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(v3.0.1.9088) add version number to intrinsic_resistant

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dr. M.S. (Matthijs) Berends
2026-09-03 12:14:25 +02:00
parent 2c33297cf6
commit bbdd3a92e2
23 changed files with 94 additions and 87 deletions
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6
DESCRIPTION
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@@ -1,6 +1,6 @@
Package: AMR
Version: 3.0.1.9087
Date: 2026-08-20
Version: 3.0.1.9088
Date: 2026-09-03
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)
data analysis and to work with microbial and antimicrobial properties by
@@ -72,5 +72,5 @@ BugReports: https://github.com/msberends/AMR/issues
License: GPL-2 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Roxygen: list(markdown = TRUE)
Config/roxygen2/version: 8.1.0

42
NAMESPACE
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@@ -474,22 +474,26 @@ if(getRversion() >= "3.0.0") S3method(vctrs::vec_ptype2, sir.default)
if(getRversion() >= "3.0.0") S3method(vctrs::vec_ptype2, sir.sir)
if(getRversion() >= "3.0.0") S3method(vctrs::vec_ptype_abbr, disk)
if(getRversion() >= "3.0.0") S3method(vctrs::vec_ptype_full, disk)
importFrom(graphics,arrows)
importFrom(graphics,axis)
importFrom(graphics,barplot)
importFrom(graphics,hist)
importFrom(graphics,legend)
importFrom(graphics,mtext)
importFrom(graphics,plot)
importFrom(graphics,points)
importFrom(graphics,text)
importFrom(stats,complete.cases)
importFrom(stats,glm)
importFrom(stats,lm)
importFrom(stats,median)
importFrom(stats,pchisq)
importFrom(stats,prcomp)
importFrom(stats,predict)
importFrom(stats,qchisq)
importFrom(stats,quantile)
importFrom(stats,var)
importFrom(graphics,
arrows,
axis,
barplot,
hist,
legend,
mtext,
plot,
points,
text
)
importFrom(stats,
complete.cases,
glm,
lm,
median,
pchisq,
prcomp,
predict,
qchisq,
quantile,
var
)

2
NEWS.md
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@@ -1,4 +1,4 @@
# AMR 3.0.1.9087
# AMR 3.0.1.9088
Planned as v3.1.0, end of September 2026.

9
R/data.R
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@@ -313,12 +313,12 @@
#'
#' ### Imported From WHONET
#' Some breakpoints in this package were validated through and imported from [WHONET](https://whonet.org), a free desktop Windows application developed and supported by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance. More can be read on [their website](https://whonet.org). The developers of WHONET and this `AMR` package have been in contact about sharing their work. We highly appreciate their great development on the WHONET software.
#'
#'
#' From WHONET, imported were:
#'
#'
#' * All CLSI breakpoints, including ECOFF
#' * EUCAST breakpoints between `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))` and 2018
#'
#'
#' EUCAST breakpoints from 2019 onwards, were retrieved directly from <https://www.eucast.org>.
#'
#' Our import and reproduction script can be found here: <https://github.com/msberends/AMR/blob/main/data-raw/_reproduction_scripts/reproduction_of_clinical_breakpoints.R>.
@@ -340,8 +340,9 @@
#' @format A [tibble][tibble::tibble] with `r format(nrow(intrinsic_resistant), big.mark = " ")` observations and `r ncol(intrinsic_resistant)` variables:
#' - `mo`\cr Microorganism ID which occurs in [`microorganisms$mo`][microorganisms]. Names can be retrieved using [mo_name()].
#' - `ab`\cr Antimicrobial ID which occurs in [`antimicrobials$ab`][antimicrobials]. Names can be retrieved using [ab_name()].
#' - `version`\cr Guideline name and version.
#' @details
#' This data set is currently based on `r format_eucast_version_nr(names(EUCAST_VERSION_EXPECTED_PHENOTYPES[1]))`.
#' This data set is currently strictly follows `r format_eucast_version_nr(names(EUCAST_VERSION_EXPECTED_PHENOTYPES[1]))`. The
#'
#' This data set is internally used by:
#' * [not_intrinsic_resistant()] (an [antimicrobial selector][antimicrobial_selectors])

3
data-raw/_reproduction_scripts/reproduction_of_intrinsic_resistant.R
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@@ -61,6 +61,9 @@ all(int_resis3$ab %in% antimicrobials$ab)
intrinsic_resistant <- int_resis3
intrinsic_resistant$version <- paste(EUCAST_VERSION_EXPECTED_PHENOTYPES$`1.2`$title,
EUCAST_VERSION_EXPECTED_PHENOTYPES$`1.2`$version_txt)
usethis::use_data(intrinsic_resistant, internal = FALSE, overwrite = TRUE, version = 2, compress = "xz")
rm(intrinsic_resistant)

3
data-raw/_reproduction_scripts/reproduction_of_microorganisms.R
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@@ -2361,6 +2361,7 @@ mo_family <- mo_family %>%
# construct code part for genus - keep old code where available and generate new ones where needed
mo_genus <- taxonomy %>%
filter(rank == "genus") %>%
arrange(status, fullname) %>% # sort on accepted < synonym < unknown, added 2026-09-03
distinct(domain, genus) %>%
# get available old MO codes
left_join(
@@ -2427,6 +2428,7 @@ mo_genus <- mo_genus %>%
# same for species - keep old where available and create new per domain-genus where needed:
mo_species <- taxonomy %>%
filter(rank == "species") %>%
arrange(status, fullname) %>% # sort on accepted < synonym < unknown, added 2026-09-03
distinct(domain, genus, species) %>%
left_join(
existing_mo_tbl %>%
@@ -2488,6 +2490,7 @@ mo_species <- mo_species %>%
# same for subspecies - keep old where available and create new per domain-genus-species where needed:
mo_subspecies <- taxonomy %>%
filter(rank == "subspecies") %>%
arrange(status, fullname) %>% # sort on accepted < synonym < unknown, added 2026-09-03
distinct(domain, genus, species, subspecies) %>%
left_join(
existing_mo_tbl %>%

BIN
data/intrinsic_resistant.rda
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59
index.md
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@@ -27,9 +27,12 @@
<div style="display: flex; font-size: 0.8em;">
<p style="text-align:left; width: 50%;">
<small><a href="https://amr-for-r.org/">amr-for-r.org</a></small>
</p>
<p style="text-align:right; width: 50%;">
<small><a href="https://doi.org/10.18637/jss.v104.i03" target="_blank">doi.org/10.18637/jss.v104.i03</a></small>
</p>
@@ -59,7 +62,7 @@ times](https://scholar.google.com/citations?view_op=view_citation&hl=en&citation
in scientific research.
After installing this package, R knows [**~97 000 distinct microbial
species**](./reference/microorganisms.html) (updated mei 2026) and all
species**](./reference/microorganisms.html) (updated May 2026) and all
[**~620 antimicrobial and antiviral
drugs**](./reference/antimicrobials.html) by name and code (including
ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all
@@ -170,13 +173,11 @@ example_isolates %>%
#> ℹ Using column mo as input for `mo_fullname()`
#> ℹ Using column mo as input for `mo_is_gram_negative()`
#> ℹ Using column mo as input for `mo_is_intrinsic_resistant()`
#> ℹ Determining intrinsic resistance based on 'EUCAST Expected
#> Resistant Phenotypes' v1.2 (2023). This note will be shown
#> once per session.
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
#> (tobramycin), AMK (amikacin), and KAN (kanamycin)
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
#> (meropenem)
#> ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant Phenotypes' v1.2 (2023).
#> This note will be shown once per session.
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN
#> (kanamycin)
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
#> # A tibble: 35 × 7
#> bacteria GEN TOB AMK KAN IPM MEM
#> <chr> <sir> <sir> <sir> <sir> <sir> <sir>
@@ -226,8 +227,8 @@ wisca(example_isolates,
```
| Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:------------------------|:-------------------------------------|:-------------------------------------|
| 70% (64.8-75.1%) | 93.6% (92.1-95%) | 89.9% (86.9-92.3%) |
|:---|:---|:---|
| 70.2% (64.6-75.4%) | 93.6% (92.1-95%) | 89.9% (87-92.5%) |
WISCA supports stratification by any clinical variable, so you can
generate syndrome-specific or ward-specific coverage estimates:
@@ -241,10 +242,10 @@ wisca(example_isolates,
```
| Syndromic Group | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:----------------|:------------------------|:-------------------------------------|:-------------------------------------|
| Clinical | 74.7% (69-80.3%) | 93.6% (92-95.2%) | 90.4% (86.8-93.1%) |
| ICU | 56.9% (48.7-66%) | 86.8% (83.6-90%) | 82.8% (78.3-87.3%) |
| Outpatient | 57.2% (46-68.2%) | 76.5% (70.3-82.2%) | 67.7% (57.3-77.2%) |
|:---|:---|:---|:---|
| Clinical | 74.7% (68.9-80.8%) | 93.7% (92.1-95.2%) | 90.5% (87-93.2%) |
| ICU | 57% (48.2-65.7%) | 86.8% (83.4-89.8%) | 83% (78-87.6%) |
| Outpatient | 57.2% (46.2-68.9%) | 76.6% (70.1-82.1%) | 67.7% (57.6-77.5%) |
**For AMR surveillance**, traditional antibiograms remain the right tool
for tracking resistance per species over time:
@@ -253,14 +254,13 @@ for tracking resistance per species over time:
antibiogram(example_isolates,
mo_transform = "gramstain",
antimicrobials = c("AMC", carbapenems(), "TZP"))
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
#> (meropenem)
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
```
| Pathogen | Amoxicillin/clavulanic acid | Imipenem | Meropenem | Piperacillin/tazobactam |
|:--------------|:----------------------------|:--------------------|:---------------------|:------------------------|
| Gram-negative | 76% (73-79%,N=726) | 99% (98-100%,N=631) | 100% (99-100%,N=626) | 88% (85-91%,N=641) |
| Gram-positive | 76% (74-79%,N=1138) | 81% (75-85%,N=257) | 77% (70-82%,N=203) | 86% (82-89%,N=345) |
| Pathogen | Amoxicillin/clavulanic acid | Imipenem | Meropenem | Piperacillin/tazobactam |
|:---|:---|:---|:---|:---|
| Gram-negative | 76% (73-79%,N=726) | 99% (98-100%,N=631) | 100% (99-100%,N=626) | 88% (85-91%,N=641) |
| Gram-positive | 76% (74-79%,N=1138) | 81% (75-85%,N=257) | 77% (70-82%,N=203) | 86% (82-89%,N=345) |
Combination antibiograms show the additional coverage gained by adding a
second agent, stratified by species:
@@ -271,10 +271,10 @@ antibiogram(example_isolates,
antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"))
```
| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:--------------|:------------------------|:-------------------------------------|:-------------------------------------|
| Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) |
| Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) |
| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:---|:---|:---|:---|
| Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) |
| Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) |
Like many other functions in this package, `antibiogram()` and `wisca()`
come with support for 28 languages that are often detected automatically
@@ -369,16 +369,15 @@ out <- example_isolates %>%
# calculate AMR using resistance(), over all aminoglycosides and polymyxins:
summarise(across(c(aminoglycosides(), polymyxins()),
resistance))
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
#> (tobramycin), AMK (amikacin), and KAN (kanamycin)
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN
#> (kanamycin)
#> ℹ For `polymyxins()` using column COL (colistin)
#> Warning: There was 1 warning in `summarise()`.
#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()),
#> resistance)`.
#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.
#> ℹ In group 3: `ward = "Outpatient"`.
#> Caused by warning:
#> ! Introducing NA: only 23 results available for KAN in group:
#> ward = "Outpatient" (whilst `minimum = 30`).
#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" (whilst `minimum =
#> 30`).
out
#> # A tibble: 3 × 6
#> ward GEN TOB AMK KAN COL

1
man/AMR.Rd
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@@ -59,6 +59,7 @@ Useful links:
Authors:
\itemize{
\item Matthijs S. Berends \email{m.s.berends@umcg.nl} (\href{https://orcid.org/0000-0001-7620-1800}{ORCID})
\item Dennis Souverein (\href{https://orcid.org/0000-0003-0455-0336}{ORCID}) [contributor]
\item Erwin E. A. Hassing [contributor]
}

10
man/amr_course.Rd
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@@ -11,16 +11,16 @@ amr_course(github_repo, branch = "main", ...)
\item{branch}{A character string specifying the branch to download. Defaults to \code{"main"}.}
\item{...}{Additional arguments passed on to \code{\link[usethis:zip-utils]{usethis::use_course()}}.}
\item{...}{Additional arguments passed on to \code{\link[usethis:use_course]{usethis::use_course()}}.}
}
\value{
Called for its side effect. \code{\link[usethis:zip-utils]{usethis::use_course()}} will prompt the user to choose a destination and open the extracted project. Returns invisibly whatever \code{\link[usethis:zip-utils]{usethis::use_course()}} returns.
Called for its side effect. \code{\link[usethis:use_course]{usethis::use_course()}} will prompt the user to choose a destination and open the extracted project. Returns invisibly whatever \code{\link[usethis:use_course]{usethis::use_course()}} returns.
}
\description{
Downloads and unpacks a GitHub repository containing course materials, using \code{\link[usethis:zip-utils]{usethis::use_course()}}. This is a convenience wrapper intended for use in educational settings, such as workshops or tutorials associated with the AMR package.
Downloads and unpacks a GitHub repository containing course materials, using \code{\link[usethis:use_course]{usethis::use_course()}}. This is a convenience wrapper intended for use in educational settings, such as workshops or tutorials associated with the AMR package.
}
\details{
This function constructs a ZIP archive URL from the provided \code{github_repo} and \code{branch}, then delegates to \code{\link[usethis:zip-utils]{usethis::use_course()}} to handle the download and extraction.
This function constructs a ZIP archive URL from the provided \code{github_repo} and \code{branch}, then delegates to \code{\link[usethis:use_course]{usethis::use_course()}} to handle the download and extraction.
The function is designed for interactive use in course or workshop settings and is not intended for use in non-interactive or automated pipelines.
}
@@ -32,5 +32,5 @@ amr_course("https://github.com/my_user_name/our_AMR_course")
}
}
\seealso{
\code{\link[usethis:zip-utils]{usethis::use_course()}}
\code{\link[usethis:use_course]{usethis::use_course()}}
}

2
man/antibiogram.Rd
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@@ -109,7 +109,7 @@ wisca_plot(
\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 \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{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_when]{case_when()}}. See \emph{Examples}.}
\item{only_all_tested}{(for combination antibiograms): a \link{logical} to indicate that isolates must be tested for all antimicrobials, see \emph{Details}.}

2
man/as.ab.Rd
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@@ -1,6 +1,5 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ab.R
\docType{data}
\name{as.ab}
\alias{as.ab}
\alias{ab}
@@ -122,4 +121,3 @@ if (require("dplyr")) {
\item \code{\link[=ab_from_text]{ab_from_text()}} for a function to retrieve antimicrobial drugs from clinical text (from health care records)
}
}
\keyword{datasets}

5
man/as.disk.Rd
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@@ -1,15 +1,11 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/disk.R
\docType{data}
\name{as.disk}
\alias{as.disk}
\alias{disk}
\alias{NA_disk_}
\alias{is.disk}
\title{Transform Input to Disk Diffusion Diameters}
\format{
An object of class \code{disk} (inherits from \code{integer}) of length 1.
}
\usage{
as.disk(x, na.rm = FALSE)
@@ -68,4 +64,3 @@ as.sir(df, uti = TRUE)
\seealso{
\code{\link[=as.sir]{as.sir()}}
}
\keyword{datasets}

2
man/as.mic.Rd
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@@ -1,6 +1,5 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mic.R
\docType{data}
\name{as.mic}
\alias{as.mic}
\alias{mic}
@@ -154,4 +153,3 @@ if (require("ggplot2")) {
\seealso{
\code{\link[=as.sir]{as.sir()}}
}
\keyword{datasets}

2
man/as.mo.Rd
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@@ -1,6 +1,5 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mo.R
\docType{data}
\name{as.mo}
\alias{as.mo}
\alias{mo}
@@ -274,4 +273,3 @@ mo_is_intrinsic_resistant("ESCCOL", ab = "vanco")
The \code{\link[=mo_property]{mo_*}} functions (such as \code{\link[=mo_genus]{mo_genus()}}, \code{\link[=mo_gramstain]{mo_gramstain()}}) to get properties based on the returned code.
}
\keyword{datasets}

2
man/as.sir.Rd
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@@ -1,6 +1,5 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sir.R
\docType{data}
\name{as.sir}
\alias{as.sir}
\alias{sir}
@@ -520,4 +519,3 @@ For interpretations of minimum inhibitory concentration (MIC) values and disk di
\seealso{
\code{\link[=as.mic]{as.mic()}}, \code{\link[=as.disk]{as.disk()}}, \code{\link[=as.mo]{as.mo()}}
}
\keyword{datasets}

10
man/clinical_breakpoints.Rd
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@@ -48,7 +48,15 @@ The default is \code{"human"}, which can also be set with the package option \co
\subsection{Imported From WHONET}{
Clinical breakpoints in this package were validated through and imported from \href{https://whonet.org}{WHONET}, a free desktop Windows application developed and supported by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance. More can be read on \href{https://whonet.org}{their website}. The developers of WHONET and this \code{AMR} package have been in contact about sharing their work. We highly appreciate their great development on the WHONET software.
Some breakpoints in this package were validated through and imported from \href{https://whonet.org}{WHONET}, a free desktop Windows application developed and supported by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance. More can be read on \href{https://whonet.org}{their website}. The developers of WHONET and this \code{AMR} package have been in contact about sharing their work. We highly appreciate their great development on the WHONET software.
From WHONET, imported were:
\itemize{
\item All CLSI breakpoints, including ECOFF
\item EUCAST breakpoints between 2011 and 2018
}
EUCAST breakpoints from 2019 onwards, were retrieved directly from \url{https://www.eucast.org}.
Our import and reproduction script can be found here: \url{https://github.com/msberends/AMR/blob/main/data-raw/_reproduction_scripts/reproduction_of_clinical_breakpoints.R}.
}

2
man/custom_interpretive_rules.Rd
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@@ -19,7 +19,7 @@ Define custom interpretive rules for your organisation or specific analysis and
Some organisations have their own adoption of interpretive rules. This function can be used to define custom rules to be used in the \code{\link[=interpretive_rules]{interpretive_rules()}} function.
\subsection{Basics}{
If you are familiar with the \code{\link[dplyr:case-and-replace-when]{case_when()}} function of the \code{dplyr} package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written \emph{before} the tilde (\code{~}) and the consequence of the rule is written \emph{after} the tilde:
If you are familiar with the \code{\link[dplyr:case_when]{case_when()}} function of the \code{dplyr} package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written \emph{before} the tilde (\code{~}) and the consequence of the rule is written \emph{after} the tilde:
\if{html}{\out{<div class="sourceCode r">}}\preformatted{x <- custom_interpretive_rules(TZP == "S" ~ aminopenicillins == "S",
TZP == "R" ~ aminopenicillins == "R")

2
man/custom_mdro_guideline.Rd
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@@ -26,7 +26,7 @@ Define custom a MDRO guideline for your organisation or specific analysis and us
Using a custom MDRO guideline is of importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.
\subsection{Basics}{
If you are familiar with the \code{\link[dplyr:case-and-replace-when]{case_when()}} function of the \code{dplyr} package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written \emph{before} the tilde (\code{~}) and the consequence of the rule is written \emph{after} the tilde:
If you are familiar with the \code{\link[dplyr:case_when]{case_when()}} function of the \code{dplyr} package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written \emph{before} the tilde (\code{~}) and the consequence of the rule is written \emph{after} the tilde:
\if{html}{\out{<div class="sourceCode r">}}\preformatted{custom <- custom_mdro_guideline(CIP == "R" & age > 60 ~ "Elderly Type A",
ERY == "R" & age > 60 ~ "Elderly Type B")

2
man/ggplot_sir.Rd
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@@ -98,7 +98,7 @@ At default, the names of antimicrobials will be shown on the plots using \code{\
Additional functions include:
\itemize{
\item \code{\link[=facet_sir]{facet_sir()}} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2:facet_wrap]{ggplot2::facet_wrap()}}.
\item \code{\link[=scale_y_percent]{scale_y_percent()}} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2:scale_continuous]{ggplot2::scale_y_continuous()}}.
\item \code{\link[=scale_y_percent]{scale_y_percent()}} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2:scale_y_continuous]{ggplot2::scale_y_continuous()}}.
\item \code{\link[=scale_sir_colours]{scale_sir_colours()}} sets colours to the bars (green for S, yellow for I, and red for R). with multilingual support. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red.
\item \code{\link[=theme_sir]{theme_sir()}} is a \link[ggplot2:theme]{ggplot2 theme} with minimal distraction.
\item \code{\link[=labels_sir_count]{labels_sir_count()}} print datalabels on the bars with percentage and amount of isolates using \code{\link[ggplot2:geom_text]{ggplot2::geom_text()}}.

5
man/intrinsic_resistant.Rd
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@@ -5,10 +5,11 @@
\alias{intrinsic_resistant}
\title{Data Set Denoting Bacterial Intrinsic Resistance}
\format{
A \link[tibble:tibble]{tibble} with 294 079 observations and 2 variables:
A \link[tibble:tibble]{tibble} with 294 079 observations and 3 variables:
\itemize{
\item \code{mo}\cr Microorganism ID which occurs in \code{\link[=microorganisms]{microorganisms$mo}}. Names can be retrieved using \code{\link[=mo_name]{mo_name()}}.
\item \code{ab}\cr Antimicrobial ID which occurs in \code{\link[=antimicrobials]{antimicrobials$ab}}. Names can be retrieved using \code{\link[=ab_name]{ab_name()}}.
\item \code{version}\cr Guideline name and version.
}
}
\usage{
@@ -18,7 +19,7 @@ intrinsic_resistant
Data set containing 'EUCAST Expected Resistant Phenotypes' of \emph{all} bug-drug combinations between the \link{microorganisms} and \link{antimicrobials} data sets.
}
\details{
This data set is currently based on \href{https://www.eucast.org/bacteria/important-additional-information/expert-rules/}{'EUCAST Expected Resistant Phenotypes' v1.2} (2023).
This data set is currently strictly follows \href{https://www.eucast.org/bacteria/important-additional-information/expert-rules/}{'EUCAST Expected Resistant Phenotypes' v1.2} (2023). The
This data set is internally used by:
\itemize{

8
man/mo_property.Rd
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@@ -349,19 +349,19 @@ All functions will, at default, \strong{not} keep old taxonomic properties, as s
\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.
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"}.
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} (domain of Bacteria) as well as \emph{Entamoeba coli} (domain 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"}.
Following the formal introduction of the new kingdom rank into prokaryotic nomenclature in 2024 (\doi{10.1099/ijsem.0.006242}), \code{\link[=mo_kingdom]{mo_kingdom()}} and \code{\link[=mo_domain]{mo_domain()}} return different results for bacteria and archaea: \code{\link[=mo_kingdom]{mo_kingdom()}} returns the new formal kingdom (e.g. "Pseudomonadati", "Bacillati"), while \code{\link[=mo_domain]{mo_domain()}} returns the new domain (e.g. "Bacteria", "Archaea"). For non-prokaryotic organisms, both functions return identical results.
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 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 the Gram stain (\code{\link[=mo_gramstain]{mo_gramstain()}} is based on the taxonomic domain 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 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 yeasts (\code{\link[=mo_is_yeast]{mo_is_yeast()}}) is based on the taxonomic domain 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 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).
Determination of both bacterial oxygen tolerance (\code{\link[=mo_oxygen_tolerance]{mo_oxygen_tolerance()}}) and morphology (\code{\link[=mo_morphology]{mo_morphology()}}) are 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"}, indicating an obligate anaerobic species or genus. It always returns \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
Determination of both bacterial oxygen tolerance (\code{\link[=mo_oxygen_tolerance]{mo_oxygen_tolerance()}}) and morphology (\code{\link[=mo_morphology]{mo_morphology()}}) are 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"}, indicating an obligate anaerobic species or genus. It always returns \code{FALSE} for species outside the taxonomic domain of Bacteria.
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.

2
man/plot.Rd
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@@ -248,7 +248,7 @@ At default, they translate the S/I/R values to an interpretative text ("Suscepti
This package contains more functions that extend the \code{ggplot2} package, to help in visualising AMR data results. All these functions are internally used by \code{\link[=ggplot_sir]{ggplot_sir()}} too.
\itemize{
\item \code{\link[=facet_sir]{facet_sir()}} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2:facet_wrap]{ggplot2::facet_wrap()}}.
\item \code{\link[=scale_y_percent]{scale_y_percent()}} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2:scale_continuous]{ggplot2::scale_y_continuous()}}.
\item \code{\link[=scale_y_percent]{scale_y_percent()}} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2:scale_y_continuous]{ggplot2::scale_y_continuous()}}.
\item \code{\link[=scale_sir_colours]{scale_sir_colours()}} allows to set colours to any aesthetic, even for \code{shape} or \code{linetype}.
\item \code{\link[=theme_sir]{theme_sir()}} is a \link[ggplot2:theme]{ggplot2 theme} with minimal distraction.
\item \code{\link[=labels_sir_count]{labels_sir_count()}} print datalabels on the bars with percentage and number of isolates, using \code{\link[ggplot2:geom_text]{ggplot2::geom_text()}}.