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Support for German and Spanish microorganism properties, cleanup
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@ -1,6 +1,6 @@
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Package: AMR
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Version: 0.3.0.9006
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Date: 2018-09-01
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Version: 0.3.0.9007
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Date: 2018-09-04
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Title: Antimicrobial Resistance Analysis
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Authors@R: c(
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person(
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@ -94,12 +94,10 @@ export(mo_family)
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export(mo_fullname)
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export(mo_genus)
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export(mo_gramstain)
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export(mo_gramstain_nl)
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export(mo_property)
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export(mo_species)
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export(mo_subspecies)
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export(mo_type)
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export(mo_type_nl)
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export(n_rsi)
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export(p.symbol)
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export(portion_I)
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10
NEWS.md
10
NEWS.md
@ -10,7 +10,15 @@
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* Column names of datasets `microorganisms` and `septic_patients`
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* All old syntaxes will still work with this version, but will throw warnings
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* Functions `as.atc` and `is.atc` to transform/look up antibiotic ATC codes as defined by the WHO. The existing function `guess_atc` is now an alias of `as.atc`.
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* Aliases for existing function `mo_property`: `mo_family`, `mo_genus`, `mo_species`, `mo_subspecies`, `mo_fullname`, `mo_type`, `mo_gramstain`, `mo_aerobic`, `mo_type_nl` and `mo_gramstain_nl`
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* Aliases for existing function `mo_property`: `mo_family`, `mo_genus`, `mo_species`, `mo_subspecies`, `mo_fullname`, `mo_aerobic`, `mo_type`, `mo_gramstain`. The last two functions have a `language` parameter, with support for Spanish, German and Dutch:
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```r
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mo_gramstain("E. coli")
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# [1] "Negative rods"
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mo_gramstain("E. coli", language = "de") # "de" = Deutsch / German
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# [1] "Negative Staebchen"
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mo_gramstain("E. coli", language = "es") # "es" = Español / Spanish
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# [1] "Bacilos negativos"
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```
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* Function `ab_property` and its aliases: `ab_official`, `ab_tradenames`, `ab_certe`, `ab_umcg`, `ab_official_nl` and `ab_trivial_nl`
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* Introduction to AMR as a vignette
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@ -36,7 +36,7 @@
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ab_property <- function(x, property = 'official') {
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property <- property[1]
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if (!property %in% colnames(antibiotics)) {
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stop("invalid property: ", property, " - use a column name of `antibiotics`")
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stop("invalid property: ", property, " - use a column name of the `antibiotics` data set")
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}
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if (!is.atc(x)) {
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x <- as.atc(x) # this will give a warning if x cannot be coerced
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4
R/atc.R
4
R/atc.R
@ -17,9 +17,9 @@
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# ==================================================================== #
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#' Find ATC code based on antibiotic property
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#' Transform to ATC code
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#'
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#' Use this function to determine the ATC code of one or more antibiotics. The dataset \code{\link{antibiotics}} will be searched for abbreviations, official names and trade names.
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#' Use this function to determine the ATC code of one or more antibiotics. The data set \code{\link{antibiotics}} will be searched for abbreviations, official names and trade names.
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#' @param x character vector to determine \code{ATC} code
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#' @rdname as.atc
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#' @aliases atc
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8
R/data.R
8
R/data.R
@ -123,7 +123,7 @@
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#' Data set with human pathogenic microorganisms
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#'
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#' A data set containing 2,664 (potential) human pathogenic microorganisms. MO codes can be looked up using \code{\link{guess_mo}}.
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#' @format A \code{\link{tibble}} with 2,664 observations and 12 variables:
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#' @format A \code{\link{tibble}} with 2,664 observations and 16 variables:
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#' \describe{
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#' \item{\code{mo}}{ID of microorganism}
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#' \item{\code{bactsys}}{Bactsyscode of microorganism}
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@ -132,11 +132,15 @@
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#' \item{\code{species}}{Species name of microorganism, like \code{"coli"}}
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#' \item{\code{subspecies}}{Subspecies name of bio-/serovar of microorganism, like \code{"EHEC"}}
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#' \item{\code{fullname}}{Full name, like \code{"Echerichia coli (EHEC)"}}
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#' \item{\code{aerobic}}{Logical whether bacteria is aerobic}
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#' \item{\code{type}}{Type of microorganism, like \code{"Bacteria"} and \code{"Fungus/yeast"}}
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#' \item{\code{gramstain}}{Gram of microorganism, like \code{"Negative rods"}}
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#' \item{\code{aerobic}}{Logical whether bacteria is aerobic}
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#' \item{\code{type_de}}{Type of microorganism in German, like \code{"Bakterien"} and \code{"Pilz/Hefe"}}
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#' \item{\code{gramstain_de}}{Gram of microorganism in German, like \code{"Negative Staebchen"}}
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#' \item{\code{type_nl}}{Type of microorganism in Dutch, like \code{"Bacterie"} and \code{"Schimmel/gist"}}
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#' \item{\code{gramstain_nl}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
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#' \item{\code{type_es}}{Type of microorganism in Spanish, like \code{"Bacteria"} and \code{"Hongo/levadura"}}
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#' \item{\code{gramstain_es}}{Gram of microorganism in Spanish, like \code{"Bacilos negativos"}}
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#' }
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# source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
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# new <- microorganisms %>% filter(genus == "Bacteroides") %>% .[1,]
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37
R/mo.R
37
R/mo.R
@ -19,15 +19,19 @@
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#' Transform to microorganism ID
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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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#' @param x a character vector or a \code{data.frame} 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].
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#'
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#' 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.
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#'
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#' This excludes \emph{Enterococci} at default (who are in group D), use \code{Lancefield = "all"} to also categorise all \emph{Enterococci} as group D.
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#' @rdname as.mo
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#' @aliases mo
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#' @keywords mo Becker becker Lancefield lancefield guess
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#' @details \code{guess_mo} is an alias of \code{as.mo}.
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#'
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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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#' Use the \code{\link{mo_property}} functions to get properties based on the returned code, see Examples.
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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. These are:
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#' \itemize{
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@ -39,10 +43,9 @@
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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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#' [1] Becker K \emph{et al.} \strong{Coagulase-Negative Staphylococci}. 2014. Clin Microbiol Rev. 27(4): 870–926. \url{https://dx.doi.org/10.1128/CMR.00109-13}
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#'
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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. \url{https://dx.doi.org/10.1084/jem.57.4.571}
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#' @export
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#' @importFrom dplyr %>% pull left_join
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#' @return Character (vector) with class \code{"mo"}. Unknown values will return \code{NA}.
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@ -63,7 +66,7 @@
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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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#'
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#' guess_mo("S. pyogenes") # will remain species: STCAGA
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#' guess_mo("S. pyogenes") # will remain species: STCPYO
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#' guess_mo("S. pyogenes", Lancefield = TRUE) # will not remain species: STCGRA
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#'
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#' # Use mo_* functions to get a specific property based on `mo`
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@ -177,10 +180,17 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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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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# coerce S. coagulase negative
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x[i] <- 'STACNS'
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next
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}
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if (tolower(x[i]) %like% 'coagulase positive'
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| tolower(x[i]) %like% 'cps'
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| tolower(x[i]) %like% 'cops') {
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# coerce S. coagulase positive
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x[i] <- 'STACPS'
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next
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}
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# translate known trivial names to genus+species
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if (!is.na(x_trimmed[i])) {
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@ -204,7 +214,7 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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next
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}
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if (toupper(x_trimmed[i]) %in% c('PISP', 'PRSP', 'VISP', 'VRSP')) {
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# peni R, peni I, vanco I, vanco R: S. pneumoniae
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# peni I, peni R, vanco I, vanco R: S. pneumoniae
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x[i] <- 'STCPNE'
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next
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}
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@ -327,7 +337,7 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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}
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}
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if (Lancefield == TRUE) {
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if (Lancefield == TRUE | Lancefield == "all") {
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# group A
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x[x == "STCPYO"] <- "STCGRA" # S. pyogenes
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# group B
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@ -338,6 +348,9 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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"zooepidemicus", "dysgalactiae")) %>%
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pull(mo)
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x[x %in% S_groupC] <- "STCGRC" # S. agalactiae
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if (Lancefield == "all") {
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x[substr(x, 1, 3) == "ENC"] <- "STCGRD" # all Enterococci
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}
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# group F
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x[x == "STCANG"] <- "STCGRF" # S. anginosus
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# group H
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130
R/mo_property.R
130
R/mo_property.R
@ -18,59 +18,80 @@
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#' Property of a microorganism
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#'
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#' Use these functions to return a specific property of a microorganism from the \code{\link{microorganisms}} data set, based on their \code{mo}. Get such an ID with \code{\link{as.mo}}.
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#' @param x a (vector of a) valid \code{\link{mo}} or any text that can be coerced to a valid microorganism code with \code{\link{as.mo}}
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#' Use these functions to return a specific property of a microorganism from the \code{\link{microorganisms}} data set. All input values will be evaluated internally with \code{\link{as.mo}}.
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#' @param x any (vector of) text that can be coerced to a valid microorganism code with \code{\link{as.mo}}
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#' @param property one of the column names of one of the \code{\link{microorganisms}} data set, like \code{"mo"}, \code{"bactsys"}, \code{"family"}, \code{"genus"}, \code{"species"}, \code{"fullname"}, \code{"gramstain"} and \code{"aerobic"}
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#' @inheritParams as.mo
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#' @param language language of the returned text, either one of \code{"en"} (English), \code{"de"} (German) or \code{"nl"} (Dutch)
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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. \url{https://dx.doi.org/10.1128/CMR.00109-13}
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#'
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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. \url{https://dx.doi.org/10.1084/jem.57.4.571}
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#' @rdname mo_property
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#' @export
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#' @importFrom dplyr %>% left_join pull
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#' @seealso \code{\link{microorganisms}}
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#' @examples
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#' # All properties
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#' mo_family("E. coli") # Enterobacteriaceae
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#' mo_genus("E. coli") # Escherichia
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#' mo_species("E. coli") # coli
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#' mo_subspecies("E. coli") # <NA>
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#' mo_fullname("E. coli") # Escherichia coli
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#' mo_type("E. coli") # Bacteria
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#' mo_gramstain("E. coli") # Negative rods
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#' mo_aerobic("E. coli") # TRUE
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#' mo_type_nl("E. coli") # Bacterie
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#' mo_gramstain_nl("E. coli") # Negatieve staven
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#' mo_family("E. coli") # "Enterobacteriaceae"
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#' mo_genus("E. coli") # "Escherichia"
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#' mo_species("E. coli") # "coli"
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#' mo_subspecies("E. coli") # <NA>
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#' mo_fullname("E. coli") # "Escherichia coli"
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#' mo_type("E. coli") # "Bacteria"
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#' mo_gramstain("E. coli") # "Negative rods"
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#' mo_aerobic("E. coli") # TRUE
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#'
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#' # language support for Spanish, German and Dutch
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#' mo_type("E. coli", "es") # "Bakteria"
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#' mo_type("E. coli", "de") # "Bakterien"
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#' mo_type("E. coli", "nl") # "Bacterie"
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#' mo_gramstain("E. coli", "es") # "Bacilos negativos"
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#' mo_gramstain("E. coli", "de") # "Negative Staebchen"
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#' mo_gramstain("E. coli", "nl") # "Negatieve staven"
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#'
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#'
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#' # Abbreviations known in the field
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#' mo_genus("EHEC") # Escherichia
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#' mo_species("EHEC") # coli
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#' mo_subspecies("EHEC") # EHEC
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#' mo_fullname("EHEC") # Escherichia coli (EHEC)
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#' mo_genus("MRSA") # "Staphylococcus"
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#' mo_species("MRSA") # "aureus"
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#' mo_gramstain("MRSA") # "Positive cocci"
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#'
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#' mo_genus("MRSA") # Staphylococcus
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#' mo_species("MRSA") # aureus
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#' mo_gramstain("MRSA") # Positive cocci
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#'
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#' mo_genus("VISA") # Staphylococcus
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#' mo_species("VISA") # aureus
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#' mo_genus("VISA") # "Staphylococcus"
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#' mo_species("VISA") # "aureus"
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#'
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#'
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#' # Known subspecies
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#' mo_genus("doylei") # Campylobacter
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#' mo_species("doylei") # jejuni
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#' mo_fullname("doylei") # Campylobacter jejuni (doylei)
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#' mo_genus("EHEC") # "Escherichia"
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#' mo_species("EHEC") # "coli"
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#' mo_subspecies("EHEC") # "EHEC"
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#' mo_fullname("EHEC") # "Escherichia coli (EHEC)"
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#'
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#' mo_genus("doylei") # "Campylobacter"
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#' mo_species("doylei") # "jejuni"
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#' mo_fullname("doylei") # "Campylobacter jejuni (doylei)"
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#'
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#' mo_fullname("K. pneu rh") # "Klebsiella pneumoniae (rhinoscleromatis)"
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#'
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#'
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#' # Anaerobic bacteria
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#' mo_genus("B. fragilis") # Bacteroides
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#' mo_species("B. fragilis") # fragilis
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#' mo_aerobic("B. fragilis") # FALSE
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mo_property <- function(x, property = 'fullname') {
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property <- property[1]
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#' mo_genus("B. fragilis") # "Bacteroides"
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#' mo_species("B. fragilis") # "fragilis"
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#' mo_aerobic("B. fragilis") # FALSE
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#'
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#'
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#' # Becker classification, see ?as.mo
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#' mo_fullname("S. epidermidis") # "Staphylococcus epidermidis"
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#' mo_fullname("S. epidermidis", Becker = TRUE) # "Coagulase Negative Staphylococcus (CoNS)"
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#'
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#' # Lancefield classification, see ?as.mo
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#' mo_fullname("S. pyogenes") # "Streptococcus pyogenes"
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#' mo_fullname("S. pyogenes", Lancefield = TRUE) # "Streptococcus group A"
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mo_property <- function(x, property = 'fullname', Becker = FALSE, Lancefield = FALSE) {
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property <- tolower(property[1])
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if (!property %in% colnames(microorganisms)) {
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stop("invalid property: ", property, " - use a column name of `microorganisms`")
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}
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if (!is.mo(x)) {
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x <- as.mo(x) # this will give a warning if x cannot be coerced
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stop("invalid property: ", property, " - use a column name of the `microorganisms` data set")
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}
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x <- as.mo(x = x, Becker = Becker, Lancefield = Lancefield) # this will give a warning if x cannot be coerced
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suppressWarnings(
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data.frame(mo = x, stringsAsFactors = FALSE) %>%
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left_join(AMR::microorganisms, by = "mo") %>%
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@ -92,32 +113,32 @@ mo_genus <- function(x) {
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#' @rdname mo_property
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#' @export
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mo_species <- function(x) {
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mo_property(x, "species")
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mo_species <- function(x, Becker = FALSE, Lancefield = FALSE) {
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mo_property(x, "species", Becker = Becker, Lancefield = Lancefield)
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}
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#' @rdname mo_property
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#' @export
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mo_subspecies <- function(x) {
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mo_property(x, "subspecies")
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mo_subspecies <- function(x, Becker = FALSE, Lancefield = FALSE) {
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mo_property(x, "subspecies", Becker = Becker, Lancefield = Lancefield)
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}
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#' @rdname mo_property
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#' @export
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mo_fullname <- function(x) {
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mo_property(x, "fullname")
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mo_fullname <- function(x, Becker = FALSE, Lancefield = FALSE) {
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mo_property(x, "fullname", Becker = Becker, Lancefield = Lancefield)
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}
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#' @rdname mo_property
|
||||
#' @export
|
||||
mo_type <- function(x) {
|
||||
mo_property(x, "type")
|
||||
mo_type <- function(x, language = "en") {
|
||||
mo_property(x, paste0("type", checklang(language)))
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_gramstain <- function(x) {
|
||||
mo_property(x, "gramstain")
|
||||
mo_gramstain <- function(x, language = "en") {
|
||||
mo_property(x, paste0("gramstain", checklang(language)))
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
@ -126,14 +147,15 @@ mo_aerobic <- function(x) {
|
||||
mo_property(x, "aerobic")
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_type_nl <- function(x) {
|
||||
mo_property(x, "type_nl")
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_gramstain_nl <- function(x) {
|
||||
mo_property(x, "gramstain_nl")
|
||||
checklang <- function(language) {
|
||||
language <- tolower(language[1])
|
||||
supported <- c("en", "de", "nl", "es")
|
||||
if (!language %in% c(NULL, "", supported)) {
|
||||
stop("invalid language: ", language, " - use one of ", paste0("'", sort(supported), "'", collapse = ", "), call. = FALSE)
|
||||
}
|
||||
if (language %in% c(NULL, "", "en")) {
|
||||
""
|
||||
} else {
|
||||
paste0("_", language)
|
||||
}
|
||||
}
|
||||
|
||||
@ -55,7 +55,7 @@ This `AMR` package basically does four important things:
|
||||
* Use `first_isolate` to identify the first isolates of every patient [using guidelines from the CLSI](https://clsi.org/standards/products/microbiology/documents/m39/) (Clinical and Laboratory Standards Institute).
|
||||
* You can also identify first *weighted* isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them.
|
||||
* Use `MDRO` (abbreviation of Multi Drug Resistant Organisms) to check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently, national guidelines for Germany and the Netherlands are supported.
|
||||
* The data set `microorganisms` contains the family, genus, species, subspecies, colloquial name and Gram stain of almost 3,000 potential human pathogenic microorganisms (bacteria, fungi/yeasts and parasites). This enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus`, `mo_family` or `mo_gramstain`. Since it uses `as.mo` internally, AI is supported. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. These functions can be used to add new variables to your data.
|
||||
* The data set `microorganisms` contains the family, genus, species, subspecies, colloquial name and Gram stain of almost 3,000 potential human pathogenic microorganisms (bacteria, fungi/yeasts and parasites). This enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus`, `mo_family` or `mo_gramstain`. As they use `as.mo` internally, they also use artificial intelligence. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. Some functions can return results in Spanish, German and Dutch. These functions can be used to add new variables to your data.
|
||||
* The data set `antibiotics` contains the ATC code, LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains a total of 298 trade names. Use functions like `ab_official` and `ab_tradenames` to look up values. As the `mo_*` functions use `as.mo` internally, the `ab_*` functions use `as.atc` internally so it uses AI to guess your expected result. For example, `ab_official("Fluclox")`, `ab_official("Floxapen")` and `ab_official("J01CF05")` will all return `"Flucloxacillin"`. These functions can again be used to add new variables to your data.
|
||||
|
||||
3. It **analyses the data** with convenient functions that use well-known methods.
|
||||
|
||||
Binary file not shown.
@ -5,7 +5,7 @@
|
||||
\alias{atc}
|
||||
\alias{guess_atc}
|
||||
\alias{is.atc}
|
||||
\title{Find ATC code based on antibiotic property}
|
||||
\title{Transform to ATC code}
|
||||
\usage{
|
||||
as.atc(x)
|
||||
|
||||
@ -20,7 +20,7 @@ is.atc(x)
|
||||
Character (vector) with class \code{"act"}. Unknown values will return \code{NA}.
|
||||
}
|
||||
\description{
|
||||
Use this function to determine the ATC code of one or more antibiotics. The dataset \code{\link{antibiotics}} will be searched for abbreviations, official names and trade names.
|
||||
Use this function to determine the ATC code of one or more antibiotics. The data set \code{\link{antibiotics}} will be searched for abbreviations, official names and trade names.
|
||||
}
|
||||
\details{
|
||||
Use the \code{\link{ab_property}} functions to get properties based on the returned ATC code, see Examples.
|
||||
|
||||
21
man/as.mo.Rd
21
man/as.mo.Rd
@ -7,10 +7,9 @@
|
||||
\alias{guess_mo}
|
||||
\title{Transform to microorganism ID}
|
||||
\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}
|
||||
[1] Becker K \emph{et al.} \strong{Coagulase-Negative Staphylococci}. 2014. Clin Microbiol Rev. 27(4): 870–926. \url{https://dx.doi.org/10.1128/CMR.00109-13}
|
||||
|
||||
[2] Lancefield RC \strong{A serological differentiation of human and other groups of hemolytic streptococci}. 1933. J Exp Med. 57(4): 571–95. \url{https://dx.doi.org/10.1084/jem.57.4.571}
|
||||
}
|
||||
\usage{
|
||||
as.mo(x, Becker = FALSE, Lancefield = FALSE)
|
||||
@ -20,11 +19,15 @@ is.mo(x)
|
||||
guess_mo(x, Becker = FALSE, Lancefield = FALSE)
|
||||
}
|
||||
\arguments{
|
||||
\item{x}{a character vector or a dataframe with one or two columns}
|
||||
\item{x}{a character vector or a \code{data.frame} with one or two columns}
|
||||
|
||||
\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".}
|
||||
\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].
|
||||
|
||||
\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}.}
|
||||
This excludes \emph{Staphylococcus aureus} at default, use \code{Becker = "all"} to also categorise \emph{S. aureus} as "CoPS".}
|
||||
|
||||
\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.
|
||||
|
||||
This excludes \emph{Enterococci} at default (who are in group D), use \code{Lancefield = "all"} to also categorise all \emph{Enterococci} as group D.}
|
||||
}
|
||||
\value{
|
||||
Character (vector) with class \code{"mo"}. Unknown values will return \code{NA}.
|
||||
@ -35,7 +38,7 @@ Use this function to determine a valid ID based on a genus (and species). This i
|
||||
\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.
|
||||
Use the \code{\link{mo_property}} functions to get properties based on the returned code, see Examples.
|
||||
|
||||
Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. These are:
|
||||
\itemize{
|
||||
@ -63,7 +66,7 @@ as.mo("VRSA") # Vancomycin Resistant S. aureus
|
||||
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") # will remain species: STCPYO
|
||||
guess_mo("S. pyogenes", Lancefield = TRUE) # will not remain species: STCGRA
|
||||
|
||||
# Use mo_* functions to get a specific property based on `mo`
|
||||
|
||||
@ -4,7 +4,7 @@
|
||||
\name{microorganisms}
|
||||
\alias{microorganisms}
|
||||
\title{Data set with human pathogenic microorganisms}
|
||||
\format{A \code{\link{tibble}} with 2,664 observations and 12 variables:
|
||||
\format{A \code{\link{tibble}} with 2,664 observations and 16 variables:
|
||||
\describe{
|
||||
\item{\code{mo}}{ID of microorganism}
|
||||
\item{\code{bactsys}}{Bactsyscode of microorganism}
|
||||
@ -13,11 +13,15 @@
|
||||
\item{\code{species}}{Species name of microorganism, like \code{"coli"}}
|
||||
\item{\code{subspecies}}{Subspecies name of bio-/serovar of microorganism, like \code{"EHEC"}}
|
||||
\item{\code{fullname}}{Full name, like \code{"Echerichia coli (EHEC)"}}
|
||||
\item{\code{aerobic}}{Logical whether bacteria is aerobic}
|
||||
\item{\code{type}}{Type of microorganism, like \code{"Bacteria"} and \code{"Fungus/yeast"}}
|
||||
\item{\code{gramstain}}{Gram of microorganism, like \code{"Negative rods"}}
|
||||
\item{\code{aerobic}}{Logical whether bacteria is aerobic}
|
||||
\item{\code{type_de}}{Type of microorganism in German, like \code{"Bakterien"} and \code{"Pilz/Hefe"}}
|
||||
\item{\code{gramstain_de}}{Gram of microorganism in German, like \code{"Negative Staebchen"}}
|
||||
\item{\code{type_nl}}{Type of microorganism in Dutch, like \code{"Bacterie"} and \code{"Schimmel/gist"}}
|
||||
\item{\code{gramstain_nl}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
|
||||
\item{\code{type_es}}{Type of microorganism in Spanish, like \code{"Bacteria"} and \code{"Hongo/levadura"}}
|
||||
\item{\code{gramstain_es}}{Gram of microorganism in Spanish, like \code{"Bacilos negativos"}}
|
||||
}}
|
||||
\usage{
|
||||
microorganisms
|
||||
|
||||
@ -10,78 +10,105 @@
|
||||
\alias{mo_type}
|
||||
\alias{mo_gramstain}
|
||||
\alias{mo_aerobic}
|
||||
\alias{mo_type_nl}
|
||||
\alias{mo_gramstain_nl}
|
||||
\title{Property of a microorganism}
|
||||
\source{
|
||||
[1] Becker K \emph{et al.} \strong{Coagulase-Negative Staphylococci}. 2014. Clin Microbiol Rev. 27(4): 870–926. \url{https://dx.doi.org/10.1128/CMR.00109-13}
|
||||
|
||||
[2] Lancefield RC \strong{A serological differentiation of human and other groups of hemolytic streptococci}. 1933. J Exp Med. 57(4): 571–95. \url{https://dx.doi.org/10.1084/jem.57.4.571}
|
||||
}
|
||||
\usage{
|
||||
mo_property(x, property = "fullname")
|
||||
mo_property(x, property = "fullname", Becker = FALSE,
|
||||
Lancefield = FALSE)
|
||||
|
||||
mo_family(x)
|
||||
|
||||
mo_genus(x)
|
||||
|
||||
mo_species(x)
|
||||
mo_species(x, Becker = FALSE, Lancefield = FALSE)
|
||||
|
||||
mo_subspecies(x)
|
||||
mo_subspecies(x, Becker = FALSE, Lancefield = FALSE)
|
||||
|
||||
mo_fullname(x)
|
||||
mo_fullname(x, Becker = FALSE, Lancefield = FALSE)
|
||||
|
||||
mo_type(x)
|
||||
mo_type(x, language = "en")
|
||||
|
||||
mo_gramstain(x)
|
||||
mo_gramstain(x, language = "en")
|
||||
|
||||
mo_aerobic(x)
|
||||
|
||||
mo_type_nl(x)
|
||||
|
||||
mo_gramstain_nl(x)
|
||||
}
|
||||
\arguments{
|
||||
\item{x}{a (vector of a) valid \code{\link{mo}} or any text that can be coerced to a valid microorganism code with \code{\link{as.mo}}}
|
||||
\item{x}{any (vector of) text that can be coerced to a valid microorganism code with \code{\link{as.mo}}}
|
||||
|
||||
\item{property}{one of the column names of one of the \code{\link{microorganisms}} data set, like \code{"mo"}, \code{"bactsys"}, \code{"family"}, \code{"genus"}, \code{"species"}, \code{"fullname"}, \code{"gramstain"} and \code{"aerobic"}}
|
||||
|
||||
\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".}
|
||||
|
||||
\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.
|
||||
|
||||
This excludes \emph{Enterococci} at default (who are in group D), use \code{Lancefield = "all"} to also categorise all \emph{Enterococci} as group D.}
|
||||
|
||||
\item{language}{language of the returned text, either one of \code{"en"} (English), \code{"de"} (German) or \code{"nl"} (Dutch)}
|
||||
}
|
||||
\description{
|
||||
Use these functions to return a specific property of a microorganism from the \code{\link{microorganisms}} data set, based on their \code{mo}. Get such an ID with \code{\link{as.mo}}.
|
||||
Use these functions to return a specific property of a microorganism from the \code{\link{microorganisms}} data set. All input values will be evaluated internally with \code{\link{as.mo}}.
|
||||
}
|
||||
\examples{
|
||||
# All properties
|
||||
mo_family("E. coli") # Enterobacteriaceae
|
||||
mo_genus("E. coli") # Escherichia
|
||||
mo_species("E. coli") # coli
|
||||
mo_subspecies("E. coli") # <NA>
|
||||
mo_fullname("E. coli") # Escherichia coli
|
||||
mo_type("E. coli") # Bacteria
|
||||
mo_gramstain("E. coli") # Negative rods
|
||||
mo_aerobic("E. coli") # TRUE
|
||||
mo_type_nl("E. coli") # Bacterie
|
||||
mo_gramstain_nl("E. coli") # Negatieve staven
|
||||
mo_family("E. coli") # "Enterobacteriaceae"
|
||||
mo_genus("E. coli") # "Escherichia"
|
||||
mo_species("E. coli") # "coli"
|
||||
mo_subspecies("E. coli") # <NA>
|
||||
mo_fullname("E. coli") # "Escherichia coli"
|
||||
mo_type("E. coli") # "Bacteria"
|
||||
mo_gramstain("E. coli") # "Negative rods"
|
||||
mo_aerobic("E. coli") # TRUE
|
||||
|
||||
# language support for Spanish, German and Dutch
|
||||
mo_type("E. coli", "es") # "Bakteria"
|
||||
mo_type("E. coli", "de") # "Bakterien"
|
||||
mo_type("E. coli", "nl") # "Bacterie"
|
||||
mo_gramstain("E. coli", "es") # "Bacilos negativos"
|
||||
mo_gramstain("E. coli", "de") # "Negative Staebchen"
|
||||
mo_gramstain("E. coli", "nl") # "Negatieve staven"
|
||||
|
||||
|
||||
# Abbreviations known in the field
|
||||
mo_genus("EHEC") # Escherichia
|
||||
mo_species("EHEC") # coli
|
||||
mo_subspecies("EHEC") # EHEC
|
||||
mo_fullname("EHEC") # Escherichia coli (EHEC)
|
||||
mo_genus("MRSA") # "Staphylococcus"
|
||||
mo_species("MRSA") # "aureus"
|
||||
mo_gramstain("MRSA") # "Positive cocci"
|
||||
|
||||
mo_genus("MRSA") # Staphylococcus
|
||||
mo_species("MRSA") # aureus
|
||||
mo_gramstain("MRSA") # Positive cocci
|
||||
|
||||
mo_genus("VISA") # Staphylococcus
|
||||
mo_species("VISA") # aureus
|
||||
mo_genus("VISA") # "Staphylococcus"
|
||||
mo_species("VISA") # "aureus"
|
||||
|
||||
|
||||
# Known subspecies
|
||||
mo_genus("doylei") # Campylobacter
|
||||
mo_species("doylei") # jejuni
|
||||
mo_fullname("doylei") # Campylobacter jejuni (doylei)
|
||||
mo_genus("EHEC") # "Escherichia"
|
||||
mo_species("EHEC") # "coli"
|
||||
mo_subspecies("EHEC") # "EHEC"
|
||||
mo_fullname("EHEC") # "Escherichia coli (EHEC)"
|
||||
|
||||
mo_genus("doylei") # "Campylobacter"
|
||||
mo_species("doylei") # "jejuni"
|
||||
mo_fullname("doylei") # "Campylobacter jejuni (doylei)"
|
||||
|
||||
mo_fullname("K. pneu rh") # "Klebsiella pneumoniae (rhinoscleromatis)"
|
||||
|
||||
|
||||
# Anaerobic bacteria
|
||||
mo_genus("B. fragilis") # Bacteroides
|
||||
mo_species("B. fragilis") # fragilis
|
||||
mo_aerobic("B. fragilis") # FALSE
|
||||
mo_genus("B. fragilis") # "Bacteroides"
|
||||
mo_species("B. fragilis") # "fragilis"
|
||||
mo_aerobic("B. fragilis") # FALSE
|
||||
|
||||
|
||||
# Becker classification, see ?as.mo
|
||||
mo_fullname("S. epidermidis") # "Staphylococcus epidermidis"
|
||||
mo_fullname("S. epidermidis", Becker = TRUE) # "Coagulase Negative Staphylococcus (CoNS)"
|
||||
|
||||
# Lancefield classification, see ?as.mo
|
||||
mo_fullname("S. pyogenes") # "Streptococcus pyogenes"
|
||||
mo_fullname("S. pyogenes", Lancefield = TRUE) # "Streptococcus group A"
|
||||
}
|
||||
\seealso{
|
||||
\code{\link{microorganisms}}
|
||||
|
||||
@ -8,4 +8,7 @@ test_that("ab_property works", {
|
||||
expect_equal(ab_umcg("amox"), "AMOX")
|
||||
expect_equal(class(ab_tradenames("amox")), "character")
|
||||
expect_equal(class(ab_tradenames(c("amox", "amox"))), "list")
|
||||
expect_equal(ab_atc("amox"), as.character(as.atc("amox")))
|
||||
|
||||
expect_error(ab_property("amox", "invalid property"))
|
||||
})
|
||||
|
||||
@ -16,9 +16,11 @@ test_that("deprecated functions work", {
|
||||
|
||||
old_mo <- "ESCCOL"
|
||||
class(old_mo) <- "bactid"
|
||||
df_oldmo <- data.frame(test = old_mo)
|
||||
# print
|
||||
expect_output(print(old_mo))
|
||||
# test data.frame and pull
|
||||
expect_equal(as.character(dplyr::pull(data.frame(test = old_mo), test)), "ESCCOL")
|
||||
# test pull
|
||||
library(dplyr)
|
||||
expect_identical(df_oldmo %>% pull(test), old_mo)
|
||||
|
||||
})
|
||||
|
||||
@ -12,7 +12,7 @@ test_that("as.mo works", {
|
||||
expect_equal(as.character(as.mo("klpn")), "KLEPNE")
|
||||
expect_equal(as.character(as.mo("Klebsiella")), "KLE")
|
||||
expect_equal(as.character(as.mo("K. pneu rhino")), "KLEPNERH") # K. pneumoniae subspp. rhinoscleromatis
|
||||
expect_equal(as.character(as.mo("coagulase negative")), "STACNS")
|
||||
expect_equal(as.character(as.mo("Bartonella")), "BAR")
|
||||
|
||||
expect_equal(as.character(as.mo("P. aer")), "PSEAER") # not Pasteurella aerogenes
|
||||
|
||||
@ -30,16 +30,21 @@ test_that("as.mo works", {
|
||||
expect_equal(as.character(as.mo("VISP")), "STCPNE")
|
||||
expect_equal(as.character(as.mo("VRSP")), "STCPNE")
|
||||
|
||||
expect_equal(as.character(as.mo("CNS")), "STACNS")
|
||||
expect_equal(as.character(as.mo("CoNS")), "STACNS")
|
||||
expect_equal(as.character(as.mo("CPS")), "STACPS")
|
||||
expect_equal(as.character(as.mo("CoPS")), "STACPS")
|
||||
|
||||
expect_identical(
|
||||
as.character(
|
||||
as.mo(c("stau",
|
||||
"STAU",
|
||||
"staaur",
|
||||
"S. aureus",
|
||||
"S aureus",
|
||||
"Staphylococcus aureus",
|
||||
"MRSA",
|
||||
"VISA"))),
|
||||
"STAU",
|
||||
"staaur",
|
||||
"S. aureus",
|
||||
"S aureus",
|
||||
"Staphylococcus aureus",
|
||||
"MRSA",
|
||||
"VISA"))),
|
||||
rep("STAAUR", 8))
|
||||
|
||||
# check for Becker classification
|
||||
@ -55,19 +60,23 @@ test_that("as.mo works", {
|
||||
expect_identical(as.character(guess_mo("STAAUR", Becker = "all")), "STACPS")
|
||||
|
||||
# check for Lancefield classification
|
||||
expect_identical(as.character(guess_mo("S. pyogenes", Lancefield = FALSE)), "STCPYO")
|
||||
expect_identical(as.character(guess_mo("S. pyogenes", Lancefield = TRUE)), "STCGRA")
|
||||
expect_identical(as.character(guess_mo("STCPYO", Lancefield = TRUE)), "STCGRA")
|
||||
expect_identical(as.character(guess_mo("S. agalactiae", Lancefield = FALSE)), "STCAGA")
|
||||
expect_identical(as.character(guess_mo("S. agalactiae", Lancefield = TRUE)), "STCGRB") # group B
|
||||
expect_identical(as.character(guess_mo("S. equisimilis", Lancefield = FALSE)), "STCEQS")
|
||||
expect_identical(as.character(guess_mo("S. equisimilis", Lancefield = TRUE)), "STCGRC") # group C
|
||||
expect_identical(as.character(guess_mo("S. anginosus", Lancefield = FALSE)), "STCANG")
|
||||
expect_identical(as.character(guess_mo("S. anginosus", Lancefield = TRUE)), "STCGRF") # group F
|
||||
expect_identical(as.character(guess_mo("S. sanguis", Lancefield = FALSE)), "STCSAN")
|
||||
expect_identical(as.character(guess_mo("S. sanguis", Lancefield = TRUE)), "STCGRH") # group H
|
||||
expect_identical(as.character(guess_mo("S. salivarius", Lancefield = FALSE)), "STCSAL")
|
||||
expect_identical(as.character(guess_mo("S. salivarius", Lancefield = TRUE)), "STCGRK") # group K
|
||||
expect_identical(as.character(guess_mo("S. pyogenes", Lancefield = FALSE)), "STCPYO")
|
||||
expect_identical(as.character(guess_mo("S. pyogenes", Lancefield = TRUE)), "STCGRA")
|
||||
expect_identical(as.character(guess_mo("STCPYO", Lancefield = TRUE)), "STCGRA") # group A
|
||||
expect_identical(as.character(guess_mo("S. agalactiae", Lancefield = FALSE)), "STCAGA")
|
||||
expect_identical(as.character(guess_mo("S. agalactiae", Lancefield = TRUE)), "STCGRB") # group B
|
||||
expect_identical(as.character(guess_mo("S. equisimilis", Lancefield = FALSE)), "STCEQS")
|
||||
expect_identical(as.character(guess_mo("S. equisimilis", Lancefield = TRUE)), "STCGRC") # group C
|
||||
# Enterococci must only be influenced if Lancefield = "all"
|
||||
expect_identical(as.character(guess_mo("E. faecium", Lancefield = FALSE)), "ENCFAC")
|
||||
expect_identical(as.character(guess_mo("E. faecium", Lancefield = TRUE)), "ENCFAC")
|
||||
expect_identical(as.character(guess_mo("E. faecium", Lancefield = "all")), "STCGRD") # group D
|
||||
expect_identical(as.character(guess_mo("S. anginosus", Lancefield = FALSE)), "STCANG")
|
||||
expect_identical(as.character(guess_mo("S. anginosus", Lancefield = TRUE)), "STCGRF") # group F
|
||||
expect_identical(as.character(guess_mo("S. sanguis", Lancefield = FALSE)), "STCSAN")
|
||||
expect_identical(as.character(guess_mo("S. sanguis", Lancefield = TRUE)), "STCGRH") # group H
|
||||
expect_identical(as.character(guess_mo("S. salivarius", Lancefield = FALSE)), "STCSAL")
|
||||
expect_identical(as.character(guess_mo("S. salivarius", Lancefield = TRUE)), "STCGRK") # group K
|
||||
|
||||
library(dplyr)
|
||||
|
||||
|
||||
@ -9,6 +9,12 @@ test_that("mo_property works", {
|
||||
expect_equal(mo_type("E. coli"), "Bacteria")
|
||||
expect_equal(mo_gramstain("E. coli"), "Negative rods")
|
||||
expect_equal(mo_aerobic("E. coli"), TRUE)
|
||||
expect_equal(mo_type_nl("E. coli"), "Bacterie")
|
||||
expect_equal(mo_gramstain_nl("E. coli"), "Negatieve staven")
|
||||
|
||||
expect_equal(mo_type("E. coli", language = "de"), "Bakterien")
|
||||
expect_equal(mo_gramstain("E. coli", language = "de"), "Negative Staebchen")
|
||||
|
||||
expect_equal(mo_type("E. coli", language = "nl"), "Bacterie")
|
||||
expect_equal(mo_gramstain("E. coli", language = "nl"), "Negatieve staven")
|
||||
|
||||
expect_error(mo_type("E. coli", language = "INVALID"))
|
||||
})
|
||||
|
||||
1
vignettes/.gitignore
vendored
1
vignettes/.gitignore
vendored
@ -1,4 +1,5 @@
|
||||
figure
|
||||
*.html
|
||||
*.md
|
||||
*.R
|
||||
rsconnect
|
||||
|
||||
@ -34,7 +34,7 @@ This `AMR` package basically does four important things:
|
||||
* Use `first_isolate` to identify the first isolates of every patient [using guidelines from the CLSI](https://clsi.org/standards/products/microbiology/documents/m39/) (Clinical and Laboratory Standards Institute).
|
||||
* You can also identify first *weighted* isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them.
|
||||
* Use `MDRO` (abbreviation of Multi Drug Resistant Organisms) to check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently, national guidelines for Germany and the Netherlands are supported.
|
||||
* The data set `microorganisms` contains the family, genus, species, subspecies, colloquial name and Gram stain of almost 2,650 microorganisms (2,207 bacteria, 285 fungi/yeasts, 153 parasites, 1 other). This enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus`, `mo_family` or `mo_gramstain`. Since it uses `as.mo` internally, AI is supported. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. These functions can be used to add new variables to your data.
|
||||
* The data set `microorganisms` contains the family, genus, species, subspecies, colloquial name and Gram stain of almost 3,000 potential human pathogenic microorganisms (bacteria, fungi/yeasts and parasites). This enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus`, `mo_family` or `mo_gramstain`. As they use `as.mo` internally, they also use artificial intelligence. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. Some functions can return results in Spanish, German and Dutch. These functions can be used to add new variables to your data.
|
||||
* The data set `antibiotics` contains the ATC code, LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains a total of 298 trade names. Use functions like `ab_official` and `ab_tradenames` to look up values. As the `mo_*` functions use `as.mo` internally, the `ab_*` functions use `as.atc` internally so it uses AI to guess your expected result. For example, `ab_official("Fluclox")`, `ab_official("Floxapen")` and `ab_official("J01CF05")` will all return `"Flucloxacillin"`. These functions can again be used to add new variables to your data.
|
||||
|
||||
3. It **analyses the data** with convenient functions that use well-known methods.
|
||||
@ -52,7 +52,6 @@ This `AMR` package basically does four important things:
|
||||
* Results of 40 antibiotics (each antibiotic in its own column) with a total of 38,414 antimicrobial results
|
||||
* Real and genuine data
|
||||
|
||||
|
||||
----
|
||||
```{r, echo = FALSE}
|
||||
# this will print "2018" in 2018, and "2018-yyyy" after 2018.
|
||||
|
||||
Loading…
Reference in New Issue
Block a user