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prepare for documentation

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dr. M.S. (Matthijs) Berends
2026-05-03 11:50:05 +02:00
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2
R/data.R
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@@ -109,7 +109,7 @@
#' - `status` \cr Status of the taxon, either `r vector_or(microorganisms$status, documentation = TRUE)`
#' - `kingdom`, `phylum`, `class`, `order`, `family`, `genus`, `species`, `subspecies`\cr Taxonomic rank of the microorganism. Note that for fungi, *phylum* is equal to their taxonomic *division*. Also, for fungi, *subkingdom* and *subdivision* were left out since they do not occur in the bacterial taxonomy.
#' - `rank`\cr Text of the taxonomic rank of the microorganism, such as `"species"` or `"genus"`
#' - `ref`\cr Abbreviated authority citation for the nomenclatural act that established the current name combination, following ICNP conventions. For species described in their current genus (sp. nov.), this is the original description author(s) and year. For species transferred to a different genus (comb. nov.), this is the reclassification author(s) and year. Emendations are excluded. For synonyms, this is the authority under which the synonym was originally published. Data sourced primarily from LPSN, supplemented by GBIF where LPSN coverage is absent.
#' - `ref`\cr Abbreviated authority citation for the nomenclatural act that established the current name combination, following ICNP conventions. For species described in their current genus (*sp. nov.*), this is the original description author(s) and year. For species transferred to a different genus (*comb. nov.*), this is the reclassification author(s) and year. Emendations are excluded. For synonyms, this is the authority under which the synonym was originally published. This field is directly retrieved from the source specified in the column `source`. Diacritics were removed to comply with CRAN, that only allows ASCII characters.
#' - `oxygen_tolerance` \cr Oxygen tolerance, either `r vector_or(microorganisms$oxygen_tolerance, documentation = TRUE)`. These data were retrieved from BacDive (see *Source*). Items that contain "likely" are missing from BacDive and were extrapolated from other species within the same genus to guess the oxygen tolerance. Currently `r round(length(microorganisms$oxygen_tolerance[which(!is.na(microorganisms$oxygen_tolerance))]) / nrow(microorganisms[which(microorganisms$kingdom == "Bacteria"), ]) * 100, 1)`% of all `r format_included_data_number(nrow(microorganisms[which(microorganisms$kingdom == "Bacteria"), ]))` bacteria in the data set contain an oxygen tolerance.
#' - `source`\cr Either `r vector_or(microorganisms$source, documentation = TRUE)` (see *Source*)
#' - `lpsn`\cr Identifier ('Record number') of `r TAXONOMY_VERSION$LPSN$name`. This will be the first/highest LPSN identifier to keep one identifier per row. For example, *Acetobacter ascendens* has LPSN Record number 7864 and 11011. Only the first is available in the `microorganisms` data set. ***This is a unique identifier***, though available for only `r format_included_data_number(sum(!is.na(microorganisms$lpsn)))` records.

12
R/mo_property.R
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@@ -44,21 +44,21 @@
#'
#' [mo_ref()] returns the abbreviated authority of the nomenclatural act that created the queried name combination. When `keep_synonyms = FALSE` (default), this is the authority of the currently accepted name. When `keep_synonyms = TRUE`, this is the authority under which the queried (possibly outdated) name was published. Emendations (changes to the species description without a name change) are not reflected; only the combination or original description authority is returned.
#'
#' The short name ([mo_shortname()]) returns the first character of the genus and the full species, such as `"E. coli"`, for species and subspecies. Exceptions are abbreviations of staphylococci (such as *"CoNS"*, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as *"GBS"*, Group B Streptococci). Please bear in mind that e.g. *E. coli* could mean *Escherichia coli* (kingdom of Bacteria) as well as *Entamoeba coli* (kingdom of Protozoa). Returning to the full name will be done using [as.mo()] internally, giving priority to bacteria and human pathogens, i.e. `"E. coli"` will be considered *Escherichia coli*. As a result, `mo_fullname(mo_shortname("Entamoeba coli"))` returns `"Escherichia coli"`.
#' The short name ([mo_shortname()]) returns the first character of the genus and the full species, such as `"E. coli"`, for species and subspecies. Exceptions are abbreviations of staphylococci (such as *"CoNS"*, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as *"GBS"*, Group B Streptococci). Please bear in mind that e.g. *E. coli* could mean *Escherichia coli* (kingdom of Bacteria) as well as *Entamoeba coli* (kingdom of Protozoa). Returning to the full name will be done using [as.mo()] internally, giving priority to bacteria and human pathogens, i.e. `"E. coli"` will always be considered *Escherichia coli*. As a result, `mo_fullname(mo_shortname("Entamoeba coli"))` returns `"Escherichia coli"`.
#'
#' Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions [mo_kingdom()] and [mo_domain()] return the exact same results.
#'
#' Determination of human pathogenicity ([mo_pathogenicity()]) is strongly based on Bartlett *et al.* (2022, \doi{10.1099/mic.0.001269}). This function returns a [factor] with the levels *Pathogenic*, *Potentially pathogenic*, *Non-pathogenic*, and *Unknown*.
#'
#' Determination of the Gram stain ([mo_gramstain()]) will be based on the taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318/)), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were later renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, [PMID 34694987](https://pubmed.ncbi.nlm.nih.gov/34694987/)). Bacteria in these phyla are considered Gram-positive in this `AMR` package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [mo_is_gram_negative()] and [mo_is_gram_positive()] always return `TRUE` or `FALSE` (or `NA` when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
#' Determination of the Gram stain ([mo_gramstain()] is based on the taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318/)), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were later renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, [PMID 34694987](https://pubmed.ncbi.nlm.nih.gov/34694987/)). Bacteria in these phyla are considered Gram-positive in this `AMR` package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [mo_is_gram_negative()] and [mo_is_gram_positive()] always return `TRUE` or `FALSE` (or `NA` when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
#'
#' Determination of yeasts ([mo_is_yeast()]) will be based on the taxonomic kingdom and class. *Budding yeasts* are yeasts that reproduce asexually through a process called budding, where a new cell develops from a small protrusion on the parent cell. Taxonomically, these are members of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes) or Pichiomycetes. *True yeasts* quite specifically refers to yeasts in the underlying order Saccharomycetales (such as *Saccharomyces cerevisiae*). Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes or Pichiomycetes, the function will return `TRUE`. It returns `FALSE` otherwise (or `NA` when the input is `NA` or the MO code is `UNKNOWN`).
#' Determination of yeasts ([mo_is_yeast()]) is based on the taxonomic kingdom and class. *Budding yeasts* are yeasts that reproduce asexually through a process called budding, where a new cell develops from a small protrusion on the parent cell. Taxonomically, these are members of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes) or Pichiomycetes. *True yeasts* quite specifically refers to yeasts in the underlying order Saccharomycetales (such as *Saccharomyces cerevisiae*). Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes or Pichiomycetes, the function will return `TRUE`. It returns `FALSE` otherwise (or `NA` when the input is `NA` or the MO code is `UNKNOWN`).
#'
#' Determination of intrinsic resistance ([mo_is_intrinsic_resistant()]) will be based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(names(EUCAST_VERSION_EXPECTED_PHENOTYPES[1]))`. The [mo_is_intrinsic_resistant()] function can be vectorised over both argument `x` (input for microorganisms) and `ab` (input for antimicrobials).
#' Determination of intrinsic resistance ([mo_is_intrinsic_resistant()]) is based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(names(EUCAST_VERSION_EXPECTED_PHENOTYPES[1]))`. The [mo_is_intrinsic_resistant()] function can be vectorised over both argument `x` (input for microorganisms) and `ab` (input for antimicrobials).
#'
#' Determination of bacterial oxygen tolerance ([mo_oxygen_tolerance()]) will be based on BacDive, see *Source*. The function [mo_is_anaerobic()] only returns `TRUE` if the oxygen tolerance is `"anaerobe"`, indicting an obligate anaerobic species or genus. It always returns `FALSE` for species outside the taxonomic kingdom of Bacteria.
#' Determination of bacterial oxygen tolerance ([mo_oxygen_tolerance()]) is based on BacDive, see *Source*. The function [mo_is_anaerobic()] only returns `TRUE` if the oxygen tolerance is `"anaerobe"`, indicting an obligate anaerobic species or genus. It always returns `FALSE` for species outside the taxonomic kingdom of Bacteria.
#'
#' The function [mo_url()] will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species. [This MycoBank URL](`r TAXONOMY_VERSION$MycoBank$url`) will be used for fungi wherever available , [this LPSN URL](`r TAXONOMY_VERSION$MycoBank$url`) for bacteria wherever available, and [this GBIF link](`r TAXONOMY_VERSION$GBIF$url`) otherwise.
#' The function [mo_url()] will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species. [This MycoBank URL](`r TAXONOMY_VERSION$MycoBank$url`) is used for fungi wherever available , [this LPSN URL](`r TAXONOMY_VERSION$MycoBank$url`) for bacteria wherever available, and [this GBIF link](`r TAXONOMY_VERSION$GBIF$url`) otherwise.
#'
#' SNOMED codes ([mo_snomed()]) was last updated on `r documentation_date(TAXONOMY_VERSION$SNOMED$accessed_date)`. See *Source* and the [microorganisms] data set for more info.
#'

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man/age_groups.Rd
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@@ -17,10 +17,10 @@ age_groups(x, split_at = c(0, 12, 25, 55, 75), names = NULL,
\item{na.rm}{A \link{logical} to indicate whether missing values should be removed.}
}
\value{
Ordered [factor]
Ordered \link{factor}
}
\description{
Split ages into age groups defined by the `split` argument. This allows for easier demographic (antimicrobial resistance) analysis. The function returns an ordered [factor].
Split ages into age groups defined by the \code{split} argument. This allows for easier demographic (antimicrobial resistance) analysis. The function returns an ordered \link{factor}.
}
\details{
To split ages, the input for the \code{split_at} argument can be:

20
man/amr-tidymodels.Rd
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@@ -30,6 +30,26 @@ step_mic_log2(recipe, ..., role = NA, trained = FALSE, columns = NULL,
step_sir_numeric(recipe, ..., role = NA, trained = FALSE, columns = NULL,
skip = FALSE, id = recipes::rand_id("sir_numeric"))
}
\arguments{
\item{recipe}{A recipe object. The step will be added to the sequence of
operations for this recipe.}
\item{...}{One or more selector functions to choose variables for this step.
See \code{\link[recipes:selections]{selections()}} for more details.}
\item{role}{Not used by this step since no new variables are created.}
\item{trained}{A logical to indicate if the quantities for preprocessing have
been estimated.}
\item{skip}{A logical. Should the step be skipped when the recipe is baked by
\code{\link[recipes:bake]{bake()}}? While all operations are baked when \code{\link[recipes:prep]{prep()}} is run, some
operations may not be able to be conducted on new data (e.g. processing the
outcome variable(s)). Care should be taken when using \code{skip = TRUE} as it
may affect the computations for subsequent operations.}
\item{id}{A character string that is unique to this step to identify it.}
}
\description{
This family of functions allows using AMR-specific data types such as \verb{<sir>} and \verb{<mic>} inside \code{tidymodels} pipelines.
}

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man/antibiogram.Rd
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@@ -73,7 +73,7 @@ retrieve_wisca_parameters(wisca_model, ...)
\item{ab_transform}{A character to transform antimicrobial input - must be one of the column names of the \link{antimicrobials} data set (defaults to \code{"name"}): \code{"ab"}, \code{"cid"}, \code{"name"}, \code{"group"}, \code{"atc"}, \code{"atc_group1"}, \code{"atc_group2"}, \code{"abbreviations"}, \code{"synonyms"}, \code{"oral_ddd"}, \code{"oral_units"}, \code{"iv_ddd"}, \code{"iv_units"}, or \code{"loinc"}. Can also be \code{NULL} to not transform the input.}
\item{syndromic_group}{A column name of `x`, or values calculated to split rows of `x`, e.g. by using [ifelse()] or [`case_when()`][dplyr::case_when()]. See *Examples*.}
\item{syndromic_group}{A column name of \code{x}, or values calculated to split rows of \code{x}, e.g. by using \code{\link[=ifelse]{ifelse()}} or \code{\link[dplyr:case-and-replace-when]{case_when()}}. See \emph{Examples}.}
\item{add_total_n}{\emph{(deprecated in favour of \code{formatting_type})} A \link{logical} to indicate whether \code{n_tested} available numbers per pathogen should be added to the table (default is \code{TRUE}). This will add the lowest and highest number of available isolates per antimicrobial (e.g, if for \emph{E. coli} 200 isolates are available for ciprofloxacin and 150 for amoxicillin, the returned number will be "150-200"). This option is unavailable when \code{wisca = TRUE}; in that case, use \code{\link[=retrieve_wisca_parameters]{retrieve_wisca_parameters()}} to get the parameters used for WISCA.}

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man/as.mic.Rd
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@@ -39,23 +39,22 @@ mic_p90(x, na.rm = FALSE, ...)
\item{mic_range}{A manual range to rescale the MIC values, e.g., \code{mic_range = c(0.001, 32)}. Use \code{NA} to prevent rescaling on one side, e.g., \code{mic_range = c(NA, 32)}.}
\item{as.mic}{A [logical] to indicate whether the `mic` class should be kept - the default is `TRUE` for [rescale_mic()] and `FALSE` for [droplevels()]. When setting this to `FALSE` in [rescale_mic()], the output will have factor levels that acknowledge `mic_range`.}
\item{as.mic}{A \link{logical} to indicate whether the \code{mic} class should be kept - the default is \code{TRUE} for \code{\link[=rescale_mic]{rescale_mic()}} and \code{FALSE} for \code{\link[=droplevels]{droplevels()}}. When setting this to \code{FALSE} in \code{\link[=rescale_mic]{rescale_mic()}}, the output will have factor levels that acknowledge \code{mic_range}.}
\item{...}{Arguments passed on to methods.}
}
\value{
Ordered [factor] with additional class [`mic`], that in mathematical operations acts as a [numeric] vector. Bear in mind that the outcome of any mathematical operation on MICs will return a [numeric] value.
Ordered \link{factor} with additional class \code{\link{mic}}, that in mathematical operations acts as a \link{numeric} vector. Bear in mind that the outcome of any mathematical operation on MICs will return a \link{numeric} value.
}
\description{
This transforms vectors to a new class \code{\link{mic}}, which treats the input as decimal numbers, while maintaining operators (such as ">=") and only allowing valid MIC values known to the field of (medical) microbiology.
}
\details{
To interpret MIC values as SIR values, use [as.sir()] on MIC values. It supports guidelines from EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`).
To interpret MIC values as SIR values, use \code{\link[=as.sir]{as.sir()}} on MIC values. It supports guidelines from EUCAST (2011-2026) and CLSI (2011-2026).
This class for MIC values is a quite a special data type: formally it is an ordered [factor] with valid MIC values as [factor] levels (to make sure only valid MIC values are retained), but for any mathematical operation it acts as decimal numbers:
This class for MIC values is a quite a special data type: formally it is an ordered \link{factor} with valid MIC values as \link{factor} levels (to make sure only valid MIC values are retained), but for any mathematical operation it acts as decimal numbers:
```
x <- random_mic(10)
\if{html}{\out{<div class="sourceCode">}}\preformatted{x <- random_mic(10)
x
#> Class <mic>
#> [1] 16 1 8 8 64 >=128 0.0625 32 32 16
@@ -68,17 +67,16 @@ x[1] * 2
median(x)
#> [1] 26
```
}\if{html}{\out{</div>}}
This makes it possible to maintain operators that often come with MIC values, such ">=" and "<=", even when filtering using [numeric] values in data analysis, e.g.:
This makes it possible to maintain operators that often come with MIC values, such ">=" and "<=", even when filtering using \link{numeric} values in data analysis, e.g.:
```
x[x > 4]
\if{html}{\out{<div class="sourceCode">}}\preformatted{x[x > 4]
#> Class <mic>
#> [1] 16 8 8 64 >=128 32 32 16
df <- data.frame(x, hospital = "A")
subset(df, x > 4) # or with dplyr: df %>% filter(x > 4)
subset(df, x > 4) # or with dplyr: df \%>\% filter(x > 4)
#> x hospital
#> 1 16 A
#> 5 64 A
@@ -86,19 +84,19 @@ subset(df, x > 4) # or with dplyr: df %>% filter(x > 4)
#> 8 32 A
#> 9 32 A
#> 10 16 A
```
}\if{html}{\out{</div>}}
All so-called [group generic functions][groupGeneric()] are implemented for the MIC class (such as `!`, `!=`, `<`, `>=`, [exp()], [log2()]). Some mathematical functions are also implemented (such as [quantile()], [median()], [fivenum()]). Since [sd()] and [var()] are non-generic functions, these could not be extended. Use [mad()] as an alternative, or use e.g. `sd(as.numeric(x))` where `x` is your vector of MIC values.
All so-called \link[=groupGeneric]{group generic functions} are implemented for the MIC class (such as \code{!}, \code{!=}, \code{<}, \code{>=}, \code{\link[=exp]{exp()}}, \code{\link[=log2]{log2()}}). Some mathematical functions are also implemented (such as \code{\link[=quantile]{quantile()}}, \code{\link[=median]{median()}}, \code{\link[=fivenum]{fivenum()}}). Since \code{\link[=sd]{sd()}} and \code{\link[=var]{var()}} are non-generic functions, these could not be extended. Use \code{\link[=mad]{mad()}} as an alternative, or use e.g. \code{sd(as.numeric(x))} where \code{x} is your vector of MIC values.
Using [as.double()] or [as.numeric()] on MIC values will remove the operators and return a numeric vector. Do **not** use [as.integer()] on MIC values as by the \R convention on [factor]s, it will return the index of the factor levels (which is often useless for regular users).
Using \code{\link[=as.double]{as.double()}} or \code{\link[=as.numeric]{as.numeric()}} on MIC values will remove the operators and return a numeric vector. Do \strong{not} use \code{\link[=as.integer]{as.integer()}} on MIC values as by the \R convention on \link{factor}s, it will return the index of the factor levels (which is often useless for regular users).
The function [is.mic()] detects if the input contains class `mic`. If the input is a [data.frame] or [list], it iterates over all columns/items and returns a [logical] vector.
The function \code{\link[=is.mic]{is.mic()}} detects if the input contains class \code{mic}. If the input is a \link{data.frame} or \link{list}, it iterates over all columns/items and returns a \link{logical} vector.
Use [droplevels()] to drop unused levels. At default, it will return a plain factor. Use `droplevels(..., as.mic = TRUE)` to maintain the `mic` class.
Use \code{\link[=droplevels]{droplevels()}} to drop unused levels. At default, it will return a plain factor. Use \code{droplevels(..., as.mic = TRUE)} to maintain the \code{mic} class.
With [rescale_mic()], existing MIC ranges can be limited to a defined range of MIC values. This can be useful to better compare MIC distributions.
With \code{\link[=rescale_mic]{rescale_mic()}}, existing MIC ranges can be limited to a defined range of MIC values. This can be useful to better compare MIC distributions.
For `ggplot2`, use one of the [`scale_*_mic()`][scale_x_mic()] functions to plot MIC values. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values.
For \code{ggplot2}, use one of the \code{\link[=scale_x_mic]{scale_*_mic()}} functions to plot MIC values. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values.
\code{NA_mic_} is a missing value of the new \code{mic} class, analogous to e.g. base \R's \code{\link[base:NA]{NA_character_}}.

6
man/as.sir.Rd
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@@ -155,12 +155,12 @@ The default \code{"conservative"} setting ensures cautious handling of uncertain
\item{clean}{A \link{logical} to indicate whether previously stored results should be forgotten after returning the 'logbook' with results.}
}
\value{
Ordered [factor] with new class `sir`
Ordered \link{factor} with new class \code{sir}
}
\description{
Clean up existing SIR values, or interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI. [as.sir()] transforms the input to a new class [`sir`], which is an ordered [factor] containing the levels `S`, `SDD`, `I`, `R`, `NI`.
Clean up existing SIR values, or interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI. \code{\link[=as.sir]{as.sir()}} transforms the input to a new class \code{\link{sir}}, which is an ordered \link{factor} containing the levels \code{S}, \code{SDD}, \code{I}, \code{R}, \code{NI}.
Breakpoints are currently implemented from EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`, see *Details*. All breakpoints used for interpretation are available in our [clinical_breakpoints] data set.
Breakpoints are currently implemented from EUCAST 2011-2026 and CLSI 2011-2026, see \emph{Details}. All breakpoints used for interpretation are available in our \link{clinical_breakpoints} data set.
}
\details{
\emph{Note: The clinical breakpoints in this package were validated through, and imported from, \href{https://whonet.org}{WHONET}. The public use of this \code{AMR} package has been endorsed by both CLSI and EUCAST. See \link{clinical_breakpoints} for more information.}

2
man/custom_mdro_guideline.Rd
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@@ -12,7 +12,7 @@ custom_mdro_guideline(..., as_factor = TRUE)
\arguments{
\item{...}{Guideline rules in \link[base:tilde]{formula} notation, see below for instructions, and in \emph{Examples}.}
\item{as_factor}{A [logical] to indicate whether the returned value should be an ordered [factor] (`TRUE`, default), or otherwise a [character] vector. For combining rules sets (using [c()]) this value will be inherited from the first set at default.}
\item{as_factor}{A \link{logical} to indicate whether the returned value should be an ordered \link{factor} (\code{TRUE}, default), or otherwise a \link{character} vector. For combining rules sets (using \code{\link[=c]{c()}}) this value will be inherited from the first set at default.}
\item{x}{Existing custom MDRO rules}
}

4
man/join.Rd
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@@ -39,9 +39,9 @@ a \link{data.frame}
Join the data set \link{microorganisms} easily to an existing data set or to a \link{character} vector.
}
\details{
**Note:** As opposed to the `join()` functions of `dplyr`, [character] vectors are supported and at default existing columns will get a suffix `"2"` and the newly joined columns will not get a suffix.
\strong{Note:} As opposed to the \code{join()} functions of \code{dplyr}, \link{character} vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix.
If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base \R will be used.
If the \code{dplyr} package is installed, their join functions will be used. Otherwise, the much slower \code{\link[=merge]{merge()}} and \code{\link[=interaction]{interaction()}} functions from base \R will be used.
}
\examples{
left_join_microorganisms(as.mo("K. pneumoniae"))

22
man/mdro.Rd
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@@ -67,16 +67,18 @@ eucast_exceptional_phenotypes(x = NULL, only_sir_columns = any(is.sir(x)),
\item{...}{Column names of antimicrobials. To automatically detect antimicrobial column names, do not provide any named arguments; \code{\link[=guess_ab_col]{guess_ab_col()}} will then be used for detection. To manually specify a column, provide its name (case-insensitive) as an argument, e.g. \code{AMX = "amoxicillin"}. To skip a specific antimicrobial, set it to \code{NULL}, e.g. \code{TIC = NULL} to exclude ticarcillin. If a manually defined column does not exist in the data, it will be skipped with a warning.}
}
\value{
- If `verbose` is set to `TRUE`:\cr
A [data.frame] containing columns `row_number`, `microorganism`, `MDRO`, `reason`, `all_nonsusceptible_columns`, `guideline`
- CMI 2012 paper - function [mdr_cmi2012()] or [mdro()]:\cr
Ordered [factor] with levels `Negative` < `Multi-drug-resistant (MDR)` < `Extensively drug-resistant (XDR)` < `Pandrug-resistant (PDR)`
- TB guideline - function [mdr_tb()] or [`mdro(..., guideline = "TB")`][mdro()]:\cr
Ordered [factor] with levels `Negative` < `Mono-resistant` < `Poly-resistant` < `Multi-drug-resistant` < `Extensively drug-resistant`
- German guideline - function [mrgn()] or [`mdro(..., guideline = "MRGN")`][mdro()]:\cr
Ordered [factor] with levels `Negative` < `3MRGN` < `4MRGN`
- Everything else, except for custom guidelines:\cr
Ordered [factor] with levels `Negative` < `Positive, unconfirmed` < `Positive`. The value `"Positive, unconfirmed"` means that, according to the guideline, it is not entirely sure if the isolate is multi-drug resistant and this should be confirmed with additional (e.g. genotypic) tests
\itemize{
\item If \code{verbose} is set to \code{TRUE}:\cr
A \link{data.frame} containing columns \code{row_number}, \code{microorganism}, \code{MDRO}, \code{reason}, \code{all_nonsusceptible_columns}, \code{guideline}
\item CMI 2012 paper - function \code{\link[=mdr_cmi2012]{mdr_cmi2012()}} or \code{\link[=mdro]{mdro()}}:\cr
Ordered \link{factor} with levels \code{Negative} < \code{Multi-drug-resistant (MDR)} < \verb{Extensively drug-resistant (XDR)} < \code{Pandrug-resistant (PDR)}
\item TB guideline - function \code{\link[=mdr_tb]{mdr_tb()}} or \code{\link[=mdro]{mdro(..., guideline = "TB")}}:\cr
Ordered \link{factor} with levels \code{Negative} < \code{Mono-resistant} < \code{Poly-resistant} < \code{Multi-drug-resistant} < \verb{Extensively drug-resistant}
\item German guideline - function \code{\link[=mrgn]{mrgn()}} or \code{\link[=mdro]{mdro(..., guideline = "MRGN")}}:\cr
Ordered \link{factor} with levels \code{Negative} < \verb{3MRGN} < \verb{4MRGN}
\item Everything else, except for custom guidelines:\cr
Ordered \link{factor} with levels \code{Negative} < \verb{Positive, unconfirmed} < \code{Positive}. The value \code{"Positive, unconfirmed"} means that, according to the guideline, it is not entirely sure if the isolate is multi-drug resistant and this should be confirmed with additional (e.g. genotypic) tests
}
}
\description{
Determine which isolates are multidrug-resistant organisms (MDRO) according to international, national, or custom guidelines.

2
man/microorganisms.Rd
View File

@@ -12,7 +12,7 @@ A \link[tibble:tibble]{tibble} with 78 679 observations and 26 variables:
\item \code{status} \cr Status of the taxon, either \code{"accepted"}, \code{"not validly published"}, \code{"synonym"}, or \code{"unknown"}
\item \code{kingdom}, \code{phylum}, \code{class}, \code{order}, \code{family}, \code{genus}, \code{species}, \code{subspecies}\cr Taxonomic rank of the microorganism. Note that for fungi, \emph{phylum} is equal to their taxonomic \emph{division}. Also, for fungi, \emph{subkingdom} and \emph{subdivision} were left out since they do not occur in the bacterial taxonomy.
\item \code{rank}\cr Text of the taxonomic rank of the microorganism, such as \code{"species"} or \code{"genus"}
\item \code{ref}\cr Author(s) and year of related scientific publication. This contains only the \emph{first surname} and year of the \emph{latest} authors, e.g. "Wallis \emph{et al.} 2006 \emph{emend.} Smith and Jones 2018" becomes "Smith \emph{et al.}, 2018". This field is directly retrieved from the source specified in the column \code{source}. Moreover, accents were removed to comply with CRAN that only allows ASCII characters.
\item \code{ref}\cr Abbreviated authority citation for the nomenclatural act that established the current name combination, following ICNP conventions. For species described in their current genus (\emph{sp. nov.}), this is the original description author(s) and year. For species transferred to a different genus (\emph{comb. nov.}), this is the reclassification author(s) and year. Emendations are excluded. For synonyms, this is the authority under which the synonym was originally published. This field is directly retrieved from the source specified in the column \code{source}. Diacritics were removed to comply with CRAN, that only allows ASCII characters.
\item \code{oxygen_tolerance} \cr Oxygen tolerance, either \code{"aerobe"}, \code{"anaerobe"}, \code{"anaerobe/microaerophile"}, \code{"facultative anaerobe"}, \code{"likely facultative anaerobe"}, \code{"microaerophile"}, or NA. These data were retrieved from BacDive (see \emph{Source}). Items that contain "likely" are missing from BacDive and were extrapolated from other species within the same genus to guess the oxygen tolerance. Currently 68.3\% of all ~39 000 bacteria in the data set contain an oxygen tolerance.
\item \code{source}\cr Either \code{"GBIF"}, \code{"LPSN"}, \code{"Manually added"}, \code{"MycoBank"}, or \code{"manually added"} (see \emph{Source})
\item \code{lpsn}\cr Identifier ('Record number') of List of Prokaryotic names with Standing in Nomenclature (LPSN). This will be the first/highest LPSN identifier to keep one identifier per row. For example, \emph{Acetobacter ascendens} has LPSN Record number 7864 and 11011. Only the first is available in the \code{microorganisms} data set. \emph{\strong{This is a unique identifier}}, though available for only ~33 000 records.

50
man/mo_property.Rd
View File

@@ -168,44 +168,50 @@ The default is \code{FALSE}, which will return a note if outdated taxonomic name
\item{property}{One of the column names of the \link{microorganisms} data set: \code{"mo"}, \code{"fullname"}, \code{"status"}, \code{"kingdom"}, \code{"phylum"}, \code{"class"}, \code{"order"}, \code{"family"}, \code{"genus"}, \code{"species"}, \code{"subspecies"}, \code{"rank"}, \code{"ref"}, \code{"oxygen_tolerance"}, \code{"source"}, \code{"lpsn"}, \code{"lpsn_parent"}, \code{"lpsn_renamed_to"}, \code{"mycobank"}, \code{"mycobank_parent"}, \code{"mycobank_renamed_to"}, \code{"gbif"}, \code{"gbif_parent"}, \code{"gbif_renamed_to"}, \code{"prevalence"}, or \code{"snomed"}, or must be \code{"shortname"}.}
}
\value{
- An [integer] in case of [mo_year()]
- An [ordered factor][factor] in case of [mo_pathogenicity()]
- A [list] in case of [mo_taxonomy()], [mo_synonyms()], [mo_snomed()], and [mo_info()]
- A [logical] in case of [mo_is_anaerobic()], [mo_is_gram_negative()], [mo_is_gram_positive()], [mo_is_intrinsic_resistant()], and [mo_is_yeast()]
- A named [character] in case of [mo_synonyms()] and [mo_url()]
- A [character] in all other cases
\itemize{
\item An \link{integer} in case of \code{\link[=mo_year]{mo_year()}}
\item An \link[=factor]{ordered factor} in case of \code{\link[=mo_pathogenicity]{mo_pathogenicity()}}
\item A \link{list} in case of \code{\link[=mo_taxonomy]{mo_taxonomy()}}, \code{\link[=mo_synonyms]{mo_synonyms()}}, \code{\link[=mo_snomed]{mo_snomed()}}, and \code{\link[=mo_info]{mo_info()}}
\item A \link{logical} in case of \code{\link[=mo_is_anaerobic]{mo_is_anaerobic()}}, \code{\link[=mo_is_gram_negative]{mo_is_gram_negative()}}, \code{\link[=mo_is_gram_positive]{mo_is_gram_positive()}}, \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}}, and \code{\link[=mo_is_yeast]{mo_is_yeast()}}
\item A named \link{character} in case of \code{\link[=mo_synonyms]{mo_synonyms()}} and \code{\link[=mo_url]{mo_url()}}
\item A \link{character} in all other cases
}
}
\description{
Use these functions to return a specific property of a microorganism based on the latest accepted taxonomy. All input values will be evaluated internally with \code{\link[=as.mo]{as.mo()}}, which makes it possible to use microbial abbreviations, codes and names as input. See \emph{Examples}.
}
\details{
All functions will, at default, **not** keep old taxonomic properties, as synonyms are automatically replaced with the current taxonomy. Take for example *Enterobacter aerogenes*, which was initially named in 1960 but renamed to *Klebsiella aerogenes* in 2017:
- `mo_genus("Enterobacter aerogenes")` will return `"Klebsiella"` (with a note about the renaming)
- `mo_genus("Enterobacter aerogenes", keep_synonyms = TRUE)` will return `"Enterobacter"` (with a once-per-session warning that the name is outdated)
- `mo_ref("Enterobacter aerogenes")` will return `"Tindall et al., 2017"` (with a note about the renaming)
- `mo_ref("Enterobacter aerogenes", keep_synonyms = TRUE)` will return `"Hormaeche et al., 1960"` (with a once-per-session warning that the name is outdated)
All functions will, at default, \strong{not} keep old taxonomic properties, as synonyms are automatically replaced with the current taxonomy. Take for example \emph{Enterobacter aerogenes}, which was initially named in 1960 but renamed to \emph{Klebsiella aerogenes} in 2017:
\itemize{
\item \code{mo_genus("Enterobacter aerogenes")} will return \code{"Klebsiella"} (with a note about the renaming)
\item \code{mo_genus("Enterobacter aerogenes", keep_synonyms = TRUE)} will return \code{"Enterobacter"} (with a once-per-session warning that the name is outdated)
\item \code{mo_ref("Enterobacter aerogenes")} will return \code{"Tindall et al., 2017"} (with a note about the renaming)
\item \code{mo_ref("Enterobacter aerogenes", keep_synonyms = TRUE)} will return \code{"Hormaeche et al., 1960"} (with a once-per-session warning that the name is outdated)
}
The short name ([mo_shortname()]) returns the first character of the genus and the full species, such as `"E. coli"`, for species and subspecies. Exceptions are abbreviations of staphylococci (such as *"CoNS"*, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as *"GBS"*, Group B Streptococci). Please bear in mind that e.g. *E. coli* could mean *Escherichia coli* (kingdom of Bacteria) as well as *Entamoeba coli* (kingdom of Protozoa). Returning to the full name will be done using [as.mo()] internally, giving priority to bacteria and human pathogens, i.e. `"E. coli"` will be considered *Escherichia coli*. As a result, `mo_fullname(mo_shortname("Entamoeba coli"))` returns `"Escherichia coli"`.
\code{\link[=mo_ref]{mo_ref()}} returns the abbreviated authority of the nomenclatural act that created the queried name combination. When \code{keep_synonyms = FALSE} (default), this is the authority of the currently accepted name. When \code{keep_synonyms = TRUE}, this is the authority under which the queried (possibly outdated) name was published. Emendations (changes to the species description without a name change) are not reflected; only the combination or original description authority is returned.
Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions [mo_kingdom()] and [mo_domain()] return the exact same results.
The short name (\code{\link[=mo_shortname]{mo_shortname()}}) returns the first character of the genus and the full species, such as \code{"E. coli"}, for species and subspecies. Exceptions are abbreviations of staphylococci (such as \emph{"CoNS"}, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as \emph{"GBS"}, Group B Streptococci). Please bear in mind that e.g. \emph{E. coli} could mean \emph{Escherichia coli} (kingdom of Bacteria) as well as \emph{Entamoeba coli} (kingdom of Protozoa). Returning to the full name will be done using \code{\link[=as.mo]{as.mo()}} internally, giving priority to bacteria and human pathogens, i.e. \code{"E. coli"} will always be considered \emph{Escherichia coli}. As a result, \code{mo_fullname(mo_shortname("Entamoeba coli"))} returns \code{"Escherichia coli"}.
Determination of human pathogenicity ([mo_pathogenicity()]) is strongly based on Bartlett *et al.* (2022, \doi{10.1099/mic.0.001269}). This function returns a [factor] with the levels *Pathogenic*, *Potentially pathogenic*, *Non-pathogenic*, and *Unknown*.
Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions \code{\link[=mo_kingdom]{mo_kingdom()}} and \code{\link[=mo_domain]{mo_domain()}} return the exact same results.
Determination of the Gram stain ([mo_gramstain()]) will be based on the taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318/)), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were later renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, [PMID 34694987](https://pubmed.ncbi.nlm.nih.gov/34694987/)). Bacteria in these phyla are considered Gram-positive in this `AMR` package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [mo_is_gram_negative()] and [mo_is_gram_positive()] always return `TRUE` or `FALSE` (or `NA` when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
Determination of human pathogenicity (\code{\link[=mo_pathogenicity]{mo_pathogenicity()}}) is strongly based on Bartlett \emph{et al.} (2022, \doi{10.1099/mic.0.001269}). This function returns a \link{factor} with the levels \emph{Pathogenic}, \emph{Potentially pathogenic}, \emph{Non-pathogenic}, and \emph{Unknown}.
Determination of yeasts ([mo_is_yeast()]) will be based on the taxonomic kingdom and class. *Budding yeasts* are yeasts that reproduce asexually through a process called budding, where a new cell develops from a small protrusion on the parent cell. Taxonomically, these are members of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes) or Pichiomycetes. *True yeasts* quite specifically refers to yeasts in the underlying order Saccharomycetales (such as *Saccharomyces cerevisiae*). Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes or Pichiomycetes, the function will return `TRUE`. It returns `FALSE` otherwise (or `NA` when the input is `NA` or the MO code is `UNKNOWN`).
Determination of the Gram stain (\code{\link[=mo_gramstain]{mo_gramstain()}} is based on the taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, \href{https://pubmed.ncbi.nlm.nih.gov/11837318/}{PMID 11837318}), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were later renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, \href{https://pubmed.ncbi.nlm.nih.gov/34694987/}{PMID 34694987}). Bacteria in these phyla are considered Gram-positive in this \code{AMR} package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value \code{NA}. Functions \code{\link[=mo_is_gram_negative]{mo_is_gram_negative()}} and \code{\link[=mo_is_gram_positive]{mo_is_gram_positive()}} always return \code{TRUE} or \code{FALSE} (or \code{NA} when the input is \code{NA} or the MO code is \code{UNKNOWN}), thus always return \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
Determination of intrinsic resistance ([mo_is_intrinsic_resistant()]) will be based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(names(EUCAST_VERSION_EXPECTED_PHENOTYPES[1]))`. The [mo_is_intrinsic_resistant()] function can be vectorised over both argument `x` (input for microorganisms) and `ab` (input for antimicrobials).
Determination of yeasts (\code{\link[=mo_is_yeast]{mo_is_yeast()}}) is based on the taxonomic kingdom and class. \emph{Budding yeasts} are yeasts that reproduce asexually through a process called budding, where a new cell develops from a small protrusion on the parent cell. Taxonomically, these are members of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes) or Pichiomycetes. \emph{True yeasts} quite specifically refers to yeasts in the underlying order Saccharomycetales (such as \emph{Saccharomyces cerevisiae}). Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes or Pichiomycetes, the function will return \code{TRUE}. It returns \code{FALSE} otherwise (or \code{NA} when the input is \code{NA} or the MO code is \code{UNKNOWN}).
Determination of bacterial oxygen tolerance ([mo_oxygen_tolerance()]) will be based on BacDive, see *Source*. The function [mo_is_anaerobic()] only returns `TRUE` if the oxygen tolerance is `"anaerobe"`, indicting an obligate anaerobic species or genus. It always returns `FALSE` for species outside the taxonomic kingdom of Bacteria.
Determination of intrinsic resistance (\code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}}) is based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/bacteria/important-additional-information/expert-rules/}{'EUCAST Expected Resistant Phenotypes' v1.2} (2023). The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} function can be vectorised over both argument \code{x} (input for microorganisms) and \code{ab} (input for antimicrobials).
The function [mo_url()] will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species. [This MycoBank URL](`r TAXONOMY_VERSION$MycoBank$url`) will be used for fungi wherever available , [this LPSN URL](`r TAXONOMY_VERSION$MycoBank$url`) for bacteria wherever available, and [this GBIF link](`r TAXONOMY_VERSION$GBIF$url`) otherwise.
Determination of bacterial oxygen tolerance (\code{\link[=mo_oxygen_tolerance]{mo_oxygen_tolerance()}}) is based on BacDive, see \emph{Source}. The function \code{\link[=mo_is_anaerobic]{mo_is_anaerobic()}} only returns \code{TRUE} if the oxygen tolerance is \code{"anaerobe"}, indicting an obligate anaerobic species or genus. It always returns \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
SNOMED codes ([mo_snomed()]) was last updated on `r documentation_date(TAXONOMY_VERSION$SNOMED$accessed_date)`. See *Source* and the [microorganisms] data set for more info.
The function \code{\link[=mo_url]{mo_url()}} will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species. \href{https://www.mycobank.org}{This MycoBank URL} is used for fungi wherever available , \href{https://www.mycobank.org}{this LPSN URL} for bacteria wherever available, and \href{https://www.gbif.org}{this GBIF link} otherwise.
Old taxonomic names (so-called 'synonyms') can be retrieved with [mo_synonyms()] (which will have the scientific reference as [name][base::names()]), the current taxonomic name can be retrieved with [mo_current()]. Both functions return full names.
SNOMED codes (\code{\link[=mo_snomed]{mo_snomed()}}) was last updated on July 16th, 2024. See \emph{Source} and the \link{microorganisms} data set for more info.
All output [will be translated][translate] where possible.
Old taxonomic names (so-called 'synonyms') can be retrieved with \code{\link[=mo_synonyms]{mo_synonyms()}} (which will have the scientific reference as \link[base:names]{name}), the current taxonomic name can be retrieved with \code{\link[=mo_current]{mo_current()}}. Both functions return full names.
All output \link[=translate]{will be translated} where possible.
}
\section{Matching Score for Microorganisms}{