P281424/AMR
1
0
Fork 0
mirror of https://github.com/msberends/AMR.git synced 2024-12-25 07:26:12 +01:00
Code Releases Activity

Support for German and Spanish microorganism properties, cleanup

Browse Source
This commit is contained in:
dr. M.S. (Matthijs) Berends 2018-09-04 11:33:30 +02:00
parent 5405002119
commit b388e3fee7
20 changed files with 256 additions and 157 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
DESCRIPTION
View File

@ -1,6 +1,6 @@
Package: AMR
Version: 0.3.0.9006
Date: 2018-09-01
Version: 0.3.0.9007
Date: 2018-09-04
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(

2
NAMESPACE
View File

@ -94,12 +94,10 @@ export(mo_family)
export(mo_fullname)
export(mo_genus)
export(mo_gramstain)
export(mo_gramstain_nl)
export(mo_property)
export(mo_species)
export(mo_subspecies)
export(mo_type)
export(mo_type_nl)
export(n_rsi)
export(p.symbol)
export(portion_I)

10
NEWS.md
View File

@ -10,7 +10,15 @@
* Column names of datasets `microorganisms` and `septic_patients`
* All old syntaxes will still work with this version, but will throw warnings
* 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`.
* 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`
* 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:
```r
mo_gramstain("E. coli")
# [1] "Negative rods"
mo_gramstain("E. coli", language = "de") # "de" = Deutsch / German
# [1] "Negative Staebchen"
mo_gramstain("E. coli", language = "es") # "es" = Español / Spanish
# [1] "Bacilos negativos"
```
* Function `ab_property` and its aliases: `ab_official`, `ab_tradenames`, `ab_certe`, `ab_umcg`, `ab_official_nl` and `ab_trivial_nl`
* Introduction to AMR as a vignette

2
R/ab_property.R
View File

@ -36,7 +36,7 @@
ab_property <- function(x, property = 'official') {
property <- property[1]
if (!property %in% colnames(antibiotics)) {
stop("invalid property: ", property, " - use a column name of `antibiotics`")
stop("invalid property: ", property, " - use a column name of the `antibiotics` data set")
}
if (!is.atc(x)) {
x <- as.atc(x) # this will give a warning if x cannot be coerced

4
R/atc.R
View File

@ -17,9 +17,9 @@
# ==================================================================== #
#' Find ATC code based on antibiotic property
#' Transform to ATC code
#'
#' 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.
#' @param x character vector to determine \code{ATC} code
#' @rdname as.atc
#' @aliases atc

8
R/data.R
View File

@ -123,7 +123,7 @@
#' Data set with human pathogenic microorganisms
#'
#' A data set containing 2,664 (potential) human pathogenic microorganisms. MO codes can be looked up using \code{\link{guess_mo}}.
#' @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}
@ -132,11 +132,15 @@
#' \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"}}
#' }
# source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
# new <- microorganisms %>% filter(genus == "Bacteroides") %>% .[1,]

37
R/mo.R
View File

@ -19,15 +19,19 @@
#' 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}.
#' @param x a character vector or a \code{data.frame} 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.
#'
#' This excludes \emph{Enterococci} at default (who are in group D), use \code{Lancefield = "all"} to also categorise all \emph{Enterococci} as group D.
#' @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.
#' 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{
@ -39,10 +43,9 @@
#' 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}
#' [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}
#' @export
#' @importFrom dplyr %>% pull left_join
#' @return Character (vector) with class \code{"mo"}. Unknown values will return \code{NA}.
@ -63,7 +66,7 @@
#' 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`
@ -177,10 +180,17 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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
# coerce S. coagulase negative
x[i] <- 'STACNS'
next
}
if (tolower(x[i]) %like% 'coagulase positive'
| tolower(x[i]) %like% 'cps'
| tolower(x[i]) %like% 'cops') {
# coerce S. coagulase positive
x[i] <- 'STACPS'
next
}
# translate known trivial names to genus+species
if (!is.na(x_trimmed[i])) {
@ -204,7 +214,7 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
next
}
if (toupper(x_trimmed[i]) %in% c('PISP', 'PRSP', 'VISP', 'VRSP')) {
# peni R, peni I, vanco I, vanco R: S. pneumoniae
# peni I, peni R, vanco I, vanco R: S. pneumoniae
x[i] <- 'STCPNE'
next
}
@ -327,7 +337,7 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
}
}
if (Lancefield == TRUE) {
if (Lancefield == TRUE | Lancefield == "all") {
# group A
x[x == "STCPYO"] <- "STCGRA" # S. pyogenes
# group B
@ -338,6 +348,9 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
"zooepidemicus", "dysgalactiae")) %>%
pull(mo)
x[x %in% S_groupC] <- "STCGRC" # S. agalactiae
if (Lancefield == "all") {
x[substr(x, 1, 3) == "ENC"] <- "STCGRD" # all Enterococci
}
# group F
x[x == "STCANG"] <- "STCGRF" # S. anginosus
# group H

130
R/mo_property.R
View File

@ -18,59 +18,80 @@
#' Property of a microorganism
#'
#' 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}}.
#' @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}}
#' 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}}.
#' @param x any (vector of) text that can be coerced to a valid microorganism code with \code{\link{as.mo}}
#' @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"}
#' @inheritParams as.mo
#' @param language language of the returned text, either one of \code{"en"} (English), \code{"de"} (German) or \code{"nl"} (Dutch)
#' @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}
#' @rdname mo_property
#' @export
#' @importFrom dplyr %>% left_join pull
#' @seealso \code{\link{microorganisms}}
#' @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_property <- function(x, property = 'fullname') {
property <- property[1]
#' 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"
mo_property <- function(x, property = 'fullname', Becker = FALSE, Lancefield = FALSE) {
property <- tolower(property[1])
if (!property %in% colnames(microorganisms)) {
stop("invalid property: ", property, " - use a column name of `microorganisms`")
}
if (!is.mo(x)) {
x <- as.mo(x) # this will give a warning if x cannot be coerced
stop("invalid property: ", property, " - use a column name of the `microorganisms` data set")
}
x <- as.mo(x = x, Becker = Becker, Lancefield = Lancefield) # this will give a warning if x cannot be coerced
suppressWarnings(
data.frame(mo = x, stringsAsFactors = FALSE) %>%
left_join(AMR::microorganisms, by = "mo") %>%
@ -92,32 +113,32 @@ mo_genus <- function(x) {
#' @rdname mo_property
#' @export
mo_species <- function(x) {
mo_property(x, "species")
mo_species <- function(x, Becker = FALSE, Lancefield = FALSE) {
mo_property(x, "species", Becker = Becker, Lancefield = Lancefield)
}
#' @rdname mo_property
#' @export
mo_subspecies <- function(x) {
mo_property(x, "subspecies")
mo_subspecies <- function(x, Becker = FALSE, Lancefield = FALSE) {
mo_property(x, "subspecies", Becker = Becker, Lancefield = Lancefield)
}
#' @rdname mo_property
#' @export
mo_fullname <- function(x) {
mo_property(x, "fullname")
mo_fullname <- function(x, Becker = FALSE, Lancefield = FALSE) {
mo_property(x, "fullname", Becker = Becker, Lancefield = Lancefield)
}
#' @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)
}
}

2
README.md
View File

@ -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.

BIN
data/microorganisms.rda
View File

Binary file not shown.

4
man/as.atc.Rd
View File

@ -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
View File

@ -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`

8
man/microorganisms.Rd
View File

@ -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

107
man/mo_property.Rd
View File

@ -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}}

3
tests/testthat/test-ab_property.R
View File

@ -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"))
})

6
tests/testthat/test-deprecated.R
View File

@ -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)
})

51
tests/testthat/test-mo.R
View File

@ -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)

10
tests/testthat/test-mo_property.R
View File

@ -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
View File

@ -1,4 +1,5 @@
figure
*.html
*.md
*.R
rsconnect

3
vignettes/AMR.Rmd
View File

@ -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.