* 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`
#' 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 dataset \code{\link{antibiotics}} will be searched for abbreviations, official names and trade names.
#' @param x character vector to determine \code{ATC} code
#' 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 @@
@@ -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}.
#' [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 @@
@@ -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`
#' 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)
#' [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
@ -55,7 +55,7 @@ This `AMR` package basically does four important things:
@@ -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.
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 dataset \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.
[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}
\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]. 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.
\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{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
@@ -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
@@ -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`
[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}
\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}}.
@ -34,7 +34,7 @@ This `AMR` package basically does four important things:
@@ -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:
@@ -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.
