mirror of https://github.com/msberends/AMR.git
443 lines
16 KiB
R
443 lines
16 KiB
R
# ==================================================================== #
|
||
# 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. #
|
||
# ==================================================================== #
|
||
|
||
#' Transform to microorganism ID
|
||
#'
|
||
#' 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
|
||
#' @param Becker a logical to indicate whether \emph{Staphylococci} should be categorised into Coagulase Negative \emph{Staphylococci} ("CoNS") and Coagulase Positive \emph{Staphylococci} ("CoPS") instead of their own species, according to Karsten Becker \emph{et al.} [1]. This excludes \emph{Staphylococcus aureus} at default, use \code{Becker = "all"} to also categorise \emph{S. aureus} as "CoPS".
|
||
#' @param Lancefield a logical to indicate whether beta-haemolytic \emph{Streptococci} should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield [2]. These \emph{Streptococci} will be categorised in their first group, i.e. \emph{Streptococcus dysgalactiae} will be group C, although officially it was also categorised into groups G and L. Groups D and E will be ignored, since they are \emph{Enterococci}.
|
||
#' @rdname as.mo
|
||
#' @aliases mo
|
||
#' @keywords mo Becker becker Lancefield lancefield guess
|
||
#' @details \code{guess_mo} is an alias of \code{as.mo}.
|
||
#'
|
||
#' Use the \code{\link{mo_property}} functions to get properties based on the returned mo, see Examples.
|
||
#'
|
||
#' Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. These are:
|
||
#' \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}.
|
||
#' @source
|
||
#' [1] Becker K \emph{et al.} \strong{Coagulase-Negative Staphylococci}. 2014. Clin Microbiol Rev. 27(4): 870–926. \cr
|
||
#' \url{https://dx.doi.org/10.1128/CMR.00109-13} \cr
|
||
#' [2] Lancefield RC \strong{A serological differentiation of human and other groups of hemolytic streptococci}. 1933. J Exp Med. 57(4): 571–95. \cr
|
||
#' \url{https://dx.doi.org/10.1084/jem.57.4.571}
|
||
#' @export
|
||
#' @importFrom dplyr %>% pull left_join
|
||
#' @return Character (vector) with class \code{"mo"}. 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:
|
||
#' as.mo("stau")
|
||
#' as.mo("STAU")
|
||
#' as.mo("staaur")
|
||
#' as.mo("S. aureus")
|
||
#' as.mo("S aureus")
|
||
#' as.mo("Staphylococcus aureus")
|
||
#' as.mo("MRSA") # Methicillin Resistant S. aureus
|
||
#' as.mo("VISA") # Vancomycin Intermediate S. aureus
|
||
#' as.mo("VRSA") # Vancomycin Resistant S. aureus
|
||
#'
|
||
#' # guess_mo is an alias of as.mo and works the same
|
||
#' guess_mo("S. epidermidis") # will remain species: STAEPI
|
||
#' guess_mo("S. epidermidis", Becker = TRUE) # will not remain species: STACNS
|
||
#'
|
||
#' guess_mo("S. pyogenes") # will remain species: STCAGA
|
||
#' guess_mo("S. pyogenes", Lancefield = TRUE) # will not remain species: STCGRA
|
||
#'
|
||
#' # Use mo_* functions to get a specific property based on `mo`
|
||
#' Ecoli <- as.mo("E. coli") # returns `ESCCOL`
|
||
#' mo_genus(Ecoli) # returns "Escherichia"
|
||
#' mo_gramstain(Ecoli) # returns "Negative rods"
|
||
#'
|
||
#' \dontrun{
|
||
#' df$mo <- as.mo(df$microorganism_name)
|
||
#'
|
||
#' # the select function of tidyverse is also supported:
|
||
#' library(dplyr)
|
||
#' df$mo <- df %>%
|
||
#' select(microorganism_name) %>%
|
||
#' guess_mo()
|
||
#'
|
||
#' # and can even contain 2 columns, which is convenient for genus/species combinations:
|
||
#' df$mo <- df %>%
|
||
#' select(genus, species) %>%
|
||
#' guess_mo()
|
||
#'
|
||
#' # same result:
|
||
#' df <- df %>%
|
||
#' mutate(mo = guess_mo(paste(genus, species)))
|
||
#' }
|
||
as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
|
||
|
||
|
||
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)
|
||
}
|
||
}
|
||
|
||
MOs <- AMR::microorganisms %>% filter(!mo %like% '^_FAM') # dont search in those
|
||
failures <- character(0)
|
||
x_input <- x
|
||
|
||
# only check the uniques, which is way faster
|
||
x <- unique(x)
|
||
|
||
x_backup <- x
|
||
# remove dots and other non-text in case of "E. coli" except spaces
|
||
x <- gsub("[^a-zA-Z0-9 ]+", "", x)
|
||
# but spaces before and after should be omitted
|
||
x <- trimws(x, which = "both")
|
||
x_trimmed <- x
|
||
# replace space by regex sign
|
||
x_withspaces <- gsub(" ", ".* ", x, fixed = TRUE)
|
||
x <- gsub(" ", ".*", x, fixed = TRUE)
|
||
# for species
|
||
x_species <- paste(x, 'species')
|
||
# add start en stop regex
|
||
x <- paste0('^', x, '$')
|
||
x_withspaces <- paste0('^', x_withspaces, '$')
|
||
|
||
for (i in 1:length(x)) {
|
||
|
||
if (Becker == TRUE | Becker == "all") {
|
||
mo <- suppressWarnings(guess_mo(x_backup[i]))
|
||
if (mo %like% '^STA') {
|
||
# See Source. It's this figure:
|
||
# https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4187637/figure/F3/
|
||
species <- left_join_microorganisms(mo)$species
|
||
if (species %in% c("arlettae", "auricularis", "capitis",
|
||
"caprae", "carnosus", "cohnii", "condimenti",
|
||
"devriesei", "epidermidis", "equorum",
|
||
"fleurettii", "gallinarum", "haemolyticus",
|
||
"hominis", "jettensis", "kloosii", "lentus",
|
||
"lugdunensis", "massiliensis", "microti",
|
||
"muscae", "nepalensis", "pasteuri", "petrasii",
|
||
"pettenkoferi", "piscifermentans", "rostri",
|
||
"saccharolyticus", "saprophyticus", "sciuri",
|
||
"stepanovicii", "simulans", "succinus",
|
||
"vitulinus", "warneri", "xylosus")) {
|
||
x[i] <- "STACNS"
|
||
next
|
||
} else if ((Becker == "all" & species == "aureus")
|
||
| species %in% c("simiae", "agnetis", "chromogenes",
|
||
"delphini", "felis", "lutrae",
|
||
"hyicus", "intermedius",
|
||
"pseudintermedius", "pseudointermedius",
|
||
"schleiferi")) {
|
||
x[i] <- "STACPS"
|
||
next
|
||
}
|
||
}
|
||
}
|
||
|
||
if (Lancefield == TRUE) {
|
||
mo <- suppressWarnings(guess_mo(x_backup[i]))
|
||
if (mo %like% '^STC') {
|
||
# See Source
|
||
species <- left_join_microorganisms(mo)$species
|
||
if (species == "pyogenes") {
|
||
x[i] <- "STCGRA"
|
||
next
|
||
}
|
||
if (species == "agalactiae") {
|
||
x[i] <- "STCGRB"
|
||
next
|
||
}
|
||
if (species %in% c("equisimilis", "equi",
|
||
"zooepidemicus", "dysgalactiae")) {
|
||
x[i] <- "STCGRC"
|
||
next
|
||
}
|
||
if (species == "anginosus") {
|
||
x[i] <- "STCGRF"
|
||
next
|
||
}
|
||
if (species == "sanguis") {
|
||
x[i] <- "STCGRH"
|
||
next
|
||
}
|
||
if (species == "salivarius") {
|
||
x[i] <- "STCGRK"
|
||
next
|
||
}
|
||
}
|
||
}
|
||
|
||
if (identical(x_trimmed[i], "")) {
|
||
# empty values
|
||
x[i] <- NA
|
||
failures <- c(failures, x_backup[i])
|
||
next
|
||
}
|
||
if (x_backup[i] %in% AMR::microorganisms$mo) {
|
||
# is already a valid mo
|
||
x[i] <- x_backup[i]
|
||
next
|
||
}
|
||
if (x_trimmed[i] %in% AMR::microorganisms$mo) {
|
||
# is already a valid mo
|
||
x[i] <- x_trimmed[i]
|
||
next
|
||
}
|
||
|
||
if (tolower(x[i]) == '^e.*coli$') {
|
||
# avoid detection of Entamoeba coli in case of E. coli
|
||
x[i] <- 'ESCCOL'
|
||
next
|
||
}
|
||
if (tolower(x[i]) == '^h.*influenzae$') {
|
||
# avoid detection of Haematobacter influenzae in case of H. influenzae
|
||
x[i] <- 'HAEINF'
|
||
next
|
||
}
|
||
if (tolower(x[i]) == '^st.*au$'
|
||
| tolower(x[i]) == '^stau$'
|
||
| tolower(x[i]) == '^staaur$') {
|
||
# avoid detection of Staphylococcus auricularis in case of S. aureus
|
||
x[i] <- 'STAAUR'
|
||
next
|
||
}
|
||
if (tolower(x[i]) == '^p.*aer$') {
|
||
# avoid detection of Pasteurella aerogenes in case of Pseudomonas aeruginosa
|
||
x[i] <- 'PSEAER'
|
||
next
|
||
}
|
||
if (tolower(x[i]) %like% 'coagulase negative'
|
||
| tolower(x[i]) %like% 'cns'
|
||
| tolower(x[i]) %like% 'cons') {
|
||
# coerce S. coagulase negative, also as CNS and CoNS
|
||
x[i] <- 'STACNS'
|
||
next
|
||
}
|
||
|
||
# translate known trivial names to genus+species
|
||
if (!is.na(x_trimmed[i])) {
|
||
if (toupper(x_trimmed[i]) == 'MRSA'
|
||
| toupper(x_trimmed[i]) == 'VISA'
|
||
| toupper(x_trimmed[i]) == 'VRSA') {
|
||
x[i] <- 'STAAUR'
|
||
next
|
||
}
|
||
if (toupper(x_trimmed[i]) == 'MRSE') {
|
||
x[i] <- 'STAEPI'
|
||
next
|
||
}
|
||
if (toupper(x_trimmed[i]) == 'VRE') {
|
||
x[i] <- 'ENC'
|
||
next
|
||
}
|
||
if (toupper(x_trimmed[i]) == 'MRPA') {
|
||
# multi resistant P. aeruginosa
|
||
x[i] <- 'PSEAER'
|
||
next
|
||
}
|
||
if (toupper(x_trimmed[i]) %in% c('PISP', 'PRSP', 'VISP', 'VRSP')) {
|
||
# peni R, peni I, vanco I, vanco R: S. pneumoniae
|
||
x[i] <- 'STCPNE'
|
||
next
|
||
}
|
||
}
|
||
|
||
# try any match keeping spaces
|
||
found <- MOs[which(MOs$fullname %like% x_withspaces[i]),]$mo
|
||
if (length(found) > 0) {
|
||
x[i] <- found[1L]
|
||
next
|
||
}
|
||
|
||
# try any match diregarding spaces
|
||
found <- MOs[which(MOs$fullname %like% x[i]),]$mo
|
||
if (length(found) > 0) {
|
||
x[i] <- found[1L]
|
||
next
|
||
}
|
||
|
||
# try exact match of only genus, with 'species' attached
|
||
# (this prevents Streptococcus from becoming Peptostreptococcus, since "p" < "s")
|
||
found <- MOs[which(MOs$fullname == x_species[i]),]$mo
|
||
if (length(found) > 0) {
|
||
x[i] <- found[1L]
|
||
next
|
||
}
|
||
|
||
# try any match of only genus, with 'species' attached
|
||
found <- MOs[which(MOs$fullname %like% x_species[i]),]$mo
|
||
if (length(found) > 0) {
|
||
x[i] <- found[1L]
|
||
next
|
||
}
|
||
|
||
# search for GLIMS code
|
||
found <- AMR::microorganisms.umcg[which(toupper(AMR::microorganisms.umcg$umcg) == toupper(x_trimmed[i])),]$mo
|
||
if (length(found) > 0) {
|
||
x[i] <- found[1L]
|
||
next
|
||
}
|
||
|
||
# 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_trimmed[i])
|
||
x_split[i] <- paste0(x_trimmed[i] %>% substr(1, x_length / 2) %>% trimws(),
|
||
'.* ',
|
||
x_trimmed[i] %>% substr((x_length / 2) + 1, x_length) %>% trimws())
|
||
found <- MOs[which(MOs$fullname %like% paste0('^', x_split[i])),]$mo
|
||
if (length(found) > 0) {
|
||
x[i] <- found[1L]
|
||
next
|
||
}
|
||
|
||
# try any match with text before and after original search string
|
||
# so "negative rods" will be "GNR"
|
||
if (x_trimmed[i] %like% "^Gram") {
|
||
x_trimmed[i] <- gsub("^Gram", "", x_trimmed[i], ignore.case = TRUE)
|
||
# remove leading and trailing spaces again
|
||
x_trimmed[i] <- trimws(x_trimmed[i], which = "both")
|
||
}
|
||
if (!is.na(x_trimmed[i])) {
|
||
found <- MOs[which(MOs$fullname %like% x_trimmed[i]),]$mo
|
||
if (length(found) > 0) {
|
||
x[i] <- found[1L]
|
||
next
|
||
}
|
||
}
|
||
|
||
# not found
|
||
x[i] <- NA_character_
|
||
failures <- c(failures, x_backup[i])
|
||
|
||
}
|
||
|
||
failures <- failures[!failures %in% c(NA, NULL, NaN)]
|
||
if (length(failures) > 0) {
|
||
warning("These values could not be coerced to a valid mo: ",
|
||
paste('"', unique(failures), '"', sep = "", collapse = ', '),
|
||
".",
|
||
call. = FALSE)
|
||
}
|
||
|
||
# left join the found results to the original input values (x_input)
|
||
df_found <- data.frame(input = as.character(unique(x_input)),
|
||
found = x,
|
||
stringsAsFactors = FALSE)
|
||
df_input <- data.frame(input = as.character(x_input),
|
||
stringsAsFactors = FALSE)
|
||
|
||
x <- df_input %>%
|
||
left_join(df_found,
|
||
by = "input") %>%
|
||
pull(found)
|
||
|
||
class(x) <- "mo"
|
||
attr(x, 'package') <- 'AMR'
|
||
x
|
||
}
|
||
|
||
#' @rdname as.mo
|
||
#' @export
|
||
is.mo <- function(x) {
|
||
# bactid for older releases
|
||
# remove when is.bactid will be removed
|
||
identical(class(x), "mo") | identical(class(x), "bactid")
|
||
}
|
||
|
||
#' @rdname as.mo
|
||
#' @export
|
||
guess_mo <- as.mo
|
||
|
||
#' @exportMethod print.mo
|
||
#' @export
|
||
#' @noRd
|
||
print.mo <- function(x, ...) {
|
||
cat("Class 'mo'\n")
|
||
print.default(as.character(x), quote = FALSE)
|
||
}
|
||
|
||
#' @exportMethod as.data.frame.mo
|
||
#' @export
|
||
#' @noRd
|
||
as.data.frame.mo <- 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, ...)
|
||
}
|
||
}
|
||
|
||
#' @exportMethod pull.mo
|
||
#' @export
|
||
#' @importFrom dplyr pull
|
||
#' @noRd
|
||
pull.mo <- function(.data, ...) {
|
||
pull(as.data.frame(.data), ...)
|
||
}
|
||
|
||
#' @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, ...)
|
||
}
|
||
}
|
||
|
||
#' @exportMethod pull.bactid
|
||
#' @export
|
||
#' @importFrom dplyr pull
|
||
#' @noRd
|
||
pull.bactid <- function(.data, ...) {
|
||
pull(as.data.frame(.data), ...)
|
||
}
|