) # for frequencies
#' freq(rsi_data) # frequency table with informative header
#'
#' # using dplyr's mutate
#' library(dplyr)
#' septic_patients %>%
#' mutate_at(vars(peni:rifa), as.rsi)
#'
#' # fastest way to transform all columns with already valid AB results to class `rsi`:
#' septic_patients %>%
#' mutate_if(is.rsi.eligible,
#' as.rsi)
as.rsi <- function(x) {
if (is.rsi(x)) {
x
} else if (identical(levels(x), c("S", "I", "R"))) {
structure(x, class = c('rsi', 'ordered', 'factor'))
} else {
x <- x %>% unlist()
x.bak <- x
na_before <- x[is.na(x) | x == ''] %>% length()
# remove all spaces
x <- gsub(' +', '', x)
# remove all MIC-like values: numbers, operators and periods
x <- gsub('[0-9.,;:<=>]+', '', x)
# disallow more than 3 characters
x[nchar(x) > 3] <- NA
# set to capitals
x <- toupper(x)
# remove all invalid characters
x <- gsub('[^RSI]+', '', x)
# in cases of "S;S" keep S, but in case of "S;I" make it NA
x <- gsub('^S+$', 'S', x)
x <- gsub('^I+$', 'I', x)
x <- gsub('^R+$', 'R', x)
x[!x %in% c('S', 'I', 'R')] <- NA
na_after <- x[is.na(x) | x == ''] %>% length()
if (na_before != na_after) {
list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ''] %>%
unique() %>%
sort()
list_missing <- paste0('"', list_missing , '"', collapse = ", ")
warning(na_after - na_before, ' results truncated (',
round(((na_after - na_before) / length(x)) * 100),
'%) that were invalid antimicrobial interpretations: ',
list_missing, call. = FALSE)
}
x <- factor(x, levels = c("S", "I", "R"), ordered = TRUE)
class(x) <- c('rsi', 'ordered', 'factor')
x
}
}
#' @rdname as.rsi
#' @export
#' @importFrom dplyr %>%
is.rsi <- function(x) {
class(x) %>% identical(c('rsi', 'ordered', 'factor'))
}
#' @rdname as.rsi
#' @export
#' @importFrom dplyr %>%
is.rsi.eligible <- function(x) {
if (is.logical(x)
| is.numeric(x)
| is.mo(x)
| identical(class(x), "Date")
| is.rsi(x)) {
# no transformation needed
FALSE
} else {
# check all but a-z
y <- unique(gsub("[^RSIrsi]+", "", unique(x)))
!all(y %in% c("", NA_character_)) &
all(y %in% c("R", "I", "S", "", NA_character_)) &
max(nchar(as.character(x)), na.rm = TRUE) < 8
}
}
#' @exportMethod print.rsi
#' @export
#' @importFrom dplyr %>%
#' @noRd
print.rsi <- function(x, ...) {
cat("Class 'rsi'\n")
print(as.character(x), quote = FALSE)
}
#' @exportMethod summary.rsi
#' @export
#' @noRd
summary.rsi <- function(object, ...) {
x <- object
c(
"Class" = 'rsi',
"<NA>" = sum(is.na(x)),
"Sum S" = sum(x == "S", na.rm = TRUE),
"Sum IR" = sum(x %in% c("I", "R"), na.rm = TRUE),
"-Sum R" = sum(x == "R", na.rm = TRUE),
"-Sum I" = sum(x == "I", na.rm = TRUE)
)
}
#' @exportMethod plot.rsi
#' @export
#' @importFrom dplyr %>% group_by summarise filter mutate if_else n_distinct
#' @importFrom graphics plot text
#' @noRd
plot.rsi <- function(x, ...) {
x_name <- deparse(substitute(x))
data <- data.frame(x = x,
y = 1,
stringsAsFactors = TRUE) %>%
group_by(x) %>%
summarise(n = sum(y)) %>%
filter(!is.na(x)) %>%
mutate(s = round((n / sum(n)) * 100, 1))
data$x <- factor(data$x, levels = c('S', 'I', 'R'), ordered = TRUE)
ymax <- if_else(max(data$s) > 95, 105, 100)
plot(x = data$x,
y = data$s,
lwd = 2,
col = c('green', 'orange', 'red'),
ylim = c(0, ymax),
ylab = 'Percentage',
xlab = 'Antimicrobial Interpretation',
main = paste('Susceptibility Analysis of', x_name),
axes = FALSE,
...)
# x axis
axis(side = 1, at = 1:n_distinct(data$x), labels = levels(data$x), lwd = 0)
# y axis, 0-100%
axis(side = 2, at = seq(0, 100, 5))
text(x = data$x,
y = data$s + 4,
labels = paste0(data$s, '% (n = ', data$n, ')'))
}
#' @exportMethod barplot.rsi
#' @export
#' @importFrom dplyr %>% group_by summarise filter mutate if_else n_distinct
#' @importFrom graphics barplot axis
#' @noRd
barplot.rsi <- function(height, ...) {
x <- height
x_name <- deparse(substitute(height))
data <- data.frame(rsi = x, cnt = 1) %>%
group_by(rsi) %>%
summarise(cnt = sum(cnt)) %>%
droplevels()
barplot(table(x),
col = c('green3', 'orange2', 'red3'),
xlab = 'Antimicrobial Interpretation',
main = paste('Susceptibility Analysis of', x_name),
ylab = 'Frequency',
axes = FALSE,
...)
# y axis, 0-100%
axis(side = 2, at = seq(0, max(data$cnt) + max(data$cnt) * 1.1, by = 25))
}
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