(v1.2.0.9008) ab_class improvement

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: AMR
-Version: 1.2.0.9007
+Version: 1.2.0.9008
 Date: 2020-06-17
 Title: Antimicrobial Resistance Analysis
 Authors@R: c(

NAMESPACE

@@ -64,6 +64,7 @@ export(ab_atc)
 export(ab_atc_group1)
 export(ab_atc_group2)
 export(ab_cid)
+export(ab_class)
 export(ab_ddd)
 export(ab_group)
 export(ab_info)

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 1.2.0.9007
+# AMR 1.2.0.9008
 ## <small>Last updated: 17-Jun-2020</small>
 
 ### New
@@ -13,17 +13,23 @@
   tibble(J01CA01 = "S") %>%
     select(penicillins())
   #> Selecting beta-lactams/penicillins: `J01CA01` (ampicillin)
+  
+  # select an antibiotic class manually with `ab_class()`
+  example_isolates %>% 
+    select(ab_class("mycobact"))
+  #> Selecting antimycobacterials: `RIF` (rifampicin)
   ```
 
 ### Changed
 * Fixed a bug where `eucast_rules()` would not work on a tibble when the `tibble` or `dplyr` package was loaded
-* All `*_join_microorganisms()` functions now return the original data class (e.g. tibbles and data.tables)
+* All `*_join_microorganisms()` functions and `bug_drug_combinations()` now return the original data class (e.g. `tibble`s and `data.table`s)
 * Fixed a bug where `as.ab()` would return an error on invalid input values
 * Fixed a bug for using grouped versions of `rsi_df()`, `proportion_df()` and `count_df()`, and fixed a bug where not all different antimicrobial results were added as rows
 * Added function `filter_penicillins()` to filter isolates on a specific result in any column with a name in the antimicrobial 'penicillins' class (more specific: ATC subgroup *Beta-lactam antibacterials, penicillins*)
 * Added official antimicrobial names to all `filter_ab_class()` functions, such as `filter_aminoglycosides()`
 * Added antibiotics code "FOX1" for cefoxitin screening (abbreviation "cfsc") to the `antibiotics` data set
 * Improved auto-determination for columns of types `<mo>` and `<Date>`
+* Fixed a bug in `bug_drug_combinations()` for when only one antibiotic was in the input data
 
 # AMR 1.2.0
 

R/aa_helper_functions.R

@@ -63,14 +63,12 @@ filter_join_worker <- function(x, y, by = NULL, type = c("anti", "semi")) {
 
 # No export, no Rd
 addin_insert_in <- function() {
-  stopifnot_installed_package("rstudioapi")
+  import_fn("insertText", "rstudioapi")(" %in% ")
-  get("insertText", envir = asNamespace("rstudioapi"))(" %in% ")
 }
 
 # No export, no Rd
 addin_insert_like <- function() {
-  stopifnot_installed_package("rstudioapi")
+  import_fn("insertText", "rstudioapi")(" %like% ")
-  get("insertText", envir = asNamespace("rstudioapi"))(" %like% ")
 }
 
 check_dataset_integrity <- function() {
@@ -186,12 +184,23 @@ stopifnot_installed_package <- function(package) {
   # https://developer.r-project.org/Blog/public/2019/02/14/staged-install/index.html
   sapply(package, function(x)
     tryCatch(get(".packageName", envir = asNamespace(x)),
-             error = function(e) stop("package '", x, "' required but not installed.",
+             error = function(e) { 
+               if (package == "rstudioapi") {
+                 stop("This function only works in RStudio.", call. = FALSE)
+               } else {
+                 stop("package '", x, "' required but not installed.",
                       "\nTry to install it with: install.packages(\"", x, "\")",
-                                      call. = FALSE)))
+                      call. = FALSE)
+               }
+             }))
   return(invisible())
 }
 
+import_fn <- function(name, pkg) {
+  stopifnot_installed_package(pkg)
+  get(name, envir = asNamespace(pkg))
+}
+
 stopifnot_msg <- function(expr, msg) {
   if (!isTRUE(expr)) {
     stop(msg, call. = FALSE)

R/ab_class_selectors.R

@@ -22,6 +22,7 @@
 #' Antibiotic class selectors
 #' 
 #' Use these selection helpers inside any function that allows [Tidyverse selections](https://tidyselect.r-lib.org/reference/language.html), like `dplyr::select()` or `tidyr::pivot_longer()`. They help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
+#' @inheritParams filter_ab_class 
 #' @details All columns will be searched for known antibiotic names, abbreviations, brand names and codes (ATC, EARS-Net, WHO, etc.). This means that a selector like e.g. [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
 #' 
 #' These functions only work if the `tidyselect` package is installed, that comes with the `dplyr` package. An error will be thrown if `tidyselect` package is not installed, or if the functions are used outside a function that allows Tidyverse selections like `select()` or `pivot_longer()`.
@@ -36,99 +37,113 @@
 #'   example_isolates %>% 
 #'     select(carbapenems())
 #'     
-#'     
 #'   # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
 #'   example_isolates %>% 
 #'     select(mo, aminoglycosides())
 #'     
+#'   # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
+#'   example_isolates %>% 
+#'     select(mo, ab_class("mycobact"))
+#'     
+#'     
+#'   # get bug/drug combinations for only macrolides in Gram-positives:
+#'   example_isolates %>% 
+#'     filter(mo_gramstain(mo) %like% "pos") %>% 
+#'     select(mo, macrolides()) %>% 
+#'     bug_drug_combinations() %>%
+#'     format()
+#'     
 #'     
 #'   data.frame(irrelevant = "value",
 #'              J01CA01 = "S") %>%   # ATC code of ampicillin
 #'     select(penicillins())         # so the 'J01CA01' column is selected
 #'
 #' }
+ab_class <- function(ab_class) {
+  ab_selector(ab_class, function_name = "ab_class")
+}
+
+#' @rdname antibiotic_class_selectors
+#' @export
 aminoglycosides <- function() {
-  ab_selector("aminoglycoside")
+  ab_selector("aminoglycoside", function_name = "aminoglycosides")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 carbapenems <- function() {
-  ab_selector("carbapenem")
+  ab_selector("carbapenem", function_name = "carbapenems")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 cephalosporins <- function() {
-  ab_selector("cephalosporin")
+  ab_selector("cephalosporin", function_name = "cephalosporins")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 cephalosporins_1st <- function() {
-  ab_selector("cephalosporins.*1")
+  ab_selector("cephalosporins.*1", function_name = "cephalosporins_1st")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 cephalosporins_2nd <- function() {
-  ab_selector("cephalosporins.*2")
+  ab_selector("cephalosporins.*2", function_name = "cephalosporins_2nd")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 cephalosporins_3rd <- function() {
-  ab_selector("cephalosporins.*3")
+  ab_selector("cephalosporins.*3", function_name = "cephalosporins_3rd")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 cephalosporins_4th <- function() {
-  ab_selector("cephalosporins.*4")
+  ab_selector("cephalosporins.*4", function_name = "cephalosporins_4th")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 cephalosporins_5th <- function() {
-  ab_selector("cephalosporins.*5")
+  ab_selector("cephalosporins.*5", function_name = "cephalosporins_5th")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 fluoroquinolones <- function() {
-  ab_selector("fluoroquinolone")
+  ab_selector("fluoroquinolone", function_name = "fluoroquinolones")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 glycopeptides <- function() {
-  ab_selector("glycopeptide")
+  ab_selector("glycopeptide", function_name = "glycopeptides")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 macrolides <- function() {
-  ab_selector("macrolide")
+  ab_selector("macrolide", function_name = "macrolides")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 penicillins <- function() {
-  ab_selector("penicillin")
+  ab_selector("penicillin", function_name = "penicillins")
 }
 
 #' @rdname antibiotic_class_selectors
 #' @export
 tetracyclines <- function() {
-  ab_selector("tetracycline")
+  ab_selector("tetracycline", function_name = "tetracyclines")
 }
 
-ab_selector <- function(ab_class, vars = NULL) {
+ab_selector <- function(ab_class, function_name) {
-  
+  peek_vars_tidyselect <- import_fn("peek_vars", "tidyselect")
-  stopifnot_installed_package("tidyselect")
+  vars_vct <- peek_vars_tidyselect(fn = function_name)
-  peek_vars_tidyselect <- get("peek_vars", envir = asNamespace("tidyselect"))
-  
-  vars_vct <- peek_vars_tidyselect(fn = ab_class)
   vars_df <- data.frame(as.list(vars_vct))[0, , drop = FALSE]
   colnames(vars_df) <- vars_vct
   ab_in_data <- suppressMessages(get_column_abx(vars_df))
@@ -143,12 +158,17 @@ ab_selector <- function(ab_class, vars = NULL) {
                            atc_group1 %like% ab_class | 
                            atc_group2 %like% ab_class)
   ab_group <- find_ab_group(ab_class)
+  if (ab_group == "") {
+    ab_group <- paste0("'", ab_class, "'")
+    examples <- ""
+  } else {
+    examples <- paste0(" (such as ", find_ab_names(ab_class, 2), ")")
+  }
   # get the columns with a group names in the chosen ab class
   agents <- ab_in_data[names(ab_in_data) %in% ab_reference$ab]
   if (length(agents) == 0) {
-    message(font_blue(paste0("NOTE: no antimicrobial agents of class ", ab_group, 
+    message(font_blue(paste0("NOTE: No antimicrobial agents of class ", ab_group, 
-                             " found (such as ", find_ab_names(ab_class, 2), 
+                             " found", examples, ".")))
-                             ").")))
   } else {
     message(font_blue(paste0("Selecting ", ab_group, ": ",
                              paste(paste0("`", font_bold(agents, collapse = NULL),

R/atc_online.R

@@ -76,15 +76,14 @@ atc_online_property <- function(atc_code,
                                 administration = "O",
                                 url = "https://www.whocc.no/atc_ddd_index/?code=%s&showdescription=no") {
   
-  stopifnot_installed_package(c("curl", "rvest", "xml2"))
+  has_internet <- import_fn("has_internet", "curl")
-  has_internet <- get("has_internet", envir = asNamespace("curl"))
+  html_attr <- import_fn("html_attr", "rvest")
-  html_attr <- get("html_attr", envir = asNamespace("rvest"))
+  html_children <- import_fn("html_children", "rvest")
-  html_children <- get("html_children", envir = asNamespace("rvest"))
+  html_node <- import_fn("html_node", "rvest")
-  html_node <- get("html_node", envir = asNamespace("rvest"))
+  html_nodes <- import_fn("html_nodes", "rvest")
-  html_nodes <- get("html_nodes", envir = asNamespace("rvest"))
+  html_table <- import_fn("html_table", "rvest")
-  html_table <- get("html_table", envir = asNamespace("rvest"))
+  html_text <- import_fn("html_text", "rvest")
-  html_text <- get("html_text", envir = asNamespace("rvest"))
+  read_html <- import_fn("read_html", "xml2")
-  read_html <- get("read_html", envir = asNamespace("xml2"))
 
   check_dataset_integrity()
   

R/bug_drug_combinations.R

@@ -62,6 +62,9 @@ bug_drug_combinations <- function(x,
   if (!is.data.frame(x)) {
     stop("`x` must be a data frame.", call. = FALSE)
   }
+  if (!any(sapply(x, is.rsi), na.rm = TRUE)) {
+    stop("No columns with class <rsi> found. See ?as.rsi.", call. = FALSE)
+  }
   
   # try to find columns based on type
   # -- mo
@@ -72,9 +75,10 @@ bug_drug_combinations <- function(x,
     stop("`col_mo` must be set.", call. = FALSE)
   }
   
+  x_class <- class(x)
   x <- as.data.frame(x, stringsAsFactors = FALSE)
   x[, col_mo] <- FUN(x[, col_mo, drop = TRUE])
-  x <- x[, c(col_mo, names(which(sapply(x, is.rsi))))]
+  x <- x[, c(col_mo, names(which(sapply(x, is.rsi)))), drop = FALSE]
   
   unique_mo <- sort(unique(x[, col_mo, drop = TRUE]))
 
@@ -88,7 +92,7 @@ bug_drug_combinations <- function(x,
 
   for (i in seq_len(length(unique_mo))) {
     # filter on MO group and only select R/SI columns
-    x_mo_filter <- x[which(x[, col_mo, drop = TRUE] == unique_mo[i]), names(which(sapply(x, is.rsi)))]
+    x_mo_filter <- x[which(x[, col_mo, drop = TRUE] == unique_mo[i]), names(which(sapply(x, is.rsi))), drop = FALSE]
     # turn and merge everything
     pivot <- lapply(x_mo_filter, function(x) {
       m <- as.matrix(table(x))
@@ -104,7 +108,7 @@ bug_drug_combinations <- function(x,
     out <- rbind(out, out_group)
   }
 
-  structure(.Data = out, class = c("bug_drug_combinations", class(x)))
+  structure(.Data = out, class = c("bug_drug_combinations", x_class))
 }
 
 #' @method format bug_drug_combinations
@@ -121,6 +125,7 @@ format.bug_drug_combinations <- function(x,
                                          decimal.mark = getOption("OutDec"),
                                          big.mark = ifelse(decimal.mark == ",", ".", ","),
                                          ...) {
+  x <- as.data.frame(x, stringsAsFactors = FALSE)
   x <- subset(x, total >= minimum)
   
   if (remove_intrinsic_resistant == TRUE) {
@@ -221,6 +226,8 @@ format.bug_drug_combinations <- function(x,
 #' @method print bug_drug_combinations
 #' @export
 print.bug_drug_combinations <- function(x, ...) {
-  print(as.data.frame(x, stringsAsFactors = FALSE))
+  x_class <- class(x)
-  message(font_blue("NOTE: Use 'format()' on this result to get a publicable/printable format."))
+  print(structure(x, class = x_class[x_class != "bug_drug_combinations"]),
+        ...)
+  message(font_blue("NOTE: Use 'format()' on this result to get a publishable/printable format."))
 }

R/eucast_rules.R

@@ -206,7 +206,7 @@ eucast_rules <- function(x,
                   "\n\nThis may overwrite your existing data if you use e.g.:",
                   "\ndata <- eucast_rules(data, verbose = TRUE)\n\nDo you want to continue?")
     if ("rstudioapi" %in% rownames(utils::installed.packages())) {
-      showQuestion <- get("showQuestion", envir = asNamespace("rstudioapi"))
+      showQuestion <- import_fn("showQuestion", "rstudioapi")
       q_continue <- showQuestion("Using verbose = TRUE with eucast_rules()", txt)
     } else {
       q_continue <- utils::menu(choices = c("OK", "Cancel"), graphics = FALSE, title = txt)

R/lifecycle.R

@@ -26,10 +26,10 @@
 #' Lifecycles of functions in the `AMR` package
 #' @name lifecycle
 #' @rdname lifecycle
-#' @description Functions in this `AMR` package are categorised using [the lifecycle circle of the `tidyverse` as found on www.tidyverse.org/lifecycle](https://www.tidyverse.org/lifecycle).
+#' @description Functions in this `AMR` package are categorised using [the lifecycle circle of the Tidyverse as found on www.tidyverse.org/lifecycle](https://www.Tidyverse.org/lifecycle).
 #' 
-#' \if{html}{\figure{lifecycle_tidyverse.svg}{options: height=200px style=margin-bottom:5px} \cr}
+#' \if{html}{\figure{lifecycle_Tidyverse.svg}{options: height=200px style=margin-bottom:5px} \cr}
-#' This page contains a section for every lifecycle (with text borrowed from the aforementioned `tidyverse` website), so they can be used in the manual pages of the functions. 
+#' This page contains a section for every lifecycle (with text borrowed from the aforementioned Tidyverse website), so they can be used in the manual pages of the functions. 
 #' @section Experimental lifecycle:
 #' \if{html}{\figure{lifecycle_experimental.svg}{options: style=margin-bottom:5px} \cr}
 #' The [lifecycle][AMR::lifecycle] of this function is **experimental**. An experimental function is in early stages of development. The unlying code might be changing frequently. Experimental functions might be removed without deprecation, so you are generally best off waiting until a function is more mature before you use it in production code. Experimental functions are only available in development versions of this `AMR` package and will thus not be included in releases that are submitted to CRAN, since such functions have not yet matured enough.

R/mdro.R

@@ -95,7 +95,7 @@ mdro <- function(x,
                   "\n\nThis may overwrite your existing data if you use e.g.:",
                   "\ndata <- mdro(data, verbose = TRUE)\n\nDo you want to continue?")
     if ("rstudioapi" %in% rownames(utils::installed.packages())) {
-      showQuestion <- get("showQuestion", envir = asNamespace("rstudioapi"))
+      showQuestion <- import_fn("showQuestion", "rstudioapi")
       q_continue <- showQuestion("Using verbose = TRUE with mdro()", txt)
     } else {
       q_continue <- utils::menu(choices = c("OK", "Cancel"), graphics = FALSE, title = txt)

R/mo.R

@@ -152,7 +152,7 @@
 #' \dontrun{
 #' df$mo <- as.mo(df$microorganism_name)
 #'
-#' # the select function of tidyverse is also supported:
+#' # the select function of the Tidyverse is also supported:
 #' library(dplyr)
 #' df$mo <- df %>%
 #'   select(microorganism_name) %>%
@@ -1805,13 +1805,13 @@ parse_and_convert <- function(x) {
       if (NCOL(x) > 2) {
         stop("A maximum of two columns is allowed.", call. = FALSE)
       } else if (NCOL(x) == 2) {
-        # support tidyverse selection like: df %>% select(colA, colB)
+        # support Tidyverse selection like: df %>% select(colA, colB)
         # paste these columns together
         x <- as.data.frame(x, stringsAsFactors = FALSE)
         colnames(x) <- c("A", "B")
         x <- paste(x$A, x$B)
       } else {
-        # support tidyverse selection like: df %>% select(colA)
+        # support Tidyverse selection like: df %>% select(colA)
         x <- as.data.frame(x, stringsAsFactors = FALSE)[[1]]
       }
     }

R/mo_source.R

@@ -135,8 +135,7 @@ set_mo_source <- function(path) {
 
   } else if (path %like% "[.]xlsx?$") {
     # is Excel file (old or new)
-    stopifnot_installed_package("readxl")
+    read_excel <- import_fn("read_excel", "readxl")
-    read_excel <- get("read_excel", envir = asNamespace("readxl"))
     df <- read_excel(path)
 
   } else if (path %like% "[.]tsv$") {

R/proportion.R

@@ -40,7 +40,7 @@
 #'  
 #' **Remember that you should filter your table to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set.
 #'
-#' These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the `count()`][AMR::count()] functions to count isolates. The function [susceptibility()] is essentially equal to `count_susceptible() / count_all()`. *Low counts can influence the outcome - the `proportion` functions may camouflage this, since they only return the proportion (albeit being dependent on the `minimum` parameter).*
+#' These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the [`count()`][AMR::count()] functions to count isolates. The function [susceptibility()] is essentially equal to `count_susceptible() / count_all()`. *Low counts can influence the outcome - the `proportion` functions may camouflage this, since they only return the proportion (albeit being dependent on the `minimum` parameter).*
 #'
 #' The function [proportion_df()] takes any variable from `data` that has an [`rsi`] class (created with [as.rsi()]) and calculates the proportions R, I and S. It also supports grouped variables. The function [rsi_df()] works exactly like [proportion_df()], but adds the number of isolates.
 #' @section Combination therapy:

R/resistance_predict.R

@@ -316,9 +316,9 @@ plot.resistance_predict <- function(x, main = paste("Resistance Prediction of",
   }
   # get plot() generic; this was moved from the 'graphics' pkg to the 'base' pkg in R 4.0.0
   if (as.integer(R.Version()$major) >= 4) {
-    plot <- get("plot", envir = asNamespace("base"))
+    plot <- import_fn("plot", "base")
   } else {
-    plot <- get("plot", envir = asNamespace("graphics"))
+    plot <- import_fn("plot", "graphics")
   }
   plot(x = x$year,
        y = x$value,

R/rsi.R

@@ -594,9 +594,9 @@ plot.rsi <- function(x,
   
   # get plot() generic; this was moved from the 'graphics' pkg to the 'base' pkg in R 4.0.0
   if (as.integer(R.Version()$major) >= 4) {
-    plot <- get("plot", envir = asNamespace("base"))
+    plot <- import_fn("plot", "base")
   } else {
-    plot <- get("plot", envir = asNamespace("graphics"))
+    plot <- import_fn("plot", "graphics")
   }
   plot(x = data$x,
        y = data$s,

docs/404.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="https://msberends.gitlab.io/AMR/index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 

docs/LICENSE-text.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 

docs/articles/index.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 

docs/authors.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 

docs/index.html

@@ -43,7 +43,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 

docs/news/index.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 
@@ -229,9 +229,9 @@
       <small>Source: <a href='https://gitlab.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
     </div>
 
-    <div id="amr-1209007" class="section level1">
+    <div id="amr-1209008" class="section level1">
-<h1 class="page-header" data-toc-text="1.2.0.9007">
+<h1 class="page-header" data-toc-text="1.2.0.9008">
-<a href="#amr-1209007" class="anchor"></a>AMR 1.2.0.9007<small> Unreleased </small>
+<a href="#amr-1209008" class="anchor"></a>AMR 1.2.0.9008<small> Unreleased </small>
 </h1>
 <div id="last-updated-17-jun-2020" class="section level2">
 <h2 class="hasAnchor">
@@ -251,7 +251,12 @@
 
 <span class="fu"><a href="https://dplyr.tidyverse.org/reference/reexports.html">tibble</a></span>(<span class="kw">J01CA01</span> <span class="kw">=</span> <span class="st">"S"</span>) <span class="kw">%&gt;%</span>
   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="fu"><a href="../reference/antibiotic_class_selectors.html">penicillins</a></span>())
-<span class="co">#&gt; Selecting beta-lactams/penicillins: `J01CA01` (ampicillin)</span></pre></div>
+<span class="co">#&gt; Selecting beta-lactams/penicillins: `J01CA01` (ampicillin)</span>
+
+<span class="co"># select an antibiotic class manually with `ab_class()`</span>
+<span class="no">example_isolates</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="fu"><a href="../reference/antibiotic_class_selectors.html">ab_class</a></span>(<span class="st">"mycobact"</span>))
+<span class="co">#&gt; Selecting antimycobacterials: `RIF` (rifampicin)</span></pre></div>
 </li>
 </ul>
 </div>
@@ -260,7 +265,7 @@
 <a href="#changed" class="anchor"></a>Changed</h3>
 <ul>
 <li>Fixed a bug where <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> would not work on a tibble when the <code>tibble</code> or <code>dplyr</code> package was loaded</li>
-<li>All <code>*_join_microorganisms()</code> functions now return the original data class (e.g. tibbles and data.tables)</li>
+<li>All <code>*_join_microorganisms()</code> functions and <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> now return the original data class (e.g. <code>tibble</code>s and <code>data.table</code>s)</li>
 <li>Fixed a bug where <code><a href="../reference/as.ab.html">as.ab()</a></code> would return an error on invalid input values</li>
 <li>Fixed a bug for using grouped versions of <code><a href="../reference/proportion.html">rsi_df()</a></code>, <code><a href="../reference/proportion.html">proportion_df()</a></code> and <code><a href="../reference/count.html">count_df()</a></code>, and fixed a bug where not all different antimicrobial results were added as rows</li>
 <li>Added function <code><a href="../reference/filter_ab_class.html">filter_penicillins()</a></code> to filter isolates on a specific result in any column with a name in the antimicrobial ‘penicillins’ class (more specific: ATC subgroup <em>Beta-lactam antibacterials, penicillins</em>)</li>
@@ -269,6 +274,7 @@
 <li>Added antibiotics code “FOX1” for cefoxitin screening (abbreviation “cfsc”) to the <code>antibiotics</code> data set</li>
 <li>Improved auto-determination for columns of types <code>&lt;mo&gt;</code> and <code>&lt;Date&gt;</code>
 </li>
+<li>Fixed a bug in <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> for when only one antibiotic was in the input data</li>
 </ul>
 </div>
 </div>

docs/pkgdown.yml

@@ -10,7 +10,7 @@ articles:
   WHONET: WHONET.html
   benchmarks: benchmarks.html
   resistance_predict: resistance_predict.html
-last_built: 2020-06-16T23:38Z
+last_built: 2020-06-17T13:03Z
 urls:
   reference: https://msberends.gitlab.io/AMR/reference
   article: https://msberends.gitlab.io/AMR/articles

docs/reference/antibiotic_class_selectors.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 
@@ -235,7 +235,9 @@
     <p>Use these selection helpers inside any function that allows <a href='https://tidyselect.r-lib.org/reference/language.html'>Tidyverse selections</a>, like <code><a href='https://dplyr.tidyverse.org/reference/select.html'>dplyr::select()</a></code> or <code><a href='https://tidyr.tidyverse.org/reference/pivot_longer.html'>tidyr::pivot_longer()</a></code>. They help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.</p>
     </div>
 
-    <pre class="usage"><span class='fu'>aminoglycosides</span>()
+    <pre class="usage"><span class='fu'>ab_class</span>(<span class='no'>ab_class</span>)
+
+<span class='fu'>aminoglycosides</span>()
 
 <span class='fu'>carbapenems</span>()
 
@@ -261,6 +263,14 @@
 
 <span class='fu'>tetracyclines</span>()</pre>
 
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>ab_class</th>
+      <td><p>an antimicrobial class, like <code>"carbapenems"</code>. The columns <code>group</code>, <code>atc_group1</code> and <code>atc_group2</code> of the <a href='antibiotics.html'>antibiotics</a> data set will be searched (case-insensitive) for this value.</p></td>
+    </tr>
+    </table>
 
     <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
 
@@ -277,11 +287,22 @@
   <span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
     <span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='fu'>carbapenems</span>())
 
-
   <span class='co'># this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':</span>
   <span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
     <span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mo</span>, <span class='fu'>aminoglycosides</span>())
 
+  <span class='co'># this will select columns 'mo' and all antimycobacterial drugs ('RIF'):</span>
+  <span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mo</span>, <span class='fu'>ab_class</span>(<span class='st'>"mycobact"</span>))
+
+
+  <span class='co'># get bug/drug combinations for only macrolides in Gram-positives:</span>
+  <span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='fu'><a href='mo_property.html'>mo_gramstain</a></span>(<span class='no'>mo</span>) <span class='kw'>%like%</span> <span class='st'>"pos"</span>) <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mo</span>, <span class='fu'>macrolides</span>()) <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='bug_drug_combinations.html'>bug_drug_combinations</a></span>() <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='https://rdrr.io/r/base/format.html'>format</a></span>()
+
 
   <span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(<span class='kw'>irrelevant</span> <span class='kw'>=</span> <span class='st'>"value"</span>,
              <span class='kw'>J01CA01</span> <span class='kw'>=</span> <span class='st'>"S"</span>) <span class='kw'>%&gt;%</span>   <span class='co'># ATC code of ampicillin</span>

docs/reference/as.mo.html

@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 
@@ -425,7 +425,7 @@ This package contains the complete taxonomic tree of almost all microorganisms (
 <span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
 <span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='fu'>as.mo</span>(<span class='no'>df</span>$<span class='no'>microorganism_name</span>)
 
-<span class='co'># the select function of tidyverse is also supported:</span>
+<span class='co'># the select function of the Tidyverse is also supported:</span>
 <span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
 <span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='no'>df</span> <span class='kw'>%&gt;%</span>
   <span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>microorganism_name</span>) <span class='kw'>%&gt;%</span>

docs/reference/index.html

@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 
@@ -420,6 +420,12 @@
         <td><p>Principal Component Analysis (for AMR)</p></td>
       </tr><tr>
         
+        <td>
+          <p><code><a href="antibiotic_class_selectors.html">ab_class()</a></code> <code><a href="antibiotic_class_selectors.html">aminoglycosides()</a></code> <code><a href="antibiotic_class_selectors.html">carbapenems()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_1st()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_2nd()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_3rd()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_4th()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_5th()</a></code> <code><a href="antibiotic_class_selectors.html">fluoroquinolones()</a></code> <code><a href="antibiotic_class_selectors.html">glycopeptides()</a></code> <code><a href="antibiotic_class_selectors.html">macrolides()</a></code> <code><a href="antibiotic_class_selectors.html">penicillins()</a></code> <code><a href="antibiotic_class_selectors.html">tetracyclines()</a></code> </p>
+        </td>
+        <td><p>Antibiotic class selectors</p></td>
+      </tr><tr>
+        
         <td>
           <p><code><a href="filter_ab_class.html">filter_ab_class()</a></code> <code><a href="filter_ab_class.html">filter_aminoglycosides()</a></code> <code><a href="filter_ab_class.html">filter_carbapenems()</a></code> <code><a href="filter_ab_class.html">filter_cephalosporins()</a></code> <code><a href="filter_ab_class.html">filter_1st_cephalosporins()</a></code> <code><a href="filter_ab_class.html">filter_2nd_cephalosporins()</a></code> <code><a href="filter_ab_class.html">filter_3rd_cephalosporins()</a></code> <code><a href="filter_ab_class.html">filter_4th_cephalosporins()</a></code> <code><a href="filter_ab_class.html">filter_5th_cephalosporins()</a></code> <code><a href="filter_ab_class.html">filter_fluoroquinolones()</a></code> <code><a href="filter_ab_class.html">filter_glycopeptides()</a></code> <code><a href="filter_ab_class.html">filter_macrolides()</a></code> <code><a href="filter_ab_class.html">filter_penicillins()</a></code> <code><a href="filter_ab_class.html">filter_tetracyclines()</a></code> </p>
         </td>

docs/reference/lifecycle.html

@@ -49,9 +49,9 @@
   <script src="../extra.js"></script>
 
 <meta property="og:title" content="Lifecycles of functions in the <code>AMR</code> package — lifecycle" />
-<meta property="og:description" content="Functions in this AMR package are categorised using the lifecycle circle of the tidyverse as found on www.tidyverse.org/lifecycle.
+<meta property="og:description" content="Functions in this AMR package are categorised using the lifecycle circle of the Tidyverse as found on www.tidyverse.org/lifecycle.
  
-This page contains a section for every lifecycle (with text borrowed from the aforementioned tidyverse website), so they can be used in the manual pages of the functions." />
+This page contains a section for every lifecycle (with text borrowed from the aforementioned Tidyverse website), so they can be used in the manual pages of the functions." />
 <meta property="og:image" content="https://msberends.gitlab.io/AMR/logo.svg" />
 
 
@@ -84,7 +84,7 @@ This page contains a section for every lifecycle (with text borrowed from the af
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 
@@ -234,9 +234,9 @@ This page contains a section for every lifecycle (with text borrowed from the af
     </div>
 
     <div class="ref-description">
-    <p>Functions in this <code>AMR</code> package are categorised using <a href='https://www.tidyverse.org/lifecycle'>the lifecycle circle of the <code>tidyverse</code> as found on www.tidyverse.org/lifecycle</a>.</p>
+    <p>Functions in this <code>AMR</code> package are categorised using <a href='https://www.Tidyverse.org/lifecycle'>the lifecycle circle of the Tidyverse as found on www.tidyverse.org/lifecycle</a>.</p>
-<p><img src='figures/lifecycle_tidyverse.svg' height=200px style=margin-bottom:5px /> <br />
+<p><img src='figures/lifecycle_Tidyverse.svg' height=200px style=margin-bottom:5px /> <br />
-This page contains a section for every lifecycle (with text borrowed from the aforementioned <code>tidyverse</code> website), so they can be used in the manual pages of the functions.</p>
+This page contains a section for every lifecycle (with text borrowed from the aforementioned Tidyverse website), so they can be used in the manual pages of the functions.</p>
     </div>
 
 

docs/reference/proportion.html

@@ -83,7 +83,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9008</span>
       </span>
     </div>
 
@@ -322,7 +322,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
 
     <p>The function <code>resistance()</code> is equal to the function <code>proportion_R()</code>. The function <code>susceptibility()</code> is equal to the function <code>proportion_SI()</code>.</p>
 <p><strong>Remember that you should filter your table to let it contain only first isolates!</strong> This is needed to exclude duplicates and to reduce selection bias. Use <code><a href='first_isolate.html'>first_isolate()</a></code> to determine them in your data set.</p>
-<p>These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the <code><a href='count.html'>count()</a></code>][AMR::count()] functions to count isolates. The function <code>susceptibility()</code> is essentially equal to <code>count_susceptible() / count_all()</code>. <em>Low counts can influence the outcome - the <code>proportion</code> functions may camouflage this, since they only return the proportion (albeit being dependent on the <code>minimum</code> parameter).</em></p>
+<p>These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the <code><a href='count.html'>count()</a></code> functions to count isolates. The function <code>susceptibility()</code> is essentially equal to <code>count_susceptible() / count_all()</code>. <em>Low counts can influence the outcome - the <code>proportion</code> functions may camouflage this, since they only return the proportion (albeit being dependent on the <code>minimum</code> parameter).</em></p>
 <p>The function <code>proportion_df()</code> takes any variable from <code>data</code> that has an <code><a href='as.rsi.html'>rsi</a></code> class (created with <code><a href='as.rsi.html'>as.rsi()</a></code>) and calculates the proportions R, I and S. It also supports grouped variables. The function <code>rsi_df()</code> works exactly like <code>proportion_df()</code>, but adds the number of isolates.</p>
     <h2 class="hasAnchor" id="combination-therapy"><a class="anchor" href="#combination-therapy"></a>Combination therapy</h2>
 
@@ -410,7 +410,7 @@ A microorganism is categorised as <em>Susceptible, Increased exposure</em> when
               <span class='kw'>SI</span> <span class='kw'>=</span> <span class='fu'>susceptibility</span>(<span class='no'>CIP</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
               <span class='kw'>n1</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>CIP</span>),  <span class='co'># the actual total; sum of all three</span>
               <span class='kw'>n2</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='no'>CIP</span>),      <span class='co'># same - analogous to n_distinct</span>
-              <span class='kw'>total</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/n.html'>n</a></span>())          <span class='co'># NOT the number of tested isolates!</span>
+              <span class='kw'>total</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/context.html'>n</a></span>())          <span class='co'># NOT the number of tested isolates!</span>
 
   <span class='co'># Calculate co-resistance between amoxicillin/clav acid and gentamicin,</span>
   <span class='co'># so we can see that combination therapy does a lot more than mono therapy:</span>

man/antibiotic_class_selectors.Rd

@@ -2,6 +2,7 @@
 % Please edit documentation in R/ab_class_selectors.R
 \name{antibiotic_class_selectors}
 \alias{antibiotic_class_selectors}
+\alias{ab_class}
 \alias{aminoglycosides}
 \alias{carbapenems}
 \alias{cephalosporins}
@@ -17,6 +18,8 @@
 \alias{tetracyclines}
 \title{Antibiotic class selectors}
 \usage{
+ab_class(ab_class)
+
 aminoglycosides()
 
 carbapenems()
@@ -43,6 +46,9 @@ penicillins()
 
 tetracyclines()
 }
+\arguments{
+\item{ab_class}{an antimicrobial class, like \code{"carbapenems"}. The columns \code{group}, \code{atc_group1} and \code{atc_group2} of the \link{antibiotics} data set will be searched (case-insensitive) for this value.}
+}
 \description{
 Use these selection helpers inside any function that allows \href{https://tidyselect.r-lib.org/reference/language.html}{Tidyverse selections}, like \code{dplyr::select()} or \code{tidyr::pivot_longer()}. They help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
 }
@@ -58,11 +64,22 @@ if (require("dplyr")) {
   example_isolates \%>\% 
     select(carbapenems())
     
-    
   # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
   example_isolates \%>\% 
     select(mo, aminoglycosides())
     
+  # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
+  example_isolates \%>\% 
+    select(mo, ab_class("mycobact"))
+    
+    
+  # get bug/drug combinations for only macrolides in Gram-positives:
+  example_isolates \%>\% 
+    filter(mo_gramstain(mo) \%like\% "pos") \%>\% 
+    select(mo, macrolides()) \%>\% 
+    bug_drug_combinations() \%>\%
+    format()
+    
     
   data.frame(irrelevant = "value",
              J01CA01 = "S") \%>\%   # ATC code of ampicillin

man/as.mo.Rd

@@ -192,7 +192,7 @@ mo_gramstain("E. coli")       # returns "Gram negative"
 \dontrun{
 df$mo <- as.mo(df$microorganism_name)
 
-# the select function of tidyverse is also supported:
+# the select function of the Tidyverse is also supported:
 library(dplyr)
 df$mo <- df \%>\%
   select(microorganism_name) \%>\%

man/lifecycle.Rd

@@ -4,10 +4,10 @@
 \alias{lifecycle}
 \title{Lifecycles of functions in the \code{AMR} package}
 \description{
-Functions in this \code{AMR} package are categorised using \href{https://www.tidyverse.org/lifecycle}{the lifecycle circle of the \code{tidyverse} as found on www.tidyverse.org/lifecycle}.
+Functions in this \code{AMR} package are categorised using \href{https://www.Tidyverse.org/lifecycle}{the lifecycle circle of the Tidyverse as found on www.tidyverse.org/lifecycle}.
 
-\if{html}{\figure{lifecycle_tidyverse.svg}{options: height=200px style=margin-bottom:5px} \cr}
+\if{html}{\figure{lifecycle_Tidyverse.svg}{options: height=200px style=margin-bottom:5px} \cr}
-This page contains a section for every lifecycle (with text borrowed from the aforementioned \code{tidyverse} website), so they can be used in the manual pages of the functions.
+This page contains a section for every lifecycle (with text borrowed from the aforementioned Tidyverse website), so they can be used in the manual pages of the functions.
 }
 \section{Experimental lifecycle}{
 

man/proportion.Rd

@@ -83,7 +83,7 @@ The function \code{\link[=resistance]{resistance()}} is equal to the function \c
 
 \strong{Remember that you should filter your table to let it contain only first isolates!} This is needed to exclude duplicates and to reduce selection bias. Use \code{\link[=first_isolate]{first_isolate()}} to determine them in your data set.
 
-These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the \code{count()}][AMR::count()] functions to count isolates. The function \code{\link[=susceptibility]{susceptibility()}} is essentially equal to \code{count_susceptible() / count_all()}. \emph{Low counts can influence the outcome - the \code{proportion} functions may camouflage this, since they only return the proportion (albeit being dependent on the \code{minimum} parameter).}
+These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the \code{\link[AMR:count]{count()}} functions to count isolates. The function \code{\link[=susceptibility]{susceptibility()}} is essentially equal to \code{count_susceptible() / count_all()}. \emph{Low counts can influence the outcome - the \code{proportion} functions may camouflage this, since they only return the proportion (albeit being dependent on the \code{minimum} parameter).}
 
 The function \code{\link[=proportion_df]{proportion_df()}} takes any variable from \code{data} that has an \code{\link{rsi}} class (created with \code{\link[=as.rsi]{as.rsi()}}) and calculates the proportions R, I and S. It also supports grouped variables. The function \code{\link[=rsi_df]{rsi_df()}} works exactly like \code{\link[=proportion_df]{proportion_df()}}, but adds the number of isolates.
 }

vignettes/AMR.Rmd

@@ -190,7 +190,7 @@ Finally, we will apply [EUCAST rules](http://www.eucast.org/expert_rules_and_int
 Because the amoxicillin (column `AMX`) and amoxicillin/clavulanic acid (column `AMC`) in our data were generated randomly, some rows will undoubtedly contain AMX = S and AMC = R, which is technically impossible. The `eucast_rules()` fixes this:
 
 ```{r eucast, warning = FALSE, message = FALSE}
-data <- eucast_rules(data, col_mo = "bacteria")
+data <- eucast_rules(data, col_mo = "bacteria", rules = "all")
 ```
 
 # Adding new variables
@@ -332,6 +332,41 @@ data_1st %>%
   freq(genus, species, header = TRUE)
 ```
 
+## Overview of different bug/drug combinations
+
+If you want to get a quick glance of the number of isolates in different bug/drug combinations, you can use the `bug_drug_combinations()` function:
+
+```{r bug_drg 1a, eval = FALSE}
+data_1st %>% 
+  bug_drug_combinations() %>% 
+  head() # show first 6 rows
+```
+
+```{r bug_drg 1b, echo = FALSE, results = 'asis'}
+knitr::kable(data_1st %>% 
+               bug_drug_combinations() %>% 
+               head(),
+             align = "c")
+```
+
+Using [Tidyverse selections](https://tidyselect.r-lib.org/reference/language.html), you can also select columns based on the antibiotic class they are in:
+
+```{r bug_drg 2a, eval = FALSE}
+data_1st %>% 
+  select(bacteria, fluoroquinolones()) %>% 
+  bug_drug_combinations()
+```
+
+
+```{r bug_drg 2b, echo = FALSE, results = 'asis'}
+knitr::kable(data_1st %>% 
+               select(bacteria, fluoroquinolones()) %>% 
+               bug_drug_combinations(),
+             align = "c")
+```
+
+This will only give you the crude numbers in the data. To calculate antimicrobial resistance, we use the `resistance()` and `susceptibility()` functions.
+
 ## Resistance percentages
 
 The functions `resistance()` and `susceptibility()` can be used to calculate antimicrobial resistance or susceptibility. For more specific analyses, the functions `proportion_S()`, `proportion_SI()`, `proportion_I()`, `proportion_IR()` and `proportion_R()` can be used to determine the proportion of a specific antimicrobial outcome.