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Becker classification
Lancefield classification Added Lancefield groups to `microorganisms` data set
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100
R/bactid.R
100
R/bactid.R
@ -20,10 +20,12 @@
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#'
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#' 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.
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#' @param x a character vector or a dataframe with one or two columns
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#' @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".
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#' @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}.
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#' @rdname as.bactid
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#' @details \code{guess_bactid} does exactly the same as \code{as.bactid}.
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#' @details \code{guess_bactid} is an alias of \code{as.bactid}.
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#'
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#' Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. For example:
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#' Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. These are:
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#' \itemize{
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#' \item{\code{"E. coli"} will return the ID of \emph{Escherichia coli} and not \emph{Entamoeba coli}, although the latter would alphabetically come first}
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#' \item{\code{"H. influenzae"} will return the ID of \emph{Haemophilus influenzae} and not \emph{Haematobacter influenzae}}
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@ -32,6 +34,11 @@
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#' }
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#' Moreover, this function also supports ID's based on only Gram stain, when the species is not known. \cr
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#' For example, \code{"Gram negative rods"} and \code{"GNR"} will both return the ID of a Gram negative rod: \code{GNR}.
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#' @source
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#' [1] Becker K \emph{et al.} \strong{Coagulase-Negative Staphylococci}. 2014. Clin Microbiol Rev. 27(4): 870–926. \cr
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#' \url{https://dx.doi.org/10.1128/CMR.00109-13} \cr
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#' [2] Lancefield RC \strong{A serological differentiation of human and other groups of hemolytic streptococci}. 1933. J Exp Med. 57(4): 571–95. \cr
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#' \url{https://dx.doi.org/10.1084/jem.57.4.571}
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#' @export
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#' @importFrom dplyr %>% filter pull
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#' @return Character (vector) with class \code{"bactid"}. Unknown values will return \code{NA}.
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@ -48,6 +55,12 @@
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#' as.bactid("VISA") # Vancomycin Intermediate S. aureus
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#' as.bactid("VRSA") # Vancomycin Resistant S. aureus
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#'
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#' guess_bactid("S. epidermidis") # will remain species: STAEPI
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#' guess_bactid("S. epidermidis", Becker = TRUE) # will not remain species: STACNS
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#'
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#' guess_bactid("S. pyogenes") # will remain species: STCAGA
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#' guess_bactid("S. pyogenes", Lancefield = TRUE) # will not remain species: STCGRA
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#'
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#' \dontrun{
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#' df$bactid <- as.bactid(df$microorganism_name)
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#'
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@ -66,7 +79,7 @@
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#' df <- df %>%
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#' mutate(bactid = guess_bactid(paste(genus, species)))
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#' }
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as.bactid <- function(x) {
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as.bactid <- function(x, Becker = FALSE, Lancefield = FALSE) {
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failures <- character(0)
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@ -96,13 +109,79 @@ as.bactid <- function(x) {
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x <- trimws(x, which = "both")
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x.backup <- x
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# replace space by regex sign
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x_withspaces <- gsub(" ", ".* ", x, fixed = TRUE)
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x <- gsub(" ", ".*", x, fixed = TRUE)
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# add start and stop
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# for species
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x_species <- paste(x, 'species')
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# add start en stop regex
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x <- paste0('^', x, '$')
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x_withspaces <- paste0('^', x_withspaces, '$')
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for (i in 1:length(x)) {
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if (Becker == TRUE | Becker == "all") {
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mo <- suppressWarnings(guess_bactid(x.fullbackup[i]))
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if (mo %like% '^STA') {
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# See Source. It's this figure:
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# https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4187637/figure/F3/
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species <- left_join_microorganisms(mo)$species
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if (species %in% c("arlettae", "auricularis", "capitis",
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"caprae", "carnosus", "cohnii", "condimene",
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"devriesei", "epidermidis", "equorum",
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"fleurettii", "gallinarum", "haemolyticus",
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"hominis", "jettensis", "kloosii", "lentus",
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"lugdunensis", "massiliensis", "microti",
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"muscae", "nepalensis", "pasteuri", "perrasii",
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"pettenkoleri", "piscifermentans", "rostri",
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"saccharott", "saprophyticus", "sciuri",
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"siepanovicii", "simulans", "succinus",
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"vitulinus", "warneri", "xylosus")) {
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x[i] <- "STACNS"
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next
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} else if ((Becker == "all" & species == "aureus")
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| species %in% c("simiae", "agnetis", "chromogenes",
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"delphirul", "felis", "futrae",
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"hyicus", "intermedius",
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"pseudointermedius", "schleiferi")) {
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x[i] <- "STACPS"
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next
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}
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}
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}
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if (Lancefield == TRUE) {
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mo <- suppressWarnings(guess_bactid(x.fullbackup[i]))
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if (mo %like% '^STC') {
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# See Source
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species <- left_join_microorganisms(mo)$species
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if (species == "pyogenes") {
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x[i] <- "STCGRA"
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next
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}
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if (species == "agalactiae") {
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x[i] <- "STCGRB"
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next
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}
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if (species %in% c("equisimilis", "equi",
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"zooepidemicus", "dysgalactiae")) {
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x[i] <- "STCGRC"
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next
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}
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if (species == "anginosus") {
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x[i] <- "STCGRF"
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next
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}
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if (species == "sanguis") {
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x[i] <- "STCGRH"
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next
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}
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if (species == "salivarius") {
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x[i] <- "STCGRK"
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next
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}
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}
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}
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if (identical(x.backup[i], "")) {
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# empty values
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x[i] <- NA
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@ -142,7 +221,7 @@ as.bactid <- function(x) {
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x[i] <- 'PSEAER'
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next
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}
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if (tolower(x[i]) %like% 'coagulase'
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if (tolower(x[i]) %like% 'coagulase negative'
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| tolower(x[i]) %like% 'cns'
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| tolower(x[i]) %like% 'cons') {
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# coerce S. coagulase negative, also as CNS and CoNS
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@ -192,7 +271,14 @@ as.bactid <- function(x) {
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next
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}
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# try any match
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# try any match keeping spaces
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found <- AMR::microorganisms[which(AMR::microorganisms$fullname %like% x_withspaces[i]),]$bactid
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if (length(found) > 0) {
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x[i] <- found[1L]
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next
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}
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# try any match diregarding spaces
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found <- AMR::microorganisms[which(AMR::microorganisms$fullname %like% x[i]),]$bactid
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if (length(found) > 0) {
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x[i] <- found[1L]
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@ -200,7 +286,7 @@ as.bactid <- function(x) {
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}
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# try exact match of only genus, with 'species' attached
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# (e.g. this prevents Streptococcus for becoming Peptostreptococcus, since "p" < "s")
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# (this prevents Streptococcus from becoming Peptostreptococcus, since "p" < "s")
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found <- AMR::microorganisms[which(AMR::microorganisms$fullname == x_species[i]),]$bactid
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if (length(found) > 0) {
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x[i] <- found[1L]
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4
R/data.R
4
R/data.R
@ -236,8 +236,8 @@
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#' Dataset with ~2500 microorganisms
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#'
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#' A dataset containing 2453 microorganisms. MO codes of the UMCG can be looked up using \code{\link{microorganisms.umcg}}.
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#' @format A data.frame with 2453 observations and 12 variables:
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#' A dataset containing 2456 microorganisms. MO codes of the UMCG can be looked up using \code{\link{microorganisms.umcg}}.
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#' @format A data.frame with 2456 observations and 12 variables:
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#' \describe{
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#' \item{\code{bactid}}{ID of microorganism}
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#' \item{\code{bactsys}}{Bactsyscode of microorganism}
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