AMR/R/guess_bactid.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 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. #
# ==================================================================== #
#' Find bacteria ID based on genus/species
#'
#' Use this function to determine a valid ID based on a genus (and species). This input could 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 character vector or a dataframe with one or two columns
#' @export
#' @importFrom dplyr %>% filter pull
#' @return Character (vector).
#' @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:
#' guess_bactid("stau")
#' guess_bactid("STAU")
#' guess_bactid("staaur")
#' guess_bactid("S. aureus")
#' guess_bactid("S aureus")
#' guess_bactid("Staphylococcus aureus")
#' guess_bactid("MRSA") # Methicillin-resistant S. aureus
#' guess_bactid("VISA") # Vancomycin Intermediate S. aureus
#'
#' \dontrun{
#' df$bactid <- guess_bactid(df$microorganism_name)
#'
#' # the select function of tidyverse is also supported:
#' df$bactid <- df %>% select(microorganism_name) %>% guess_bactid()
#'
#' # and can even contain 2 columns, which is convenient for genus/species combinations:
#' df$bactid <- df %>% select(genus, species) %>% guess_bactid()
#' # same result:
2018-06-19 10:05:38 +02:00
#' df <- df %>% mutate(bactid = paste(genus, species)) %>% guess_bactid())
#' }
guess_bactid <- function(x) {
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)
}
# support tidyverse selection like: df %>% select(colA)
if (!is.vector(x)) {
x <- pull(x, 1)
}
}
# remove dots and other non-text in case of "E. coli" except spaces
x <- gsub("[^a-zA-Z ]+", "", x)
# but spaces before and after should be omitted
x <- trimws(x, which = "both")
x.bak <- 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$') {
# avoid detection of Pasteurella aerogenes in case of Pseudomonas aeruginosa
x[i] <- 'Pseudomonas aeruginosa'
}
# translate known trivial names to genus+species
if (!is.na(x.bak[i])) {
if (toupper(x.bak[i]) == 'MRSA'
| toupper(x.bak[i]) == 'VISA'
| toupper(x.bak[i]) == 'VRSA') {
x[i] <- 'Staphylococcus aureus'
}
if (toupper(x.bak[i]) == 'MRSE') {
x[i] <- 'Staphylococcus epidermidis'
}
if (toupper(x.bak[i]) == 'VRE') {
x[i] <- 'Enterococcus'
}
if (toupper(x.bak[i]) == 'MRPA') {
# multi resistant P. aeruginosa
x[i] <- 'Pseudomonas aeruginosa'
}
if (toupper(x.bak[i]) == 'PISP'
| toupper(x.bak[i]) == 'PRSP') {
# peni resistant S. pneumoniae
x[i] <- 'Streptococcus pneumoniae'
}
if (toupper(x.bak[i]) == 'VISP'
| toupper(x.bak[i]) == 'VRSP') {
# vanco resistant S. pneumoniae
x[i] <- 'Streptococcus pneumoniae'
}
}
# let's try the ID's first
found <- AMR::microorganisms %>% filter(bactid == x.bak[i])
if (nrow(found) == 0) {
# now try exact match
found <- AMR::microorganisms %>% filter(fullname == x[i])
}
if (nrow(found) == 0) {
# try any match
found <- AMR::microorganisms %>% filter(fullname %like% x[i])
}
if (nrow(found) == 0) {
# try exact match of only genus, with 'species' attached
# (e.g. this prevents Streptococcus for becoming Peptostreptococcus, since "p" < "s")
found <- AMR::microorganisms %>% filter(fullname == x_species[i])
}
if (nrow(found) == 0) {
# try any match of only genus, with 'species' attached
found <- AMR::microorganisms %>% filter(fullname %like% x_species[i])
}
if (nrow(found) == 0) {
# search for GLIMS code
if (toupper(x.bak[i]) %in% toupper(AMR::microorganisms.umcg$mocode)) {
found <- AMR::microorganisms.umcg %>% filter(toupper(mocode) == toupper(x.bak[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
x_length <- nchar(x.bak[i])
x_split[i] <- paste0(x.bak[i] %>% substr(1, x_length / 2) %>% trimws(),
'.* ',
x.bak[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"
if (x.bak[i] %like% "^Gram") {
x.bak[i] <- gsub("^Gram", "", x.bak[i], ignore.case = TRUE)
# remove leading and trailing spaces again
x.bak[i] <- trimws(x.bak[i], which = "both")
}
if (!is.na(x.bak[i])) {
found <- AMR::microorganisms %>% filter(fullname %like% x.bak[i])
}
}
if (nrow(found) != 0) {
x[i] <- as.character(found[1, 'bactid'])
} else {
x[i] <- ""
}
}
x
}