AMR/R/bactid.R

258 lines
9.6 KiB
R
Raw Normal View History

# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
# AUTHORS #
# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
# #
# LICENCE #
# This program 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 program 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 for more details. #
# ==================================================================== #
2018-07-23 14:14:03 +02:00
#' Transform to bacteria ID
#'
2018-07-23 14:14:03 +02:00
#' Use this function to determine a valid ID based on a genus (and species). This input can be a full name (like \code{"Staphylococcus aureus"}), an abbreviated name (like \code{"S. aureus"}), or just a genus. You could also \code{\link{select}} a genus and species column, zie Examples.
#' @param x a character vector or a dataframe with one or two columns
#' @rdname as.bactid
#' @details Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. For example:
#' \itemize{
#' \item{\code{"E. coli"} will return the ID of \emph{Escherichia coli} and not \emph{Entamoeba coli}, although the latter would alphabetically come first}
#' \item{\code{"H. influenzae"} will return the ID of \emph{Haemophilus influenzae} and not \emph{Haematobacter influenzae}}
#' \item{Something like \code{"p aer"} will return the ID of \emph{Pseudomonas aeruginosa} and not \emph{Pasteurella aerogenes}}
#' \item{Something like \code{"stau"} or \code{"staaur"} will return the ID of \emph{Staphylococcus aureus} and not \emph{Staphylococcus auricularis}}
#' }
#' Moreover, this function also supports ID's based on only Gram stain, when the species is not known. \cr
#' For example, \code{"Gram negative rods"} and \code{"GNR"} will both return the ID of a Gram negative rod: \code{GNR}.
#' @export
#' @importFrom dplyr %>% filter pull
2018-07-23 14:14:03 +02:00
#' @return Character (vector) with class \code{"bactid"}. Unknown values will return \code{NA}.
#' @seealso \code{\link{microorganisms}} for the dataframe that is being used to determine ID's.
#' @examples
#' # These examples all return "STAAUR", the ID of S. aureus:
2018-07-23 14:14:03 +02:00
#' as.bactid("stau")
#' as.bactid("STAU")
#' as.bactid("staaur")
#' as.bactid("S. aureus")
#' as.bactid("S aureus")
#' as.bactid("Staphylococcus aureus")
#' as.bactid("MRSA") # Methicillin Resistant S. aureus
#' as.bactid("VISA") # Vancomycin Intermediate S. aureus
#' as.bactid("VRSA") # Vancomycin Resistant S. aureus
#'
#' \dontrun{
2018-07-23 14:14:03 +02:00
#' df$bactid <- as.bactid(df$microorganism_name)
#'
#' # the select function of tidyverse is also supported:
2018-07-23 14:14:03 +02:00
#' library(dplyr)
#' df$bactid <- df %>%
#' select(microorganism_name) %>%
#' as.bactid()
#'
#' # and can even contain 2 columns, which is convenient for genus/species combinations:
2018-07-23 14:14:03 +02:00
#' df$bactid <- df %>%
#' select(genus, species) %>%
#' as.bactid()
#'
#' # same result:
2018-07-23 14:14:03 +02:00
#' df <- df %>%
#' mutate(bactid = paste(genus, species) %>%
#' as.bactid())
#' }
2018-07-23 14:14:03 +02:00
as.bactid <- function(x) {
failures <- character(0)
if (NCOL(x) == 2) {
# support tidyverse selection like: df %>% select(colA, colB)
# paste these columns together
x_vector <- vector("character", NROW(x))
for (i in 1:NROW(x)) {
x_vector[i] <- paste(pull(x[i,], 1), pull(x[i,], 2), sep = " ")
}
x <- x_vector
} else {
if (NCOL(x) > 2) {
stop('`x` can be 2 columns at most', call. = FALSE)
}
2018-07-23 14:14:03 +02:00
# support tidyverse selection like: df %>% select(colA)
if (!is.vector(x)) {
x <- pull(x, 1)
}
}
2018-07-23 14:14:03 +02:00
x.fullbackup <- x
# remove dots and other non-text in case of "E. coli" except spaces
2018-07-23 14:14:03 +02:00
x <- gsub("[^a-zA-Z0-9 ]+", "", x)
# but spaces before and after should be omitted
x <- trimws(x, which = "both")
2018-07-23 14:14:03 +02:00
x.backup <- x
# replace space by regex sign
x <- gsub(" ", ".*", x, fixed = TRUE)
# add start and stop
x_species <- paste(x, 'species')
x <- paste0('^', x, '$')
for (i in 1:length(x)) {
if (tolower(x[i]) == '^e.*coli$') {
# avoid detection of Entamoeba coli in case of E. coli
x[i] <- 'Escherichia coli'
}
if (tolower(x[i]) == '^h.*influenzae$') {
# avoid detection of Haematobacter influenzae in case of H. influenzae
x[i] <- 'Haemophilus influenzae'
}
if (tolower(x[i]) == '^st.*au$'
| tolower(x[i]) == '^stau$'
| tolower(x[i]) == '^staaur$') {
# avoid detection of Staphylococcus auricularis in case of S. aureus
x[i] <- 'Staphylococcus aureus'
}
if (tolower(x[i]) == '^p.*aer$') {
# avoid detection of Pasteurella aerogenes in case of Pseudomonas aeruginosa
x[i] <- 'Pseudomonas aeruginosa'
}
2018-07-23 14:14:03 +02:00
if (tolower(x[i]) %like% 'coagulase'
| tolower(x[i]) %like% 'cns'
| tolower(x[i]) %like% 'cons') {
# coerce S. coagulase negative, also as CNS and CoNS
x[i] <- 'Coagulase Negative Staphylococcus (CNS)'
}
# translate known trivial names to genus+species
2018-07-23 14:14:03 +02:00
if (!is.na(x.backup[i])) {
if (toupper(x.backup[i]) == 'MRSA'
| toupper(x.backup[i]) == 'VISA'
| toupper(x.backup[i]) == 'VRSA') {
x[i] <- 'Staphylococcus aureus'
}
2018-07-23 14:14:03 +02:00
if (toupper(x.backup[i]) == 'MRSE') {
x[i] <- 'Staphylococcus epidermidis'
}
2018-07-23 14:14:03 +02:00
if (toupper(x.backup[i]) == 'VRE') {
x[i] <- 'Enterococcus'
}
2018-07-23 14:14:03 +02:00
if (toupper(x.backup[i]) == 'MRPA') {
# multi resistant P. aeruginosa
x[i] <- 'Pseudomonas aeruginosa'
}
2018-07-23 14:14:03 +02:00
if (toupper(x.backup[i]) == 'PISP'
| toupper(x.backup[i]) == 'PRSP') {
# peni resistant S. pneumoniae
x[i] <- 'Streptococcus pneumoniae'
}
2018-07-23 14:14:03 +02:00
if (toupper(x.backup[i]) == 'VISP'
| toupper(x.backup[i]) == 'VRSP') {
# vanco resistant S. pneumoniae
x[i] <- 'Streptococcus pneumoniae'
}
}
# let's try the ID's first
2018-07-23 14:14:03 +02:00
found <- AMR::microorganisms %>% filter(bactid == x.backup[i])
if (nrow(found) == 0) {
# now try exact match
found <- AMR::microorganisms %>% filter(fullname == x[i])
}
if (nrow(found) == 0) {
# try any match
found <- AMR::microorganisms %>% filter(fullname %like% x[i])
}
if (nrow(found) == 0) {
# try exact match of only genus, with 'species' attached
# (e.g. this prevents Streptococcus for becoming Peptostreptococcus, since "p" < "s")
found <- AMR::microorganisms %>% filter(fullname == x_species[i])
}
if (nrow(found) == 0) {
# try any match of only genus, with 'species' attached
found <- AMR::microorganisms %>% filter(fullname %like% x_species[i])
}
if (nrow(found) == 0) {
# search for GLIMS code
2018-07-23 14:14:03 +02:00
if (toupper(x.backup[i]) %in% toupper(AMR::microorganisms.umcg$mocode)) {
found <- AMR::microorganisms.umcg %>% filter(toupper(mocode) == toupper(x.backup[i]))
}
}
if (nrow(found) == 0) {
# try splitting of characters and then find ID
# like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus
x_split <- x
2018-07-23 14:14:03 +02:00
x_length <- nchar(x.backup[i])
x_split[i] <- paste0(x.backup[i] %>% substr(1, x_length / 2) %>% trimws(),
'.* ',
2018-07-23 14:14:03 +02:00
x.backup[i] %>% substr((x_length / 2) + 1, x_length) %>% trimws())
found <- AMR::microorganisms %>% filter(fullname %like% paste0('^', x_split[i]))
}
if (nrow(found) == 0) {
# try any match with text before and after original search string
# so "negative rods" will be "GNR"
2018-07-23 14:14:03 +02:00
if (x.backup[i] %like% "^Gram") {
x.backup[i] <- gsub("^Gram", "", x.backup[i], ignore.case = TRUE)
# remove leading and trailing spaces again
2018-07-23 14:14:03 +02:00
x.backup[i] <- trimws(x.backup[i], which = "both")
}
2018-07-23 14:14:03 +02:00
if (!is.na(x.backup[i])) {
found <- AMR::microorganisms %>% filter(fullname %like% x.backup[i])
}
}
2018-07-23 14:14:03 +02:00
if (nrow(found) != 0 & x.backup[i] != "") {
x[i] <- as.character(found[1, 'bactid'])
} else {
2018-07-23 14:14:03 +02:00
x[i] <- NA_character_
failures <- c(failures, x.fullbackup[i])
}
}
2018-07-23 14:14:03 +02:00
failures <- failures[!failures %in% c(NA, NULL, NaN)]
if (length(failures) > 0) {
warning("These values could not be coerced to a valid bactid: ",
paste('"', unique(failures), '"', sep = "", collapse = ', '),
".",
call. = FALSE)
}
class(x) <- "bactid"
attr(x, 'package') <- 'AMR'
x
}
2018-07-23 14:14:03 +02:00
#' @rdname as.bactid
#' @export
guess_bactid <- as.bactid
#' @rdname as.bactid
#' @export
is.bactid <- function(x) {
identical(class(x), "bactid")
}
#' @exportMethod print.bactid
#' @export
#' @noRd
print.bactid <- function(x, ...) {
cat("Class 'bactid'\n")
print.default(as.character(x), quote = FALSE)
}
#' @exportMethod as.data.frame.bactid
#' @export
#' @noRd
as.data.frame.bactid <- function (x, ...) {
# same as as.data.frame.character but with removed stringsAsFactors
nm <- paste(deparse(substitute(x), width.cutoff = 500L),
collapse = " ")
if (!"nm" %in% names(list(...))) {
as.data.frame.vector(x, ..., nm = nm)
} else {
as.data.frame.vector(x, ...)
}
}