(v3.0.1.9137) Add the guideline argument to count_df(), proportion_df(), sir_df(), ggplot_sir(), geom_sir(), and labels_sir_count(), so that with CLSI the 'I' category is merged with R, and describe in the documentation of get_AMR_locale() that LANG takes precedence over LANGUAGE

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: AMR
-Version: 3.0.1.9136
+Version: 3.0.1.9137
 Date: 2026-10-15
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 3.0.1.9136
+# AMR 3.0.1.9137
 
 Planned as v3.1.0, mid October 2026.
 
@@ -25,6 +25,7 @@ Planned as v3.1.0, mid October 2026.
 * Parallel computing in `as.sir()`, `antibiogram()`, and `wisca()` now uses the `future` and `future.apply` packages, which is faster. A non-sequential plan (e.g., `future::plan(future::multisession)`) must be active before using `parallel = TRUE` (#281).
 * The options of `capped_mic_handling` in `as.sir()` have been redefined as `"none"`, `"conservative"`, `"standard"` (default), and `"lenient"`. The option `"inverse"` is no longer available (#243).
 * `as.sir()` now returns WT/NWT (Wildtype/Non-wildtype) instead of S/R when using ECOFF-based interpretation with `breakpoint_type = "ECOFF"`. WT/NWT results are fully supported in all resistance and susceptibility functions and in all plots (#254).
+* `count_df()`, `proportion_df()`, and `sir_df()` now follow the `AMR_guideline` option through their new `guideline` argument. With CLSI, `combine_SI = TRUE` merges 'I' with R into `"IR"` and returns `"S"` vs. `"IR"`, consistent with `count_susceptible()` and `susceptibility()`. Previously, these functions always merged 'I' with S, as with EUCAST. Use `guideline = "EUCAST"` for the old behaviour. This also applies to `ggplot_sir()`, `geom_sir()`, and `labels_sir_count()`, which got the same argument.
 
 ### New
 * **Updated clinical breakpoints**
@@ -109,7 +110,7 @@ Planned as v3.1.0, mid October 2026.
   * `wisca()` now follows Bielicki *et al.* (2016) more strictly by using $\text{Beta}(1, 9999)$ for intrinsically resistant pairs, forcing near-zero susceptibility regardless of observed data (based on EUCAST Expected Resistant Phenotypes)
   * Fixed a bug where both functions failed without the `antimicrobials` argument if `tidyselect` was not available, e.g., for binary installations without `dplyr`
 * Resistance and susceptibility calculation
-  * New argument `guideline` (default: EUCAST) in `susceptibility()` and `resistance()` to interpret the 'I' category correctly per guideline
+  * New argument `guideline` (default: EUCAST) in `susceptibility()`, `resistance()`, `count_df()`, `proportion_df()`, `sir_df()`, `ggplot_sir()`, `geom_sir()`, and `labels_sir_count()` to interpret the 'I' category correctly per guideline
   * `count_*()` and `proportion_*()` now handle WT, NWT, NS, and NI results correctly (#321)
 * MICs and disk diffusion
   * New argument `round_to_next_log2` in `as.mic()` and `rescale_mic()` to round values up to the nearest log2 dilution level (#255)
@@ -141,6 +142,7 @@ Planned as v3.1.0, mid October 2026.
 
 ### Other
 * Improved console messages with clickable links throughout the package, powered by `cli` if it is installed (#191, #265)
+* The documentation of `get_AMR_locale()` now describes the actual order in which the language is determined: the `AMR_locale` option, then the `LANG` system variable, then `LANGUAGE` only if `LANG` is not set, and then the system locale
 * Revamped console output of `interpretive_rules()`, with section headers, S/I/R values styled as in the printing of `sir` columns in tibbles, and the summary of edits sorted by SIR level, using `cli` if it is installed (#259)
 * The printing of `custom_interpretive_rules()` and `custom_mdro_guideline()` now styles SIR values as in tibbles, i.e., the colour of `I` depends on the guideline. `WT`, `NWT`, and `NS` were previously shown as `SDD`, `I`, and `R`, and values other than `S` and `R` as `I`.
 * The 'AMR for Python' vignette now contains sections on installation channels (stable from CRAN, or development from GitHub via `AMR.beta`) and on using `enforce_method` in `as_sir()` from Python

R/count.R

@@ -267,7 +267,8 @@ n_sir <- count_all
 count_df <- function(data,
                      translate_ab = "name",
                      language = get_AMR_locale(),
-                     combine_SI = TRUE) {
+                     combine_SI = TRUE,
+                     guideline = getOption("AMR_guideline", "EUCAST")) {
   tryCatch(
     sir_calc_df(
       type = "count",
@@ -275,7 +276,8 @@ count_df <- function(data,
       translate_ab = translate_ab,
       language = language,
       combine_SI = combine_SI,
-      confidence_level = 0.95 # doesn't matter, will be removed
+      confidence_level = 0.95, # doesn't matter, will be removed
+      guideline = guideline
     ),
     error = function(e) stop_(gsub("in sir_calc_df(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )

R/ggplot_sir.R

@@ -174,6 +174,7 @@ ggplot_sir <- function(data,
                        combine_SI = TRUE,
                        minimum = 30,
                        language = get_AMR_locale(),
+                       guideline = getOption("AMR_guideline", "EUCAST"),
                        nrow = NULL,
                        colours = c(
                          S = "#3CAEA3",
@@ -242,7 +243,7 @@ ggplot_sir <- function(data,
     geom_sir(
       position = position, x = x, fill = fill, translate_ab = translate_ab,
       minimum = minimum, language = language,
-      combine_SI = combine_SI, ...
+      combine_SI = combine_SI, guideline = guideline, ...
     ) +
     theme_sir()
 
@@ -263,6 +264,7 @@ ggplot_sir <- function(data,
       minimum = minimum,
       language = language,
       combine_SI = combine_SI,
+      guideline = guideline,
       datalabels.size = datalabels.size,
       datalabels.colour = datalabels.colour
     )
@@ -292,6 +294,7 @@ geom_sir <- function(position = NULL,
                      minimum = 30,
                      language = get_AMR_locale(),
                      combine_SI = TRUE,
+                     guideline = getOption("AMR_guideline", "EUCAST"),
                      ...) {
   x <- x[1]
   stop_ifnot_installed("ggplot2")
@@ -334,7 +337,8 @@ geom_sir <- function(position = NULL,
         translate_ab = translate_ab,
         language = language,
         minimum = minimum,
-        combine_SI = combine_SI
+        combine_SI = combine_SI,
+        guideline = guideline
       )
     },
     mapping = utils::modifyList(ggplot2::aes(), list(x = str2lang(x), y = str2lang(y), fill = str2lang(fill))),

R/plotting.R

@@ -1554,6 +1554,7 @@ labels_sir_count <- function(position = NULL,
                              minimum = 30,
                              language = get_AMR_locale(),
                              combine_SI = TRUE,
+                             guideline = getOption("AMR_guideline", "EUCAST"),
                              datalabels.size = 3,
                              datalabels.colour = "grey15") {
   stop_ifnot_installed("ggplot2")
@@ -1587,7 +1588,8 @@ labels_sir_count <- function(position = NULL,
         translate_ab = translate_ab,
         combine_SI = combine_SI,
         minimum = minimum,
-        language = language
+        language = language,
+        guideline = guideline
       )
       transformed$gr <- transformed[, x_name, drop = TRUE]
       transformed %pm>%

R/proportion.R

@@ -42,9 +42,9 @@
 #'   * EUCAST: [susceptibility()] \eqn{= \%S + \%I}, [resistance()] \eqn{= \%R}
 #'   * CLSI: [susceptibility()] \eqn{= \%S + \%SDD}, [resistance()] \eqn{= \%I + \%R}
 #'
-#' You can also use e.g. [proportion_R()] or [proportion_S()] instead, to be explicit.
+#' You can also use e.g. [proportion_R()] or [proportion_S()] instead, to be explicit. For [proportion_df()], [count_df()], and [sir_df()], the guideline determines how 'I' is merged when `combine_SI = TRUE`.
 #' @inheritParams ab_property
-#' @param combine_SI A [logical] to indicate whether all values of S, SDD, and I must be merged into one, so the output only consists of S+SDD+I vs. R (susceptible vs. resistant) - the default is `TRUE`.
+#' @param combine_SI A [logical] to indicate whether the 'I' category must be merged with another category, so the output only consists of susceptible vs. resistant - the default is `TRUE`. Following the `guideline` argument, the output then consists of `"SI"` (S+SDD+I) vs. `"R"` with EUCAST, and of `"S"` (S+SDD) vs. `"IR"` (I+R) with CLSI.
 #' @param ab_result Antibiotic results to test against, must be one or more values of "S", "SDD", "I", or "R".
 #' @param confidence_level The confidence level for the returned confidence interval. For the calculation, the number of S or SI isolates, and R isolates are compared with the total number of available isolates with R, S, or I by using [binom.test()], i.e., the Clopper-Pearson method.
 #' @param side The side of the confidence interval to return. The default is `"both"` for a length 2 vector, but can also be (abbreviated as) `"min"`/`"left"`/`"lower"`/`"less"` or `"max"`/`"right"`/`"higher"`/`"greater"`.
@@ -431,7 +431,8 @@ proportion_df <- function(data,
                           minimum = 30,
                           as_percent = FALSE,
                           combine_SI = TRUE,
-                          confidence_level = 0.95) {
+                          confidence_level = 0.95,
+                          guideline = getOption("AMR_guideline", "EUCAST")) {
   tryCatch(
     sir_calc_df(
       type = "proportion",
@@ -441,7 +442,8 @@ proportion_df <- function(data,
       minimum = minimum,
       as_percent = as_percent,
       combine_SI = combine_SI,
-      confidence_level = confidence_level
+      confidence_level = confidence_level,
+      guideline = guideline
     ),
     error = function(e) stop_(gsub("in sir_calc_df(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )

R/sir_calc.R

@@ -220,7 +220,8 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
                         minimum = 30,
                         as_percent = FALSE,
                         combine_SI = TRUE,
-                        confidence_level = 0.95) {
+                        confidence_level = 0.95,
+                        guideline = getOption("AMR_guideline", "EUCAST")) {
   meet_criteria(type, is_in = c("proportion", "count", "both"), has_length = 1)
   meet_criteria(data, allow_class = "data.frame")
   data <- ascertain_sir_classes(data, "data")
@@ -230,6 +231,15 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
   meet_criteria(as_percent, allow_class = "logical", has_length = 1)
   meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
   meet_criteria(confidence_level, allow_class = "numeric", has_length = 1)
+  meet_criteria(guideline, allow_class = "character", has_length = 1)
+  if (guideline %like% "EUCAST") {
+    guideline <- "EUCAST"
+  } else if (guideline %like% "CLSI") {
+    guideline <- "CLSI"
+  }
+  meet_criteria(guideline, allow_class = "character", is_in = c("EUCAST", "CLSI"), has_length = 1)
+  # with EUCAST, 'I' is merged with S into 'SI', with CLSI, 'I' is merged with R into 'IR'
+  combined_levels <- if (identical(guideline, "CLSI")) c("S", "IR") else c("SI", "R")
 
   translate_ab <- get_translate_ab(translate_ab)
 
@@ -252,10 +262,12 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
       data[, i] <- as.character(as.sir(data[, i, drop = TRUE]))
       data[which(data[, i, drop = TRUE] %in% c("S", "SDD", "WT")), i] <- "S"
       data[which(data[, i, drop = TRUE] %in% c("R", "NWT", "NS")), i] <- "R"
-      if (isTRUE(combine_SI)) {
+      if (isTRUE(combine_SI) && identical(guideline, "CLSI")) {
+        data[which(data[, i, drop = TRUE] %in% c("I", "R")), i] <- "IR"
+      } else if (isTRUE(combine_SI)) {
         data[which(data[, i, drop = TRUE] %in% c("I", "S")), i] <- "SI"
       }
-      data[which(!data[, i, drop = TRUE] %in% c("S", "SI", "I", "R")), i] <- NA_character_
+      data[which(!data[, i, drop = TRUE] %in% c("S", "SI", "I", "IR", "R")), i] <- NA_character_
     }
   }
 
@@ -277,7 +289,7 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
     for (i in seq_len(ncol(.data))) {
       values <- .data[, i, drop = TRUE]
       if (isTRUE(combine_SI)) {
-        values <- factor(values, levels = c("SI", "R", "NI"), ordered = TRUE)
+        values <- factor(values, levels = c(combined_levels, "NI"), ordered = TRUE)
       } else {
         values <- factor(values, levels = c("S", "SDD", "I", "R", "NI"), ordered = TRUE)
       }
@@ -352,7 +364,7 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
 
   # apply factors for right sorting in interpretation
   if (isTRUE(combine_SI)) {
-    out$interpretation <- factor(out$interpretation, levels = c("SI", "R"), ordered = TRUE)
+    out$interpretation <- factor(out$interpretation, levels = combined_levels, ordered = TRUE)
   } else {
     # don't use as.sir() here, as it would add the class 'sir' and we would like
     # the same data structure as output, regardless of input

R/sir_df.R

@@ -35,7 +35,8 @@ sir_df <- function(data,
                    minimum = 30,
                    as_percent = FALSE,
                    combine_SI = TRUE,
-                   confidence_level = 0.95) {
+                   confidence_level = 0.95,
+                   guideline = getOption("AMR_guideline", "EUCAST")) {
   tryCatch(
     sir_calc_df(
       type = "both",
@@ -45,7 +46,8 @@ sir_df <- function(data,
       minimum = minimum,
       as_percent = as_percent,
       combine_SI = combine_SI,
-      confidence_level = confidence_level
+      confidence_level = confidence_level,
+      guideline = guideline
     ),
     error = function(e) stop_(gsub("in sir_calc_df(): ", "", conditionMessage(e), fixed = TRUE), call = -5)
   )

R/translate.R

@@ -49,14 +49,16 @@
 #' Please read about adding or updating a language in [our Wiki](https://github.com/msberends/AMR/wiki/).
 #'
 #' ### Changing the Default Language
-#' The system language will be used at default (as returned by `Sys.getenv("LANG")` or, if `LANG` is not set, [`Sys.getlocale("LC_COLLATE")`][Sys.getlocale()]), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:
+#' The system language will be used at default, if that language is supported. The language to be used is determined in this order:
 #'
-#'   1. Setting the package option [`AMR_locale`][AMR-options], either by using e.g. `set_AMR_locale("German")` or by running e.g. `options(AMR_locale = "German")`.
+#'   1. The package option [`AMR_locale`][AMR-options], set by using e.g. `set_AMR_locale("German")` or by running e.g. `options(AMR_locale = "German")`.
 #'
 #'      Note that setting an \R option only works in the same session. Save the command `options(AMR_locale = "(your language)")` to your `.Rprofile` file to apply it for every session. Run `utils::file.edit("~/.Rprofile")` to edit your `.Rprofile` file.
-#'   2. Setting the system variable `LANGUAGE` or `LANG`, e.g. by adding `LANGUAGE="de_DE.utf8"` to your `.Renviron` file in your home directory.
+#'   2. The system variable `LANG`, as returned by `Sys.getenv("LANG")`, e.g. set by adding `LANG="de_DE.utf8"` to your `.Renviron` file in your home directory.
+#'   3. The system variable `LANGUAGE`, but only if `LANG` is not set. Note that `LANG` is set on most Linux and macOS systems, in which case `LANGUAGE` has no effect.
+#'   4. The system locale, as returned by [`Sys.getlocale("LC_COLLATE")`][Sys.getlocale()], if neither `LANG` nor `LANGUAGE` is set.
 #'
-#' Thus, if the package option [`AMR_locale`][AMR-options] is set, the system variables `LANGUAGE` and `LANG` will be ignored.
+#' Thus, if the package option [`AMR_locale`][AMR-options] is set, the system variables `LANG` and `LANGUAGE` will be ignored.
 #' @rdname translate
 #' @name translate
 #' @export
@@ -90,7 +92,7 @@ get_AMR_locale <- function() {
     return(validate_language(getOption("AMR_locale"), extra_txt = "set with `options(AMR_locale = ...)`"))
   }
   lang <- ""
-  # now check the LANGUAGE system variable - return it if set
+  # now check the system variables, of which LANG takes precedence over LANGUAGE
   if (!identical("", Sys.getenv("LANGUAGE"))) {
     lang <- Sys.getenv("LANGUAGE")
   }

man/count.Rd

@@ -44,7 +44,8 @@ count_df(
   data,
   translate_ab = "name",
   language = get_AMR_locale(),
-  combine_SI = TRUE
+  combine_SI = TRUE,
+  guideline = getOption("AMR_guideline", "EUCAST")
 )
 }
 \arguments{
@@ -66,7 +67,7 @@ You can also use e.g. \code{\link[=count_R]{count_R()}} or \code{\link[=count_S]
 
 \item{language}{Language of the returned text - the default is the current system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}}) and can also be set with the package option \code{\link[=AMR-options]{AMR_locale}}. Use \code{language = NULL} or \code{language = ""} to prevent translation.}
 
-\item{combine_SI}{A \link{logical} to indicate whether all values of S, SDD, and I must be merged into one, so the output only consists of S+SDD+I vs. R (susceptible vs. resistant) - the default is \code{TRUE}.}
+\item{combine_SI}{A \link{logical} to indicate whether the 'I' category must be merged with another category, so the output only consists of susceptible vs. resistant - the default is \code{TRUE}. Following the \code{guideline} argument, the output then consists of \code{"SI"} (S+SDD+I) vs. \code{"R"} with EUCAST, and of \code{"S"} (S+SDD) vs. \code{"IR"} (I+R) with CLSI.}
 }
 \value{
 An \link{integer}

man/ggplot_sir.Rd

@@ -17,6 +17,7 @@ ggplot_sir(
   combine_SI = TRUE,
   minimum = 30,
   language = get_AMR_locale(),
+  guideline = getOption("AMR_guideline", "EUCAST"),
   nrow = NULL,
   colours = c(S = "#3CAEA3", SDD = "#8FD6C4", SI = "#3CAEA3", I = "#F6D55C", IR =
     "#ED553B", R = "#ED553B"),
@@ -39,6 +40,7 @@ geom_sir(
   minimum = 30,
   language = get_AMR_locale(),
   combine_SI = TRUE,
+  guideline = getOption("AMR_guideline", "EUCAST"),
   ...
 )
 }
@@ -59,12 +61,20 @@ geom_sir(
 
 \item{translate_ab}{A column name of the \link{antimicrobials} data set to translate the antibiotic abbreviations to, using \code{\link[=ab_property]{ab_property()}}.}
 
-\item{combine_SI}{A \link{logical} to indicate whether all values of S, SDD, and I must be merged into one, so the output only consists of S+SDD+I vs. R (susceptible vs. resistant) - the default is \code{TRUE}.}
+\item{combine_SI}{A \link{logical} to indicate whether the 'I' category must be merged with another category, so the output only consists of susceptible vs. resistant - the default is \code{TRUE}. Following the \code{guideline} argument, the output then consists of \code{"SI"} (S+SDD+I) vs. \code{"R"} with EUCAST, and of \code{"S"} (S+SDD) vs. \code{"IR"} (I+R) with CLSI.}
 
 \item{minimum}{The minimum allowed number of available (tested) isolates. Any isolate count lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see \emph{Source}.}
 
 \item{language}{Language of the returned text - the default is the current system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}}) and can also be set with the package option \code{\link[=AMR-options]{AMR_locale}}. Use \code{language = NULL} or \code{language = ""} to prevent translation.}
 
+\item{guideline}{Either \code{"EUCAST"} (default) or \code{"CLSI"}. With EUCAST, the 'I' category will be considered as susceptible (see \href{https://www.eucast.org/bacteria/clinical-breakpoints-and-interpretation/definition-of-s-i-and-r/}{EUCAST website}), but with with CLSI, it will be considered resistant. Therefore:
+\itemize{
+\item EUCAST: \code{\link[=susceptibility]{susceptibility()}} \eqn{= \%S + \%I}, \code{\link[=resistance]{resistance()}} \eqn{= \%R}
+\item CLSI: \code{\link[=susceptibility]{susceptibility()}} \eqn{= \%S + \%SDD}, \code{\link[=resistance]{resistance()}} \eqn{= \%I + \%R}
+}
+
+You can also use e.g. \code{\link[=proportion_R]{proportion_R()}} or \code{\link[=proportion_S]{proportion_S()}} instead, to be explicit. For \code{\link[=proportion_df]{proportion_df()}}, \code{\link[=count_df]{count_df()}}, and \code{\link[=sir_df]{sir_df()}}, the guideline determines how 'I' is merged when \code{combine_SI = TRUE}.}
+
 \item{nrow}{(when using \code{facet}) number of rows.}
 
 \item{colours}{A named vactor with colour to be used for filling. The default colours are colour-blind friendly.}

man/plot.Rd

@@ -159,6 +159,7 @@ labels_sir_count(
   minimum = 30,
   language = get_AMR_locale(),
   combine_SI = TRUE,
+  guideline = getOption("AMR_guideline", "EUCAST"),
   datalabels.size = 3,
   datalabels.colour = "grey15"
 )
@@ -210,7 +211,7 @@ labels_sir_count(
 
 \item{minimum}{The minimum allowed number of available (tested) isolates. Any isolate count lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see \emph{Source}.}
 
-\item{combine_SI}{A \link{logical} to indicate whether all values of S, SDD, and I must be merged into one, so the output only consists of S+SDD+I vs. R (susceptible vs. resistant) - the default is \code{TRUE}.}
+\item{combine_SI}{A \link{logical} to indicate whether the 'I' category must be merged with another category, so the output only consists of susceptible vs. resistant - the default is \code{TRUE}. Following the \code{guideline} argument, the output then consists of \code{"SI"} (S+SDD+I) vs. \code{"R"} with EUCAST, and of \code{"S"} (S+SDD) vs. \code{"IR"} (I+R) with CLSI.}
 
 \item{datalabels.size}{Size of the datalabels.}
 

man/proportion.Rd

@@ -59,7 +59,8 @@ proportion_df(
   minimum = 30,
   as_percent = FALSE,
   combine_SI = TRUE,
-  confidence_level = 0.95
+  confidence_level = 0.95,
+  guideline = getOption("AMR_guideline", "EUCAST")
 )
 
 sir_df(
@@ -69,7 +70,8 @@ sir_df(
   minimum = 30,
   as_percent = FALSE,
   combine_SI = TRUE,
-  confidence_level = 0.95
+  confidence_level = 0.95,
+  guideline = getOption("AMR_guideline", "EUCAST")
 )
 }
 \arguments{
@@ -87,7 +89,7 @@ sir_df(
 \item CLSI: \code{\link[=susceptibility]{susceptibility()}} \eqn{= \%S + \%SDD}, \code{\link[=resistance]{resistance()}} \eqn{= \%I + \%R}
 }
 
-You can also use e.g. \code{\link[=proportion_R]{proportion_R()}} or \code{\link[=proportion_S]{proportion_S()}} instead, to be explicit.}
+You can also use e.g. \code{\link[=proportion_R]{proportion_R()}} or \code{\link[=proportion_S]{proportion_S()}} instead, to be explicit. For \code{\link[=proportion_df]{proportion_df()}}, \code{\link[=count_df]{count_df()}}, and \code{\link[=sir_df]{sir_df()}}, the guideline determines how 'I' is merged when \code{combine_SI = TRUE}.}
 
 \item{ab_result}{Antibiotic results to test against, must be one or more values of "S", "SDD", "I", or "R".}
 
@@ -103,7 +105,7 @@ You can also use e.g. \code{\link[=proportion_R]{proportion_R()}} or \code{\link
 
 \item{language}{Language of the returned text - the default is the current system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}}) and can also be set with the package option \code{\link[=AMR-options]{AMR_locale}}. Use \code{language = NULL} or \code{language = ""} to prevent translation.}
 
-\item{combine_SI}{A \link{logical} to indicate whether all values of S, SDD, and I must be merged into one, so the output only consists of S+SDD+I vs. R (susceptible vs. resistant) - the default is \code{TRUE}.}
+\item{combine_SI}{A \link{logical} to indicate whether the 'I' category must be merged with another category, so the output only consists of susceptible vs. resistant - the default is \code{TRUE}. Following the \code{guideline} argument, the output then consists of \code{"SI"} (S+SDD+I) vs. \code{"R"} with EUCAST, and of \code{"S"} (S+SDD) vs. \code{"IR"} (I+R) with CLSI.}
 }
 \value{
 A \link{double} or, when \code{as_percent = TRUE}, a \link{character}.

man/translate.Rd

@@ -41,15 +41,17 @@ And then save the file.
 Please read about adding or updating a language in \href{https://github.com/msberends/AMR/wiki/}{our Wiki}.
 \subsection{Changing the Default Language}{
 
-The system language will be used at default (as returned by \code{Sys.getenv("LANG")} or, if \code{LANG} is not set, \code{\link[=Sys.getlocale]{Sys.getlocale("LC_COLLATE")}}), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:
+The system language will be used at default, if that language is supported. The language to be used is determined in this order:
 \enumerate{
-\item Setting the package option \code{\link[=AMR-options]{AMR_locale}}, either by using e.g. \code{set_AMR_locale("German")} or by running e.g. \code{options(AMR_locale = "German")}.
+\item The package option \code{\link[=AMR-options]{AMR_locale}}, set by using e.g. \code{set_AMR_locale("German")} or by running e.g. \code{options(AMR_locale = "German")}.
 
 Note that setting an \R option only works in the same session. Save the command \code{options(AMR_locale = "(your language)")} to your \code{.Rprofile} file to apply it for every session. Run \code{utils::file.edit("~/.Rprofile")} to edit your \code{.Rprofile} file.
-\item Setting the system variable \code{LANGUAGE} or \code{LANG}, e.g. by adding \code{LANGUAGE="de_DE.utf8"} to your \code{.Renviron} file in your home directory.
+\item The system variable \code{LANG}, as returned by \code{Sys.getenv("LANG")}, e.g. set by adding \code{LANG="de_DE.utf8"} to your \code{.Renviron} file in your home directory.
+\item The system variable \code{LANGUAGE}, but only if \code{LANG} is not set. Note that \code{LANG} is set on most Linux and macOS systems, in which case \code{LANGUAGE} has no effect.
+\item The system locale, as returned by \code{\link[=Sys.getlocale]{Sys.getlocale("LC_COLLATE")}}, if neither \code{LANG} nor \code{LANGUAGE} is set.
 }
 
-Thus, if the package option \code{\link[=AMR-options]{AMR_locale}} is set, the system variables \code{LANGUAGE} and \code{LANG} will be ignored.
+Thus, if the package option \code{\link[=AMR-options]{AMR_locale}} is set, the system variables \code{LANG} and \code{LANGUAGE} will be ignored.
 }
 }
 \examples{

tests/testthat/test-count.R

@@ -89,14 +89,28 @@ test_that("test-count.R", {
       c(946, 428, 94)
     )
 
-    # count_df, which always combines S and I, as with EUCAST
+    # count_df, which combines 'I' with S for EUCAST and with R for CLSI
     expect_equal(
-      example_isolates %>% select(AMX) %>% count_df() %>% pull(value),
+      example_isolates %>% select(AMX) %>% count_df(guideline = "EUCAST") %>% pull(value),
       c(
         example_isolates$AMX %>% count_susceptible(guideline = "EUCAST"),
         example_isolates$AMX %>% count_resistant(guideline = "EUCAST")
       )
     )
+    expect_equal(
+      example_isolates %>% select(AMX) %>% count_df(guideline = "CLSI") %>% pull(value),
+      c(
+        example_isolates$AMX %>% count_susceptible(guideline = "CLSI"),
+        example_isolates$AMX %>% count_resistant(guideline = "CLSI")
+      )
+    )
+    expect_identical(
+      levels(count_df(example_isolates[, "AMX"], guideline = "CLSI")$interpretation),
+      c("S", "IR")
+    )
+    old_opts <- options(AMR_guideline = "CLSI")
+    expect_identical(count_df(example_isolates[, "AMX"]), count_df(example_isolates[, "AMX"], guideline = "CLSI"))
+    options(old_opts)
     expect_equal(
       example_isolates %>% select(AMX) %>% count_df(combine_SI = FALSE) %>% pull(value),
       c(

tests/testthat/test-ggplot_sir.R

@@ -96,6 +96,12 @@ test_that("test-ggplot_sir.R", {
         as.double()
     )
 
+    # the 'I' category is merged with R for CLSI
+    expect_identical(
+      levels(ggplot_sir(example_isolates[, c("AMC", "CIP")], guideline = "CLSI")$layers[[1]]$data(example_isolates[, c("AMC", "CIP")])$interpretation),
+      c("S", "IR")
+    )
+
     # support for scale_type ab and mo
     expect_inherits(
       (data.frame(

tests/testthat/test-proportion.R

@@ -99,14 +99,28 @@ test_that("test-proportion.R", {
       c(1181, 577, 116)
     )
 
-    # proportion_df
+    # proportion_df, which combines 'I' with S for EUCAST and with R for CLSI
     expect_equal(
-      example_isolates %>% select(AMX) %>% proportion_df() %>% pull(value),
+      example_isolates %>% select(AMX) %>% proportion_df(guideline = "EUCAST") %>% pull(value),
       c(
         example_isolates$AMX %>% proportion_SI(),
         example_isolates$AMX %>% proportion_R()
       )
     )
+    expect_equal(
+      example_isolates %>% select(AMX) %>% proportion_df(guideline = "CLSI") %>% pull(value),
+      c(
+        example_isolates$AMX %>% proportion_S(),
+        example_isolates$AMX %>% proportion_IR()
+      )
+    )
+    expect_equal(
+      example_isolates %>% select(AMX) %>% sir_df(guideline = "CLSI") %>% pull(isolates),
+      c(
+        example_isolates$AMX %>% count_S(),
+        example_isolates$AMX %>% count_IR()
+      )
+    )
     expect_equal(
       example_isolates %>% select(AMX) %>% proportion_df(combine_SI = FALSE) %>% pull(value),
       c(