AMR/R/mic.R

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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
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# SOURCE #
# https://gitlab.com/msberends/AMR #
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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 #
# 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. #
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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
#' Class 'mic'
#'
#' This transforms a vector to a new class \code{mic}, which is an ordered factor with valid MIC values as levels. Invalid MIC values will be translated as \code{NA} with a warning.
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#' @rdname as.mic
#' @param x vector
#' @param na.rm a logical indicating whether missing values should be removed
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#' @details Interpret MIC values as RSI values with \code{\link{as.rsi}}. It supports guidelines from EUCAST and CLSI.
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#' @return Ordered factor with new class \code{mic}
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#' @keywords mic
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#' @export
#' @importFrom dplyr %>%
#' @seealso \code{\link{as.rsi}}
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#' @inheritSection AMR Read more on our website!
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#' @examples
#' mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
#' is.mic(mic_data)
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#'
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#' # this can also coerce combined MIC/RSI values:
#' as.mic("<=0.002; S") # will return <=0.002
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#'
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#' # interpret MIC values
#' as.rsi(x = as.mic(2),
#' mo = as.mo("S. pneumoniae"),
#' ab = "AMX",
#' guideline = "EUCAST")
#' as.rsi(x = as.mic(4),
#' mo = as.mo("S. pneumoniae"),
#' ab = "AMX",
#' guideline = "EUCAST")
#'
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#' plot(mic_data)
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#' barplot(mic_data)
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#' freq(mic_data)
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as.mic <- function(x, na.rm = FALSE) {
if (is.mic(x)) {
x
} else {
x <- x %>% unlist()
if (na.rm == TRUE) {
x <- x[!is.na(x)]
}
x.bak <- x
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# comma to period
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x <- gsub(',', '.', x, fixed = TRUE)
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# remove space between operator and number ("<= 0.002" -> "<=0.002")
x <- gsub('(<|=|>) +', '\\1', x)
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# starting dots must start with 0
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x <- gsub('^[.]+', '0.', x)
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# <=0.2560.512 should be 0.512
x <- gsub('.*[.].*[.]', '0.', x)
# remove ending .0
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x <- gsub('[.]+0$', '', x)
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# remove all after last digit
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x <- gsub('[^0-9]+$', '', x)
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# remove last zeroes
x <- gsub('([.].?)0+$', '\\1', x)
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x <- gsub('(.*[.])0+$', '\\10', x)
# remove ending .0 again
x <- gsub('[.]+0$', '', x)
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# force to be character
x <- as.character(x)
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## previously unempty values now empty - should return a warning later on
x[x.bak != "" & x == ""] <- "invalid"
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# these are allowed MIC values and will become factor levels
lvls <- c("<0.001", "<=0.001", "0.001", ">=0.001", ">0.001",
"<0.002", "<=0.002", "0.002", ">=0.002", ">0.002",
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"<0.003", "<=0.003", "0.003", ">=0.003", ">0.003",
"<0.004", "<=0.004", "0.004", ">=0.004", ">0.004",
"<0.006", "<=0.006", "0.006", ">=0.006", ">0.006",
"<0.008", "<=0.008", "0.008", ">=0.008", ">0.008",
"<0.012", "<=0.012", "0.012", ">=0.012", ">0.012",
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"<0.0125", "<=0.0125", "0.0125", ">=0.0125", ">0.0125",
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"<0.016", "<=0.016", "0.016", ">=0.016", ">0.016",
"<0.023", "<=0.023", "0.023", ">=0.023", ">0.023",
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"<0.025", "<=0.025", "0.025", ">=0.025", ">0.025",
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"<0.03", "<=0.03", "0.03", ">=0.03", ">0.03",
"<0.032", "<=0.032", "0.032", ">=0.032", ">0.032",
"<0.047", "<=0.047", "0.047", ">=0.047", ">0.047",
"<0.05", "<=0.05", "0.05", ">=0.05", ">0.05",
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"<0.054", "<=0.054", "0.054", ">=0.054", ">0.054",
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"<0.06", "<=0.06", "0.06", ">=0.06", ">0.06",
"<0.0625", "<=0.0625", "0.0625", ">=0.0625", ">0.0625",
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"<0.063", "<=0.063", "0.063", ">=0.063", ">0.063",
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"<0.064", "<=0.064", "0.064", ">=0.064", ">0.064",
"<0.09", "<=0.09", "0.09", ">=0.09", ">0.09",
"<0.094", "<=0.094", "0.094", ">=0.094", ">0.094",
"<0.12", "<=0.12", "0.12", ">=0.12", ">0.12",
"<0.125", "<=0.125", "0.125", ">=0.125", ">0.125",
"<0.128", "<=0.128", "0.128", ">=0.128", ">0.128",
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"<0.16", "<=0.16", "0.16", ">=0.16", ">0.16",
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"<0.19", "<=0.19", "0.19", ">=0.19", ">0.19",
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"<0.23", "<=0.23", "0.23", ">=0.23", ">0.23",
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"<0.25", "<=0.25", "0.25", ">=0.25", ">0.25",
"<0.256", "<=0.256", "0.256", ">=0.256", ">0.256",
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"<0.28", "<=0.28", "0.28", ">=0.28", ">0.28",
"<0.3", "<=0.3", "0.3", ">=0.3", ">0.3",
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"<0.32", "<=0.32", "0.32", ">=0.32", ">0.32",
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"<0.36", "<=0.36", "0.36", ">=0.36", ">0.36",
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"<0.38", "<=0.38", "0.38", ">=0.38", ">0.38",
"<0.5", "<=0.5", "0.5", ">=0.5", ">0.5",
"<0.512", "<=0.512", "0.512", ">=0.512", ">0.512",
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"<0.64", "<=0.64", "0.64", ">=0.64", ">0.64",
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"<0.75", "<=0.75", "0.75", ">=0.75", ">0.75",
"<1", "<=1", "1", ">=1", ">1",
"<1.5", "<=1.5", "1.5", ">=1.5", ">1.5",
"<2", "<=2", "2", ">=2", ">2",
"<3", "<=3", "3", ">=3", ">3",
"<4", "<=4", "4", ">=4", ">4",
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"<5", "<=5", "5", ">=5", ">5",
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"<6", "<=6", "6", ">=6", ">6",
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"<7", "<=7", "7", ">=7", ">7",
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"<8", "<=8", "8", ">=8", ">8",
"<10", "<=10", "10", ">=10", ">10",
"<12", "<=12", "12", ">=12", ">12",
"<16", "<=16", "16", ">=16", ">16",
"<20", "<=20", "20", ">=20", ">20",
"<24", "<=24", "24", ">=24", ">24",
"<32", "<=32", "32", ">=32", ">32",
"<40", "<=40", "40", ">=40", ">40",
"<48", "<=48", "48", ">=48", ">48",
"<64", "<=64", "64", ">=64", ">64",
"<80", "<=80", "80", ">=80", ">80",
"<96", "<=96", "96", ">=96", ">96",
"<128", "<=128", "128", ">=128", ">128",
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"129",
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"<160", "<=160", "160", ">=160", ">160",
"<256", "<=256", "256", ">=256", ">256",
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"257",
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"<320", "<=320", "320", ">=320", ">320",
"<512", "<=512", "512", ">=512", ">512",
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"513",
"<1024", "<=1024", "1024", ">=1024", ">1024",
"1025")
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na_before <- x[is.na(x) | x == ''] %>% length()
x[!x %in% lvls] <- NA
na_after <- x[is.na(x) | x == ''] %>% length()
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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),
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'%) that were invalid MICs: ',
list_missing, call. = FALSE)
}
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x <- factor(x, levels = lvls, ordered = TRUE)
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class(x) <- c('mic', 'ordered', 'factor')
x
}
}
#' @rdname as.mic
#' @export
#' @importFrom dplyr %>%
is.mic <- function(x) {
class(x) %>% identical(c('mic', 'ordered', 'factor'))
}
#' @exportMethod as.double.mic
#' @export
#' @noRd
as.double.mic <- function(x, ...) {
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as.double(gsub('(<|=|>)+', '', as.character(x)))
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}
#' @exportMethod as.integer.mic
#' @export
#' @noRd
as.integer.mic <- function(x, ...) {
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as.integer(gsub('(<|=|>)+', '', as.character(x)))
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}
#' @exportMethod as.numeric.mic
#' @export
#' @noRd
as.numeric.mic <- function(x, ...) {
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as.numeric(gsub('(<|=|>)+', '', as.character(x)))
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}
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#' @exportMethod droplevels.mic
#' @export
#' @noRd
droplevels.mic <- function(x, exclude = if(anyNA(levels(x))) NULL else NA, ...) {
x <- droplevels.factor(x, exclude = exclude, ...)
class(x) <- c('mic', 'ordered', 'factor')
x
}
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#' @exportMethod print.mic
#' @export
#' @importFrom dplyr %>% tibble group_by summarise pull
#' @noRd
print.mic <- function(x, ...) {
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cat("Class 'mic'\n")
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print(as.character(x), quote = FALSE)
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}
#' @exportMethod summary.mic
#' @export
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#' @importFrom dplyr %>%
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#' @noRd
summary.mic <- function(object, ...) {
x <- object
n_total <- x %>% length()
x <- x[!is.na(x)]
n <- x %>% length()
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c(
"Class" = 'mic',
"<NA>" = n_total - n,
"Min." = sort(x)[1] %>% as.character(),
"Max." = sort(x)[n] %>% as.character()
)
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}
#' @exportMethod plot.mic
#' @export
#' @importFrom dplyr %>% group_by summarise
#' @importFrom graphics plot text
#' @noRd
plot.mic <- function(x, ...) {
x_name <- deparse(substitute(x))
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create_barplot_mic(x, x_name, ...)
}
#' @exportMethod barplot.mic
#' @export
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#' @importFrom graphics barplot axis
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#' @noRd
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barplot.mic <- function(height, ...) {
x_name <- deparse(substitute(height))
create_barplot_mic(height, x_name, ...)
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}
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#' @importFrom graphics barplot axis
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#' @importFrom dplyr %>% group_by summarise
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create_barplot_mic <- function(x, x_name, ...) {
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data <- data.frame(mic = droplevels(x), cnt = 1) %>%
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group_by(mic) %>%
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summarise(cnt = sum(cnt))
barplot(table(droplevels.factor(x)),
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ylab = 'Frequency',
xlab = 'MIC value',
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main = paste('MIC values of', x_name),
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axes = FALSE,
...)
axis(2, seq(0, max(data$cnt)))
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}