fix add_missing

R/aa_options.R

@@ -35,7 +35,7 @@
 #' `options(AMR_guideline = "CLSI")`
 #' @section Options (alphabetical order):
 #' * `AMR_antibiogram_formatting_type` \cr A [numeric] (1-22) to use in [antibiogram()], to indicate which formatting type to use.
-#' * `AMR_breakpoint_type` \cr A [character] to use in [as.sir()], to indicate which breakpoint type to use. This must be either `r vector_or(clinical_breakpoints$type)`.
+#' * `AMR_breakpoint_type` \cr A [character] to use in [as.sir()], to indicate which breakpoint type to use. This must be either `r vector_or(clinical_breakpoints$type, documentation = TRUE)`.
 #' * `AMR_capped_mic_handling` \cr A [character] to use in [as.sir()], to indicate how capped MIC values (`<`, `<=`, `>`, `>=`) should be interpreted. Must be one of `"none"`, `"conservative"`, `"standard"`, or `"lenient"` - the default is `"conservative"`.
 #' * `AMR_cleaning_regex` \cr A [regular expression][base::regex] (case-insensitive) to use in [as.mo()] and all [`mo_*`][mo_property()] functions, to clean the user input. The default is the outcome of [mo_cleaning_regex()], which removes texts between brackets and texts such as "species" and "serovar".
 #' * `AMR_custom_ab` \cr A file location to an RDS file, to use custom antimicrobial drugs with this package. This is explained in [add_custom_antimicrobials()].

R/ab_property.R

@@ -32,7 +32,7 @@
 #' Use these functions to return a specific property of an antibiotic from the [antimicrobials] data set. All input values will be evaluated internally with [as.ab()].
 #' @param x Any (vector of) text that can be coerced to a valid antibiotic drug code with [as.ab()].
 #' @param tolower A [logical] to indicate whether the first [character] of every output should be transformed to a lower case [character]. This will lead to e.g. "polymyxin B" and not "polymyxin b".
-#' @param property One of the column names of one of the [antimicrobials] data set: `vector_or(colnames(antimicrobials), sort = FALSE)`.
+#' @param property One of the column names of one of the [antimicrobials] data set: `r vector_or(colnames(antimicrobials), documentation = TRUE, sort = FALSE)`.
 #' @param language Language of the returned text - the default is the current system language (see [get_AMR_locale()]) and can also be set with the package option [`AMR_locale`][AMR-options]. Use `language = NULL` or `language = ""` to prevent translation.
 #' @param administration Way of administration, either `"oral"` or `"iv"`.
 #' @param open Browse the URL using [utils::browseURL()].

R/antibiogram.R

@@ -48,8 +48,8 @@
 #'     - `carbapenems() + "GEN"`
 #'     - `carbapenems() + c("", "GEN")`
 #'     - `carbapenems() + c("", aminoglycosides())`
-#' @param mo_transform A character to transform microorganism input - must be `"name"`, `"shortname"` (default), `"gramstain"`, or one of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, quotes = TRUE)`. Can also be `NULL` to not transform the input or `NA` to consider all microorganisms 'unknown'.
-#' @param ab_transform A character to transform antimicrobial input - must be one of the column names of the [antimicrobials] data set (defaults to `"name"`): `r vector_or(colnames(antimicrobials), sort = FALSE, quotes = TRUE)`. Can also be `NULL` to not transform the input.
+#' @param mo_transform A character to transform microorganism input - must be `"name"`, `"shortname"` (default), `"gramstain"`, or one of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, documentation = TRUE)`. Can also be `NULL` to not transform the input or `NA` to consider all microorganisms 'unknown'.
+#' @param ab_transform A character to transform antimicrobial input - must be one of the column names of the [antimicrobials] data set (defaults to `"name"`): `r vector_or(colnames(antimicrobials), sort = FALSE, documentation = TRUE)`. Can also be `NULL` to not transform the input.
 #' @param 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*.
 #' @param add_total_n *(deprecated in favour of `formatting_type`)* A [logical] to indicate whether `n_tested` available numbers per pathogen should be added to the table (default is `TRUE`). This will add the lowest and highest number of available isolates per antimicrobial (e.g, if for *E. coli* 200 isolates are available for ciprofloxacin and 150 for amoxicillin, the returned number will be "150-200"). This option is unavailable when `wisca = TRUE`; in that case, use [retrieve_wisca_parameters()] to get the parameters used for WISCA.
 #' @param only_all_tested (for combination antibiograms): a [logical] to indicate that isolates must be tested for all antimicrobials, see *Details*.

R/av_property.R

@@ -32,7 +32,7 @@
 #' Use these functions to return a specific property of an antiviral drug from the [antivirals] data set. All input values will be evaluated internally with [as.av()].
 #' @param x Any (vector of) text that can be coerced to a valid antiviral drug code with [as.av()].
 #' @param tolower A [logical] to indicate whether the first [character] of every output should be transformed to a lower case [character].
-#' @param property One of the column names of one of the [antivirals] data set: `vector_or(colnames(antivirals), sort = FALSE)`.
+#' @param property One of the column names of one of the [antivirals] data set: `r vector_or(colnames(antivirals), documentation = TRUE, sort = FALSE)`.
 #' @param language Language of the returned text - the default is system language (see [get_AMR_locale()]) and can also be set with the package option [`AMR_locale`][AMR-options]. Use `language = NULL` or `language = ""` to prevent translation.
 #' @param administration Way of administration, either `"oral"` or `"iv"`.
 #' @param open Browse the URL using [utils::browseURL()].

R/data.R

@@ -307,7 +307,7 @@
 #' - `is_SDD`\cr A [logical] value (`TRUE`/`FALSE`) to indicate whether the intermediate range between "S" and "R" should be interpreted as "SDD", instead of "I". This currently applies to `r sum(clinical_breakpoints$is_SDD)` breakpoints.
 #' @details
 #' ### Different Types of Breakpoints
-#' Supported types of breakpoints are `r vector_and(clinical_breakpoints$type, quote = FALSE)`. ECOFF (Epidemiological cut-off) values are used in antimicrobial susceptibility testing to differentiate between wild-type and non-wild-type strains of bacteria or fungi.
+#' Supported types of breakpoints are `r vector_and(clinical_breakpoints$type, quotes = FALSE)`. ECOFF (Epidemiological cut-off) values are used in antimicrobial susceptibility testing to differentiate between wild-type and non-wild-type strains of bacteria or fungi.
 #'
 #' The default is `"human"`, which can also be set with the package option [`AMR_breakpoint_type`][AMR-options]. Use [`as.sir(..., breakpoint_type = ...)`][as.sir()] to interpret raw data using a specific breakpoint type, e.g. `as.sir(..., breakpoint_type = "ECOFF")` to use ECOFFs.
 #'

R/interpretive_rules.R

@@ -65,12 +65,12 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
 #' @param rules A [character] vector that specifies which rules should be applied. Must be one or more of `"breakpoints"`, `"expected_phenotypes"`, `"expert"`, `"other"`, `"custom"`, `"all"`, and defaults to `c("breakpoints", "expected_phenotypes")`. The default value can be set to another value using the package option [`AMR_interpretive_rules`][AMR-options]: `options(AMR_interpretive_rules = "all")`. If using `"custom"`, be sure to fill in argument `custom_rules` too. Custom rules can be created with [custom_eucast_rules()].
 #' @param verbose A [logical] to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time.
 #' @param version_breakpoints The version number to use for the EUCAST Clinical Breakpoints guideline. Can be `r vector_or(names(EUCAST_VERSION_BREAKPOINTS), documentation = TRUE, reverse = TRUE)`.
-#' @param version_expected_phenotypes The version number to use for the EUCAST Expected Phenotypes. Can be `r vector_or(names(EUCAST_VERSION_EXPECTED_PHENOTYPES), reverse = TRUE)`.
-#' @param version_expertrules The version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be `r vector_or(names(EUCAST_VERSION_EXPERT_RULES), reverse = TRUE)`.
+#' @param version_expected_phenotypes The version number to use for the EUCAST Expected Phenotypes. Can be `r vector_or(names(EUCAST_VERSION_EXPECTED_PHENOTYPES), documentation = TRUE, reverse = TRUE)`.
+#' @param version_expertrules The version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be `r vector_or(names(EUCAST_VERSION_EXPERT_RULES), documentation = TRUE, reverse = TRUE)`.
 #' @param ampc_cephalosporin_resistance (only applies when `rules` contains `"expert"` or `"all"`) a [character] value that should be applied to cefotaxime, ceftriaxone and ceftazidime for AmpC de-repressed cephalosporin-resistant mutants - the default is `NA`. Currently only works when `version_expertrules` is `3.2` and higher; these versions of '*EUCAST Expert Rules on Enterobacterales*' state that results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these three drugs. A value of `NA` (the default) for this argument will remove results for these three drugs, while e.g. a value of `"R"` will make the results for these drugs resistant. Use `NULL` or `FALSE` to not alter results for these three drugs of AmpC de-repressed cephalosporin-resistant mutants. Using `TRUE` is equal to using `"R"`. \cr For *EUCAST Expert Rules* v3.2, this rule applies to: `r vector_and(gsub("[^a-zA-Z ]+", "", unlist(strsplit(EUCAST_RULES_DF[which(EUCAST_RULES_DF$reference.version %in% c(3.2, 3.3) & EUCAST_RULES_DF$reference.rule %like% "ampc"), "this_value"][1], "|", fixed = TRUE))), quotes = "*")`.
 #' @param ... Column names of antimicrobials. To automatically detect antimicrobial column names, do not provide any named arguments; [guess_ab_col()] will then be used for detection. To manually specify a column, provide its name (case-insensitive) as an argument, e.g. `AMX = "amoxicillin"`. To skip a specific antimicrobial, set it to `NULL`, e.g. `TIC = NULL` to exclude ticarcillin. If a manually defined column does not exist in the data, it will be skipped with a warning.
 #' @param ab Any (vector of) text that can be coerced to a valid antimicrobial drug code with [as.ab()].
-#' @param administration Route of administration, either `r vector_or(dosage$administration)`.
+#' @param administration Route of administration, either `r vector_or(dosage$administration, documentation = TRUE)`.
 #' @param only_sir_columns A [logical] to indicate whether only antimicrobial columns must be included that were transformed to class [sir][as.sir()] on beforehand. Defaults to `FALSE` if no columns of `x` have a class [sir][as.sir()].
 #' @param custom_rules Custom rules to apply, created with [custom_eucast_rules()].
 #' @param overwrite A [logical] indicating whether to overwrite existing SIR values (default: `FALSE`). When `FALSE`, only non-SIR values are modified (i.e., any value that is not already S, I or R). To ensure compliance with EUCAST guidelines, **this should remain** `FALSE`, as EUCAST notes often state that an organism "should be tested for susceptibility to individual agents or be reported resistant".
@@ -619,7 +619,7 @@ interpretive_rules <- function(x,
   # >>> Apply Official EUCAST rules <<< ---------------------------------------------------
   eucast_notification_shown <- FALSE
   if (!is.null(list(...)$eucast_rules_df)) {
-    # this allows: eucast_rules(x, eucast_rules_df = AMR:::EUCAST_RULES_DF %>% filter(is.na(have_these_values)))
+    # this allows: eucast_rules(x, eucast_rules_df = AMR:::EUCAST_RULES_DF |> filter(is.na(have_these_values)))
     eucast_rules_df_total <- list(...)$eucast_rules_df
   } else {
     # otherwise internal data file, created in data-raw/_pre_commit_checks.R
@@ -1075,13 +1075,13 @@ interpretive_rules <- function(x,
     warn_lacking_sir_class <- warn_lacking_sir_class[order(colnames(x.bak))]
     warn_lacking_sir_class <- warn_lacking_sir_class[!is.na(warn_lacking_sir_class)]
     warning_(
-      "in {.help [{.fun eucast_rules}](AMR::eucast_rules)}: not all columns with antimicrobial results are of class {.cls sir}. Transform them on beforehand, e.g.:\n",
-      "  - ", highlight_code(paste0(x_deparsed, " %>% as.sir(", ifelse(length(warn_lacking_sir_class) == 1,
+      "in {.help [{.fun eucast_rules}](AMR::eucast_rules)}: not all columns with antimicrobial results are of class {.cls sir}. Transform them on beforehand, e.g.:\n\n",
+      "\u00a0\u00a0", AMR_env$bullet_icon, " ", highlight_code(paste0(x_deparsed, " |> as.sir(", ifelse(length(warn_lacking_sir_class) == 1,
         warn_lacking_sir_class,
         paste0(warn_lacking_sir_class[1], ":", warn_lacking_sir_class[length(warn_lacking_sir_class)])
-      ), ")")), "\n",
-      "  - ", highlight_code(paste0(x_deparsed, " %>% mutate_if(is_sir_eligible, as.sir)")), "\n",
-      "  - ", highlight_code(paste0(x_deparsed, " %>% mutate(across(where(is_sir_eligible), as.sir))"))
+      ), ")")), "\n\n",
+      "\u00a0\u00a0", AMR_env$bullet_icon, " ", highlight_code(paste0(x_deparsed, " |> mutate_if(is_sir_eligible, as.sir)")), "\n\n",
+      "\u00a0\u00a0", AMR_env$bullet_icon, " ", highlight_code(paste0(x_deparsed, " |> mutate(across(where(is_sir_eligible), as.sir))"))
     )
   }
 
@@ -1165,18 +1165,31 @@ edit_sir <- function(x,
       track_changes$sir_warn <- cols[!vapply(FUN.VALUE = logical(1), x[, cols, drop = FALSE], is.sir)]
     }
     isNA <- is.na(new_edits[rows, cols])
-    isSIR <- !isNA & (new_edits[rows, cols] == "S" | new_edits[rows, cols] == "I" | new_edits[rows, cols] == "R" | new_edits[rows, cols] == "SDD" | new_edits[rows, cols] == "NI" | new_edits[rows, cols] == "WT" | new_edits[rows, cols] == "NWT" | new_edits[rows, cols] == "NS")
+    isSIR <- !isNA &
+      (new_edits[rows, cols] == "S" |
+        new_edits[rows, cols] == "I" |
+        new_edits[rows, cols] == "R" |
+        new_edits[rows, cols] == "SDD" |
+        new_edits[rows, cols] == "NI" |
+        new_edits[rows, cols] == "WT" |
+        new_edits[rows, cols] == "NWT" |
+        new_edits[rows, cols] == "NS")
     non_SIR <- !isSIR
     if (isFALSE(overwrite) && any(isSIR) && message_not_thrown_before("edit_sir.warning_overwrite")) {
-      warning_("Some values had SIR values and were not overwritten, since {.code overwrite = FALSE}.")
+      warning_("in {.help [{.fun eucast_rules}](AMR::eucast_rules)}: some columns had SIR values which were not overwritten, since {.code overwrite = FALSE}.")
     }
     # determine which cells to modify based on overwrite and add_if_missing
-    apply_mask <- if (isTRUE(overwrite)) {
-      if (isFALSE(add_if_missing)) !isNA else rep(TRUE, length(isNA))
+    if (isTRUE(overwrite)) {
+      if (isTRUE(add_if_missing)) {
+        apply_mask <- rep(TRUE, length(isSIR))
+      } else {
+        apply_mask <- isSIR
+      }
     } else {
-      if (isFALSE(add_if_missing)) isSIR else non_SIR
+      # overwrite = FALSE, add_if_missing = TRUE: fill missing and placeholder cells only
+      apply_mask <- !isSIR
     }
-warning_("test", call = T) # aaaaaaa
+
     tryCatch(
       # insert into original table
       new_edits[rows, cols][apply_mask] <- to,

R/mo.R

@@ -792,7 +792,7 @@ print.mo <- function(x, print.shortnames = FALSE, ...) {
   names(x) <- x_names
   if (!all(x %in% c(AMR_env$MO_lookup$mo, NA))) {
     warning_(
-      "Some MO codes are from a previous AMR package version. ",
+      "Some MO codes are from another AMR package version. ",
       "Please update the MO codes with {.help [{.fun as.mo}](AMR::as.mo)}.",
       call = FALSE
     )
@@ -826,7 +826,7 @@ as.data.frame.mo <- function(x, ...) {
   add_MO_lookup_to_AMR_env()
   if (!all(x %in% c(AMR_env$MO_lookup$mo, NA))) {
     warning_(
-      "The data contains old MO codes (from a previous AMR package version). ",
+      "The data contains old MO codes (from another AMR package version). ",
       "Please update your MO codes with {.help [{.fun as.mo}](AMR::as.mo)}."
     )
   }

R/mo_property.R

@@ -31,7 +31,7 @@
 #'
 #' 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 [as.mo()], which makes it possible to use microbial abbreviations, codes and names as input. See *Examples*.
 #' @param x Any [character] (vector) that can be coerced to a valid microorganism code with [as.mo()]. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, see *Examples*.
-#' @param property One of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, quotes = TRUE)`, or must be `"shortname"`.
+#' @param property One of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, documentation = TRUE)`, or must be `"shortname"`.
 #' @inheritParams as.mo
 #' @param ... Other arguments passed on to [as.mo()], such as 'minimum_matching_score', 'ignore_pattern', and 'remove_from_input'.
 #' @param ab Any (vector of) text that can be coerced to a valid antibiotic drug code with [as.ab()].

R/pca.R

@@ -66,12 +66,12 @@
 #'
 #' # new ggplot2 plotting method using this package:
 #' if (require("dplyr") && require("ggplot2")) {
-#'     ggplot_pca(pca_result)
+#'   ggplot_pca(pca_result)
 #' }
 #' if (require("dplyr") && require("ggplot2")) {
-#'     ggplot_pca(pca_result) +
-#'       scale_colour_viridis_d() +
-#'       labs(title = "Title here")
+#'   ggplot_pca(pca_result) +
+#'     scale_colour_viridis_d() +
+#'     labs(title = "Title here")
 #' }
 #' }
 pca <- function(x,

R/plotting.R

@@ -200,7 +200,7 @@
 #'     theme_minimal() +
 #'     geom_boxplot(fill = NA, colour = "grey30") +
 #'     geom_jitter(width = 0.25)
-#'     labs(title = "scale_y_mic()/scale_colour_sir() automatically applied")
+#'   labs(title = "scale_y_mic()/scale_colour_sir() automatically applied")
 #'
 #'   mic_sir_plot
 #' }

R/sir.R

@@ -65,7 +65,7 @@ VALID_SIR_LEVELS <- c("S", "SDD", "I", "R", "NI", "WT", "NWT", "NS")
 #' @param substitute_missing_r_breakpoint A [logical] to indicate that a missing clinical breakpoints for R (resistant) must be substituted with R - the default is `FALSE`. Some (especially CLSI) breakpoints only have a breakpoint for S, meaning that the outcome can only be `"S"` or `NA`. Setting this to `TRUE` will convert the `NA`s in these cases to `"R"`. Can also be set with the package option [`AMR_substitute_missing_r_breakpoint`][AMR-options].
 #' @param include_screening A [logical] to indicate that clinical breakpoints for screening are allowed - the default is `FALSE`. Can also be set with the package option [`AMR_include_screening`][AMR-options].
 #' @param include_PKPD A [logical] to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is `TRUE`. Can also be set with the package option [`AMR_include_PKPD`][AMR-options].
-#' @param breakpoint_type The type of breakpoints to use, either `r vector_or(clinical_breakpoints$type)`. ECOFF stands for Epidemiological Cut-Off values. The default is `"human"`, which can also be set with the package option [`AMR_breakpoint_type`][AMR-options]. If `host` is set to values of veterinary species, this will automatically be set to `"animal"`.
+#' @param breakpoint_type The type of breakpoints to use, either `r vector_or(clinical_breakpoints$type, documentation = TRUE)`. ECOFF stands for Epidemiological Cut-Off values. The default is `"human"`, which can also be set with the package option [`AMR_breakpoint_type`][AMR-options]. If `host` is set to values of veterinary species, this will automatically be set to `"animal"`.
 #' @param host A vector (or column name) with [character]s to indicate the host. Only useful for veterinary breakpoints, as it requires `breakpoint_type = "animal"`. The values can be any text resembling the animal species, even in any of the `r length(LANGUAGES_SUPPORTED)` supported languages of this package. For foreign languages, be sure to set the language with [set_AMR_locale()] (though it will be automatically guessed based on the system language).
 #' @param language Language to convert values set in `host` when using animal breakpoints. Use one of these supported language names or [ISO 639-1 codes](https://en.wikipedia.org/wiki/ISO_639-1): `r vector_or(paste0(sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), " (" , LANGUAGES_SUPPORTED, ")"), quotes = FALSE, sort = FALSE)`.
 #' @param verbose A [logical] to indicate that all notes should be printed during interpretation of MIC values or disk diffusion values.

R/tidymodels.R

@@ -21,7 +21,6 @@
 #' @export
 #' @examples
 #' if (require("tidymodels")) {
-#'
 #'   # The below approach formed the basis for this paper: DOI 10.3389/fmicb.2025.1582703
 #'   # Presence of ESBL genes was predicted based on raw MIC values.
 #'
@@ -40,13 +39,10 @@
 #'
 #'   # Create and prep a recipe with MIC log2 transformation
 #'   mic_recipe <- recipe(esbl ~ ., data = training_data) %>%
-#'
 #'     # Optionally remove non-predictive variables
 #'     remove_role(genus, old_role = "predictor") %>%
-#'
 #'     # Apply the log2 transformation to all MIC predictors
 #'     step_mic_log2(all_mic_predictors()) %>%
-#'
 #'     # And apply the preparation steps
 #'     prep()
 #'
@@ -67,13 +63,15 @@
 #'     bind_cols(out_testing)
 #'
 #'   # Evaluate predictions using standard classification metrics
-#'   our_metrics <- metric_set(accuracy,
-#'                             recall,
-#'                             precision,
-#'                             sensitivity,
-#'                             specificity,
-#'                             ppv,
-#'                             npv)
+#'   our_metrics <- metric_set(
+#'     accuracy,
+#'     recall,
+#'     precision,
+#'     sensitivity,
+#'     specificity,
+#'     ppv,
+#'     npv
+#'   )
 #'   metrics <- our_metrics(predictions, truth = esbl, estimate = .pred_class)
 #'
 #'   # Show performance

R/top_n_microorganisms.R

@@ -32,7 +32,7 @@
 #' This function filters a data set to include only the top *n* microorganisms based on a specified property, such as taxonomic family or genus. For example, it can filter a data set to the top 3 species, or to any species in the top 5 genera, or to the top 3 species in each of the top 5 genera.
 #' @param x A data frame containing microbial data.
 #' @param n An integer specifying the maximum number of unique values of the `property` to include in the output.
-#' @param property A character string indicating the microorganism property to use for filtering. Must be one of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, quotes = TRUE)`. If `NULL`, the raw values from `col_mo` will be used without transformation. When using `"species"` (default) or `"subpecies"`, the genus will be added to make sure each (sub)species still belongs to the right genus.
+#' @param property A character string indicating the microorganism property to use for filtering. Must be one of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, documentation = TRUE)`. If `NULL`, the raw values from `col_mo` will be used without transformation. When using `"species"` (default) or `"subpecies"`, the genus will be added to make sure each (sub)species still belongs to the right genus.
 #' @param n_for_each An optional integer specifying the maximum number of rows to retain for each value of the selected property. If `NULL`, all rows within the top *n* groups will be included.
 #' @param col_mo A character string indicating the column in `x` that contains microorganism names or codes. Defaults to the first column of class [`mo`]. Values will be coerced using [as.mo()].
 #' @param ... Additional arguments passed on to [mo_property()] when `property` is not `NULL`.