mirror of https://github.com/msberends/AMR.git
102 lines
4.5 KiB
R
102 lines
4.5 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/mo.R
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\name{as.mo}
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\alias{as.mo}
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\alias{mo}
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\alias{is.mo}
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\alias{guess_mo}
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\title{Transform to microorganism ID}
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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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}
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\usage{
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as.mo(x, Becker = FALSE, Lancefield = FALSE)
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is.mo(x)
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guess_mo(x, Becker = FALSE, Lancefield = FALSE)
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}
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\arguments{
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\item{x}{a character vector or a dataframe with one or two columns}
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\item{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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\item{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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}
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\value{
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Character (vector) with class \code{"mo"}. Unknown values will return \code{NA}.
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}
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\description{
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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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}
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\details{
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\code{guess_mo} is an alias of \code{as.mo}.
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Use the \code{\link{mo_property}} functions to get properties based on the returned mo, see Examples.
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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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\item{Something like \code{"p aer"} will return the ID of \emph{Pseudomonas aeruginosa} and not \emph{Pasteurella aerogenes}}
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\item{Something like \code{"stau"} or \code{"staaur"} will return the ID of \emph{Staphylococcus aureus} and not \emph{Staphylococcus auricularis}}
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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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}
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\examples{
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# These examples all return "STAAUR", the ID of S. aureus:
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as.mo("stau")
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as.mo("STAU")
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as.mo("staaur")
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as.mo("S. aureus")
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as.mo("S aureus")
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as.mo("Staphylococcus aureus")
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as.mo("MRSA") # Methicillin Resistant S. aureus
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as.mo("VISA") # Vancomycin Intermediate S. aureus
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as.mo("VRSA") # Vancomycin Resistant S. aureus
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# guess_mo is an alias of as.mo and works the same
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guess_mo("S. epidermidis") # will remain species: STAEPI
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guess_mo("S. epidermidis", Becker = TRUE) # will not remain species: STACNS
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guess_mo("S. pyogenes") # will remain species: STCAGA
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guess_mo("S. pyogenes", Lancefield = TRUE) # will not remain species: STCGRA
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# Use mo_* functions to get a specific property based on `mo`
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Ecoli <- as.mo("E. coli") # returns `ESCCOL`
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mo_genus(Ecoli) # returns "Escherichia"
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mo_gramstain(Ecoli) # returns "Negative rods"
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\dontrun{
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df$mo <- as.mo(df$microorganism_name)
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# the select function of tidyverse is also supported:
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library(dplyr)
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df$mo <- df \%>\%
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select(microorganism_name) \%>\%
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guess_mo()
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# and can even contain 2 columns, which is convenient for genus/species combinations:
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df$mo <- df \%>\%
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select(genus, species) \%>\%
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guess_mo()
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# same result:
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df <- df \%>\%
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mutate(mo = guess_mo(paste(genus, species)))
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}
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}
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\seealso{
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\code{\link{microorganisms}} for the dataframe that is being used to determine ID's.
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}
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\keyword{Becker}
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\keyword{Lancefield}
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\keyword{becker}
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\keyword{guess}
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\keyword{lancefield}
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\keyword{mo}
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