(v1.6.0.9012) unit tests

(v1.6.0.9011) unit tests
(v1.6.0.9010) big first_isolate() update
2026-10-01 04:13:33 +02:00 · 2021-04-27 11:28:17 +02:00 · 2021-04-27 10:27:13 +02:00 · 2021-04-26 23:57:37 +02:00 · 2021-04-23 16:13:26 +02:00 · 2021-04-23 09:59:36 +02:00
172 changed files with 5491 additions and 3970 deletions
@@ -1,3 +1,4 @@
+^.*\.RData$
 ^.*\.Rproj$
 ^\.Renviron$
 ^\.Rprofile$
@@ -65,10 +65,10 @@ jobs:
          - {os: ubuntu-20.04,   r: '3.6',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
          - {os: ubuntu-20.04,   r: '3.5',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
          - {os: ubuntu-20.04,   r: '3.4',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.3',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
+          - {os: ubuntu-20.04,   r: '3.3',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
          # - {os: ubuntu-20.04,   r: '3.2',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
          # - {os: ubuntu-20.04,   r: '3.1',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.0',     allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
+          - {os: ubuntu-20.04,   r: '3.0',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
          
          - {os: ubuntu-16.04,   r: 'devel',   allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
          - {os: ubuntu-16.04,   r: 'release', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
@@ -77,10 +77,10 @@ jobs:
          - {os: ubuntu-16.04,   r: '3.6',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
          - {os: ubuntu-16.04,   r: '3.5',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
          - {os: ubuntu-16.04,   r: '3.4',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
-          - {os: ubuntu-16.04,   r: '3.3',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
+          - {os: ubuntu-16.04,   r: '3.3',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
          # - {os: ubuntu-16.04,   r: '3.2',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
          # - {os: ubuntu-16.04,   r: '3.1',     allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
-          - {os: ubuntu-16.04,   r: '3.0',     allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
+          - {os: ubuntu-16.04,   r: '3.0',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
          
    env:
      R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
@@ -151,6 +151,8 @@ jobs:
        if: matrix.config.r != '3.0' && matrix.config.r != '3.1' && matrix.config.r != '3.2'
        env:
          _R_CHECK_CRAN_INCOMING_: false
+          _R_CHECK_LENGTH_1_CONDITION_: verbose
+          _R_CHECK_LENGTH_1_LOGIC2_: verbose
        run: rcmdcheck::rcmdcheck(args = c("--no-manual", "--as-cran"), error_on = "warning", check_dir = "check")
        shell: Rscript {0}
        
@@ -159,10 +161,12 @@ jobs:
        env:
          _R_CHECK_CRAN_INCOMING_: false
          _R_CHECK_FORCE_SUGGESTS_: false
+          _R_CHECK_DEPENDS_ONLY_: true
          _R_CHECK_LENGTH_1_CONDITION_: verbose
          _R_CHECK_LENGTH_1_LOGIC2_: verbose
        run: |
-          R CMD check data-raw/AMR_latest.tar.gz --no-manual --no-build-vignettes
+          tar -xvf data-raw/AMR_latest.tar.gz
+          R CMD check AMR --no-manual --no-build-vignettes

      - name: Show testthat output
        if: always()
@@ -1,6 +1,6 @@
 Package: AMR
-Version: 1.6.0
-Date: 2021-03-14
+Version: 1.6.0.9012
+Date: 2021-04-27
 Title: Antimicrobial Resistance Data Analysis
 Authors@R: c(
    person(role = c("aut", "cre"), 
@@ -35,11 +35,10 @@ Authors@R: c(
           family = "Souverein", given = "Dennis", email = "d.souvereing@streeklabhaarlem.nl"),
    person(role = "ctb",
           family = "Underwood", given = "Anthony", email = "au3@sanger.ac.uk"))
-Description: Functions to simplify the analysis and prediction of Antimicrobial 
-    Resistance (AMR) and to work with microbial and antimicrobial properties by
-    using evidence-based methods, like those defined by Leclercq et al. (2013) 
-    <doi:10.1111/j.1469-0691.2011.03703.x> and containing reference data such as 
-    LPSN <doi:10.1099/ijsem.0.004332>.
+Description: Functions to simplify and standardise antimicrobial resistance (AMR)
+    data analysis and to work with microbial and antimicrobial properties by
+    using evidence-based methods and reliable reference data such as LPSN
+    <doi:10.1099/ijsem.0.004332>.
 Depends:
    R (>= 3.0.0)
 Suggests:
@@ -43,6 +43,8 @@ S3method(as.data.frame,ab)
 S3method(as.data.frame,mo)
 S3method(as.double,mic)
 S3method(as.integer,mic)
+S3method(as.list,custom_eucast_rules)
+S3method(as.list,custom_mdro_guideline)
 S3method(as.matrix,mic)
 S3method(as.numeric,mic)
 S3method(as.rsi,data.frame)
@@ -57,6 +59,8 @@ S3method(barplot,disk)
 S3method(barplot,mic)
 S3method(barplot,rsi)
 S3method(c,ab)
+S3method(c,custom_eucast_rules)
+S3method(c,custom_mdro_guideline)
 S3method(c,disk)
 S3method(c,mic)
 S3method(c,mo)
@@ -97,6 +101,7 @@ S3method(plot,rsi)
 S3method(print,ab)
 S3method(print,bug_drug_combinations)
 S3method(print,catalogue_of_life_version)
+S3method(print,custom_eucast_rules)
 S3method(print,custom_mdro_guideline)
 S3method(print,disk)
 S3method(print,mic)
@@ -137,6 +142,8 @@ S3method(unique,mo)
 S3method(unique,rsi)
 export("%like%")
 export("%like_case%")
+export("%unlike%")
+export("%unlike_case%")
 export(ab_atc)
 export(ab_atc_group1)
 export(ab_atc_group2)
@@ -154,8 +161,10 @@ export(ab_tradenames)
 export(ab_url)
 export(age)
 export(age_groups)
+export(all_antimicrobials)
 export(aminoglycosides)
 export(anti_join_microorganisms)
+export(antimicrobials_equal)
 export(as.ab)
 export(as.disk)
 export(as.mic)
@@ -184,6 +193,7 @@ export(count_all)
 export(count_df)
 export(count_resistant)
 export(count_susceptible)
+export(custom_eucast_rules)
 export(custom_mdro_guideline)
 export(eucast_dosage)
 export(eucast_exceptional_phenotypes)
@@ -229,6 +239,7 @@ export(is.rsi.eligible)
 export(is_new_episode)
 export(key_antibiotics)
 export(key_antibiotics_equal)
+export(key_antimicrobials)
 export(kurtosis)
 export(labels_rsi_count)
 export(left_join_microorganisms)
@@ -1,5 +1,40 @@
-# AMR 1.6.0
+# AMR 1.6.0.9012
+## <small>Last updated: 27 April 2021</small>

+### New
+* Function `custom_eucast_rules()` that brings support for custom AMR rules in `eucast_rules()`
+* Support for all four methods to determine first isolates as summarised by Hindler *et al* (doi: [10.1086/511864](https://doi.org/10.1086/511864)): isolate-based, patient-based, episode-based and phenotype-based. The last method is now the default.
+  * Since fungal isolates can also be selected, new functions `key_antimicrobials()` and `all_antimicrobials()` have replaced the now deprecated function `key_antibiotics()`
+  * Using `key_antimicrobials()` still only selects six preferred antibiotics for Gram-negatives, six for Gram-positives, and six universal antibiotics. It has a new `antifungal` argument to set antifungal agents (antimycotics).
+  * The `first_isolate()` function gained the argument `method` that has to be "phenotype-based", "episode-based", "patient-based", or "isolate-based". The old behaviour is equal to "episode-based", while the new default is "phenotype-based".
+  * Using `type == "points"` in the `first_isolate()` function for phenotype-based selection will now consider all antimicrobial drugs in the data set, using the new `all_antimicrobials()`
+  * The `first_isolate()` function can now take a vector of values for `col_keyantibiotics` and can have an episode length of `Inf`
+  * The `filter_first_isolate()` function has not changed, as it uses the episode-based method. The `filter_first_weighted_isolate()` may now include more isolates as uses the phenotype-based method.
+  * The documentation of the `first_isolate()` and `key_antimicrobials()` functions has been completely rewritten.
+
+### Changed
+* Custom MDRO guidelines (`mdro()`, `custom_mdro_guideline()`):
+  * Custom MDRO guidelines can now be combined with other custom MDRO guidelines using `c()`
+  * Fix for applying the rules; in previous versions, rows were interpreted according to the last matched rule. Now, rows are interpreted according to the first matched rule
+* Fix for `age_groups()` for persons aged zero
+* The `example_isolates` data set now contains some (fictitious) zero-year old patients
+* Fix for minor translation errors
+* Printing of microbial codes in a `data.frame` or `tibble` now gives a warning if the data contains old microbial codes (from a previous AMR package version)
+* Extended the `like()` functions:
+  * Now checks if `pattern` is a *valid* regular expression
+  * Added `%unlike%` and `%unlike_case%` (as negations of the existing `%like%` and `%like_case%`). This greatly improves readability:
+    ```r
+    if (!grepl("EUCAST", guideline)) ...
+    # same:
+    if (guideline %unlike% "EUCAST") ...
+    ```
+  * Altered the RStudio addin, so it now iterates over `%like%` -> `%unlike%` -> `%like_case%` -> `%unlike_case%` if you keep pressing your keyboard shortcut
+* Fixed an installation error on R-3.0
+* Added `info` argument to `as.mo()` to turn on/off the progress bar
+* Fixed a bug that `col_mo` for some functions (esp. `eucast_rules()` and `mdro()`) could not be column names of the `microorganisms` data set as it would throw an error
+
+
+# AMR 1.6.0

 ### New
 * Support for EUCAST Clinical Breakpoints v11.0 (2021), effective in the `eucast_rules()` function and in `as.rsi()` to interpret MIC and disk diffusion values. This is now the default guideline in this package.
@@ -59,7 +94,7 @@
  ```

 ### Changed
-* Updated the bacterial taxonomy to 3 March 2021 (using [LSPN](https://lpsn.dsmz.de))
+* Updated the bacterial taxonomy to 3 March 2021 (using [LPSN](https://lpsn.dsmz.de))
  * Added 3,372 new species and 1,523 existing species became synomyms
  * The URL of a bacterial species (`mo_url()`) will now lead to https://lpsn.dsmz.de
 * Big update for plotting classes `rsi`, `<mic>`, and `<disk>`:
@@ -71,7 +71,49 @@ addin_insert_in <- function() {

 # No export, no Rd
 addin_insert_like <- function() {
-  import_fn("insertText", "rstudioapi")(" %like% ")
+  # we want Shift + Ctrl/Cmd + L to iterate over %like%, %unlike%, %like_case%, and %unlike_case%
+  
+  getActiveDocumentContext <- import_fn("getActiveDocumentContext", "rstudioapi")
+  insertText <- import_fn("insertText", "rstudioapi")
+  modifyRange <- import_fn("modifyRange", "rstudioapi")
+  document_range <- import_fn("document_range", "rstudioapi")
+  document_position <- import_fn("document_position", "rstudioapi")
+  
+  context <- getActiveDocumentContext()
+  current_row <- context$selection[[1]]$range$end[1]
+  current_col <- context$selection[[1]]$range$end[2]
+  current_row_txt <- context$contents[current_row]
+  if (is.null(current_row) || current_row_txt %unlike% "%(un)?like") {
+    insertText(" %like% ")
+    return(invisible())
+  }
+  
+  pos_preceded_by <- function(txt) {
+    if (tryCatch(substr(current_row_txt, current_col - nchar(trimws(txt, which = "right")), current_col) == trimws(txt, which = "right"),
+                 error = function(e) FALSE)) {
+      return(TRUE)
+    }
+    tryCatch(substr(current_row_txt, current_col - nchar(txt), current_col) %like% paste0("^", txt),
+             error = function(e) FALSE)
+  }
+  replace_pos <- function(old, with) {
+    modifyRange(document_range(document_position(current_row, current_col - nchar(old)),
+                               document_position(current_row, current_col)),
+                text = with,
+                id = context$id)
+  }
+  
+  if (pos_preceded_by(" %like% ")) {
+    replace_pos(" %like% ", with = " %unlike% ")
+  } else if (pos_preceded_by(" %unlike% ")) {
+    replace_pos(" %unlike% ", with = " %like_case% ")
+  } else if (pos_preceded_by(" %like_case% ")) {
+    replace_pos(" %like_case% ", with = " %unlike_case% ")
+  } else if (pos_preceded_by(" %unlike_case% ")) {
+    replace_pos(" %unlike_case% ", with = " %like% ")
+  } else {
+    insertText(" %like% ")
+  }
 }

 check_dataset_integrity <- function() {
@@ -148,8 +190,8 @@ search_type_in_df <- function(x, type, info = TRUE) {
  }
  # -- key antibiotics
  if (type == "keyantibiotics") {
-    if (any(colnames(x) %like% "^key.*(ab|antibiotics)")) {
-      found <- sort(colnames(x)[colnames(x) %like% "^key.*(ab|antibiotics)"])[1]
+    if (any(colnames(x) %like% "^key.*(ab|antibiotics|antimicrobials)")) {
+      found <- sort(colnames(x)[colnames(x) %like% "^key.*(ab|antibiotics|antimicrobials)"])[1]
    }
  }
  # -- date
@@ -211,10 +253,21 @@ search_type_in_df <- function(x, type, info = TRUE) {
  found
 }

-is_possibly_regex <- function(x) {
-  tryCatch(vapply(FUN.VALUE = character(1), strsplit(x, ""),
-                  function(y) any(y %in% c("$", "(", ")", "*", "+", "-", ".", "?", "[", "]", "^", "{", "|", "}", "\\"), na.rm = TRUE)),
-           error = function(e) rep(TRUE, length(x)))
+is_valid_regex <- function(x) {
+  regex_at_all <- tryCatch(vapply(FUN.VALUE = logical(1),
+                                  X = strsplit(x, ""),
+                                  FUN = function(y) any(y %in% c("$", "(", ")", "*", "+", "-",
+                                                                 ".", "?", "[", "]", "^", "{", 
+                                                                 "|", "}", "\\"),
+                                                        na.rm = TRUE),
+                                  USE.NAMES = FALSE),
+                           error = function(e) rep(TRUE, length(x)))
+  regex_valid <- vapply(FUN.VALUE = logical(1),
+                        X = x,
+                        FUN = function(y) !"try-error" %in% class(try(grepl(y, "", perl = TRUE),
+                                                                      silent = TRUE)),
+                        USE.NAMES = FALSE)
+  regex_at_all & regex_valid
 }

 stop_ifnot_installed <- function(package) {
@@ -223,8 +276,8 @@ stop_ifnot_installed <- function(package) {
  vapply(FUN.VALUE = character(1), package, function(pkg)
    tryCatch(get(".packageName", envir = asNamespace(pkg)),
             error = function(e) {
-               if (package == "rstudioapi") {
-                 stop("This function only works in RStudio.", call. = FALSE)
+               if (pkg == "rstudioapi") {
+                 stop("This function only works in RStudio when using R >= 3.2.", call. = FALSE)
               } else if (pkg != "base") {
                 stop("This requires the '", pkg, "' package.",
                      "\nTry to install it with: install.packages(\"", pkg, "\")",
@@ -265,7 +318,9 @@ word_wrap <- function(...,
  msg <- paste0(c(...), collapse = "")
  
  if (isTRUE(as_note)) {
-    msg <- paste0("NOTE: ", gsub("^note:? ?", "", msg, ignore.case = TRUE))
+    # \u2139 is a symbol officially named 'information source'
+    # \ufe0f can add the blue square around it: \u2139\ufe0f
+    msg <- paste0("\u2139 ", gsub("^note:? ?", "", msg, ignore.case = TRUE))
  }
  
  if (msg %like% "\n") {
@@ -299,8 +354,8 @@ word_wrap <- function(...,
  msg <- paste0(msg, collapse = " ")
  msg <- gsub("\n ", "\n", msg, fixed = TRUE)
  
-  if (msg_stripped %like% "^NOTE: ") {
-    indentation <- 6 + extra_indent
+  if (msg_stripped %like% "\u2139 ") {
+    indentation <- 2 + extra_indent
  } else if (msg_stripped %like% "^=> ") {
    indentation <- 3 + extra_indent
  } else {
@@ -504,8 +559,8 @@ format_class <- function(class, plural) {
  if ("matrix" %in% class) {
    class <- "a matrix"
  }
-  if ("isolate_identifier" %in% class) {
-    class <- "created with isolate_identifier()"
+  if ("custom_eucast_rules" %in% class) {
+    class <- "input created with `custom_eucast_rules()`"
  }
  if (any(c("mo", "ab", "rsi") %in% class)) {
    class <- paste0("of class <", class[1L], ">")
@@ -522,6 +577,7 @@ meet_criteria <- function(object,
                          looks_like = NULL,
                          is_in = NULL,
                          is_positive = NULL,
+                          is_positive_or_zero = NULL,
                          is_finite = NULL,
                          contains_column_class = NULL,
                          allow_NULL = FALSE,
@@ -590,16 +646,23 @@ meet_criteria <- function(object,
               ifelse(allow_NA == TRUE, ", or NA", ""),
               call = call_depth)
  }
-  if (!is.null(is_positive)) {
+  if (isTRUE(is_positive)) {
    stop_if(is.numeric(object) && !all(object > 0, na.rm = TRUE), "argument `", obj_name,
            "` must ",
            ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
-                   "be a positive number",
-                   "all be positive numbers"),
-            " (higher than zero)",
+                   "be a number higher than zero",
+                   "all be numbers higher than zero"),
            call = call_depth)
  }
-  if (!is.null(is_finite)) {
+  if (isTRUE(is_positive_or_zero)) {
+    stop_if(is.numeric(object) && !all(object >= 0, na.rm = TRUE), "argument `", obj_name,
+            "` must ",
+            ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
+                   "be zero or a positive number",
+                   "all be zero or numbers higher than zero"),
+            call = call_depth)
+  }
+  if (isTRUE(is_finite)) {
    stop_if(is.numeric(object) && !all(is.finite(object[!is.na(object)]), na.rm = TRUE), "argument `", obj_name,
            "` must ",
            ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
@@ -633,7 +696,7 @@ get_current_data <- function(arg_name, call) {
      return(out)
    }
  }
-  
+
  if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2) {
    # R-3.0 and R-3.1 do not have an `x` element in the call stack, rendering this function useless
    if (is.na(arg_name)) {
@@ -641,6 +704,7 @@ get_current_data <- function(arg_name, call) {
      warning_("this function can only be used in R >= 3.2", call = call)
      return(data.frame())
    } else {
+      # mimic a default R error, e.g. for example_isolates[which(mo_name() %like% "^ent"), ] 
      stop_("argument `", arg_name, "` is missing with no default", call = call)
    }
  }
@@ -650,12 +714,17 @@ get_current_data <- function(arg_name, call) {
  frms <- lapply(sys.frames(), function(el) {
    if (not_set == TRUE && ".Generic" %in% names(el)) {
      if (tryCatch(".data" %in% names(el) && is.data.frame(el$`.data`), error = function(e) FALSE)) {
-        # dplyr? - an element `.data` will be in the system call stack
-        # will be used in dplyr::select() (but not in dplyr::filter(), dplyr::mutate() or dplyr::summarise())
+        # - - - -
+        # dplyr
+        # - - - -
+        # an element `.data` will be in the system call stack when using dplyr::select()
+        # [but not when using dplyr::filter(), dplyr::mutate() or dplyr::summarise()]
        not_set <<- FALSE
        el$`.data`
      } else if (tryCatch(any(c("x", "xx") %in% names(el)), error = function(e) FALSE)) {
-        # otherwise try base R:
+        # - - - -
+        # base R
+        # - - - -
        # an element `x` will be in this environment for only cols, e.g. `example_isolates[, carbapenems()]`
        # an element `xx` will be in this environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
        if (tryCatch(is.data.frame(el$xx), error = function(e) FALSE)) {
@@ -675,6 +744,7 @@ get_current_data <- function(arg_name, call) {
    }
  })
  
+  # lookup the matched frame and return its value: a data.frame
  vars_df <- tryCatch(frms[[which(!vapply(FUN.VALUE = logical(1), frms, is.null))]], error = function(e) NULL)
  if (is.data.frame(vars_df)) {
    return(vars_df)
@@ -913,8 +983,8 @@ font_stripstyle <- function(x) {
  gsub("(?:(?:\\x{001b}\\[)|\\x{009b})(?:(?:[0-9]{1,3})?(?:(?:;[0-9]{0,3})*)?[A-M|f-m])|\\x{001b}[A-M]", "", x, perl = TRUE)
 }

-progress_ticker <- function(n = 1, n_min = 0, ...) {
-  if (!interactive() || n < n_min) {
+progress_ticker <- function(n = 1, n_min = 0, print = TRUE, ...) {
+  if (print == FALSE || n < n_min) {
    pb <- list()
    pb$tick <- function() {
      invisible()
@@ -1087,8 +1157,8 @@ time_track <- function(name = NULL) {
  paste("(until now:", trimws(round(as.numeric(Sys.time()) * 1000) - pkg_env$time_start), "ms)")
 }

-# prevent dependency on package 'backports'
-# these functions were not available in previous versions of R (last checked: R 4.0.3)
+# prevent dependency on package 'backports' ----
+# these functions were not available in previous versions of R (last checked: R 4.0.5)
 # see here for the full list: https://github.com/r-lib/backports
 strrep <- function(x, times) {
  x <- as.character(x)
@@ -1135,3 +1205,11 @@ isNamespaceLoaded <- function(pkg) {
 lengths <- function(x, use.names = TRUE) {
  vapply(x, length, FUN.VALUE = NA_integer_, USE.NAMES = use.names)
 }
+
+if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.1) {
+  # R-3.0 does not contain these functions, set them here to prevent installation failure
+  # (required for extension of the <mic> class)
+  cospi <- function(...) 1
+  sinpi <- function(...) 1
+  tanpi <- function(...) 1
+}
@@ -29,7 +29,7 @@
 #' @inheritSection lifecycle Stable Lifecycle
 #' @param x character vector to determine to antibiotic ID
 #' @param flag_multiple_results logical to indicate whether a note should be printed to the console that probably more than one antibiotic code or name can be retrieved from a single input value.
-#' @param info logical to indicate whether a progress bar should be printed
+#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
 #' @param ... arguments passed on to internal functions
 #' @rdname as.ab
 #' @inheritSection WHOCC WHOCC
@@ -90,7 +90,7 @@
 #'     rename_with(as.ab, where(is.rsi))
 #'    
 #' }
-as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
+as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
  meet_criteria(x, allow_class = c("character", "numeric", "integer", "factor"), allow_NA = TRUE)
  meet_criteria(flag_multiple_results, allow_class = "logical", has_length = 1)
  meet_criteria(info, allow_class = "logical", has_length = 1)
@@ -155,7 +155,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
  }
  
  if (initial_search == TRUE) {
-    progress <- progress_ticker(n = length(x), n_min = ifelse(isTRUE(info), 25, length(x) + 1)) # start if n >= 25
+    progress <- progress_ticker(n = length(x), n_min = 25, print = info) # start if n >= 25
    on.exit(close(progress))
  }
  
@@ -389,7 +389,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
      
      # first 5 except for cephalosporins, then first 7 (those cephalosporins all start quite the same!)
      found <- suppressWarnings(as.ab(substr(x[i], 1, 5), initial_search = FALSE))
-      if (!is.na(found) && !ab_group(found, initial_search = FALSE) %like% "cephalosporins") {
+      if (!is.na(found) && ab_group(found, initial_search = FALSE) %unlike% "cephalosporins") {
        x_new[i] <- note_if_more_than_one_found(found, i, from_text)
        next
      }
@@ -32,6 +32,7 @@
 #' @param collapse character to pass on to `paste(, collapse = ...)` to only return one character per element of `text`, see *Examples*
 #' @param translate_ab if `type = "drug"`: a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]. Defaults to `FALSE`. Using `TRUE` is equal to using "name".
 #' @param thorough_search logical to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to `TRUE` will take considerably more time than when using `FALSE`. At default, it will turn `TRUE` when all input elements contain a maximum of three words.
+#' @param info logical to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
 #' @param ... arguments passed on to [as.ab()]
 #' @details This function is also internally used by [as.ab()], although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the [as.ab()] function may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.
 #' 
@@ -92,6 +93,7 @@ ab_from_text <- function(text,
                         collapse = NULL,
                         translate_ab = FALSE,
                         thorough_search = NULL,
+                         info = interactive(),
                         ...) {
  if (missing(type)) {
    type <- type[1L]
@@ -102,12 +104,13 @@ ab_from_text <- function(text,
  meet_criteria(collapse, has_length = 1, allow_NULL = TRUE)
  meet_criteria(translate_ab, allow_NULL = FALSE) # get_translate_ab() will be more informative about what's allowed
  meet_criteria(thorough_search, allow_class = "logical", has_length = 1, allow_NULL = TRUE)
+  meet_criteria(info, allow_class = "logical", has_length = 1)

  type <- tolower(trimws(type))
  
  text <- tolower(as.character(text))
  text_split_all <- strsplit(text, "[ ;.,:\\|]")
-  progress <- progress_ticker(n = length(text_split_all), n_min = 5)
+  progress <- progress_ticker(n = length(text_split_all), n_min = 5, print = info)
  on.exit(close(progress))
  
  if (type %like% "(drug|ab|anti)") {
@@ -149,8 +149,8 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
 #' }
 #' }
 age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
-  meet_criteria(x, allow_class = c("numeric", "integer"), is_positive = TRUE, is_finite = TRUE)
-  meet_criteria(split_at, allow_class = c("numeric", "integer", "character"), is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(x, allow_class = c("numeric", "integer"), is_positive_or_zero = TRUE, is_finite = TRUE)
+  meet_criteria(split_at, allow_class = c("numeric", "integer", "character"), is_positive_or_zero = TRUE, is_finite = TRUE)
  meet_criteria(na.rm, allow_class = "logical", has_length = 1) 
  
  if (any(x < 0, na.rm = TRUE)) {
@@ -0,0 +1,306 @@
+# ==================================================================== #
+# TITLE                                                                #
+# Antimicrobial Resistance (AMR) Data Analysis for R                   #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# LICENCE                                                              #
+# (c) 2018-2021 Berends MS, Luz CF et al.                              #
+# Developed at the University of Groningen, the Netherlands, in        #
+# collaboration with non-profit organisations Certe Medical            #
+# Diagnostics & Advice, and University Medical Center Groningen.       #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+#' Define Custom EUCAST Rules
+#' 
+#' Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in [eucast_rules()].
+#' @inheritSection lifecycle Maturing Lifecycle
+#' @param ... rules in formula notation, see *Examples*
+#' @details
+#' Some organisations have their own adoption of EUCAST rules. This function can be used to define custom EUCAST rules to be used in the [eucast_rules()] function.
+#' 
+#' @section How it works:
+#' 
+#' ### Basics
+#' 
+#' If you are familiar with the [`case_when()`][dplyr::case_when()] function of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written *before* the tilde (`~`) and the consequence of the rule is written *after* the tilde:
+#' 
+#' ```
+#' x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
+#'                          TZP == "R" ~ aminopenicillins == "R")
+#' ```
+#' 
+#' These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:
+#' 
+#' ```
+#' x
+#' #> A set of custom EUCAST rules:
+#' #> 
+#' #>   1. If TZP is S then set to S:
+#' #>      amoxicillin (AMX), ampicillin (AMP)
+#' #> 
+#' #>   2. If TZP is R then set to R:
+#' #>      amoxicillin (AMX), ampicillin (AMP)
+#' ```
+#' 
+#' The rules (the part *before* the tilde, in above example `TZP == "S"` and `TZP == "R"`) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column `TZP` must exist. We will create a sample data set and test the rules set:
+#' 
+#' ```
+#' df <- data.frame(mo = c("E. coli", "K. pneumoniae"),
+#'                  TZP = "R",
+#'                  amox = "",
+#'                  AMP = "")
+#' df
+#' #>              mo TZP amox AMP
+#' #> 1       E. coli   R         
+#' #> 2 K. pneumoniae   R         
+#'                  
+#' eucast_rules(df, rules = "custom", custom_rules = x)
+#' #>              mo TZP amox AMP
+#' #> 1       E. coli   R    R   R     
+#' #> 2 K. pneumoniae   R    R   R  
+#' ```
+#' 
+#' ### Using taxonomic properties in rules
+#' 
+#' There is one exception in variables used for the rules: all column names of the [microorganisms] data set can also be used, but do not have to exist in the data set. These column names are: `r vector_and(colnames(microorganisms), quote = "``", sort = FALSE)`. Thus, this next example will work as well, despite the fact that the `df` data set does not contain a column `genus`:
+#' 
+#' ```
+#' y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
+#'                          TZP == "R" & genus == "Klebsiella" ~ aminopenicillins == "R")
+#'
+#' eucast_rules(df, rules = "custom", custom_rules = y)
+#' #>              mo TZP amox AMP
+#' #> 1       E. coli   R         
+#' #> 2 K. pneumoniae   R    R   R
+#' ```
+#' 
+#' ### Usage of antibiotic group names
+#' 
+#' It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part *after* the tilde. In above examples, the antibiotic group `aminopenicillins` is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the antibiotic agents that will be matched when running the rule.
+#' 
+#' `r paste0("  * ", sapply(DEFINED_AB_GROUPS, function(x) paste0("``", tolower(x), "``\\cr(", paste0(sort(ab_name(eval(parse(text = x), envir = asNamespace("AMR")), language = NULL, tolower = TRUE)), collapse = ", "), ")"), USE.NAMES = FALSE), "\n", collapse = "")`
+#' @returns A [list] containing the custom rules
+#' @export
+#' @examples
+#' x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
+#'                          AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+#' eucast_rules(example_isolates,
+#'              rules = "custom",
+#'              custom_rules = x,
+#'              info = FALSE)
+#'              
+#' # combine rule sets
+#' x2 <- c(x,
+#'         custom_eucast_rules(TZP == "R" ~ carbapenems == "R"))
+#' x2
+custom_eucast_rules <- function(...) {
+
+  dots <- tryCatch(list(...),
+                   error = function(e) "error")
+  stop_if(identical(dots, "error"),
+          "rules must be a valid formula inputs (e.g., using '~'), see `?custom_eucast_rules`")
+  n_dots <- length(dots)
+  stop_if(n_dots == 0, "no custom rules were set. Please read the documentation using `?custom_eucast_rules`.")
+  out <- vector("list", n_dots)
+  for (i in seq_len(n_dots)) {
+    stop_ifnot(inherits(dots[[i]], "formula"), 
+               "rule ", i, " must be a valid formula input (e.g., using '~'), see `?custom_eucast_rules`")
+    
+    # Query
+    qry <- dots[[i]][[2]]
+    if (inherits(qry, "call")) {
+      qry <- as.expression(qry)
+    }
+    qry <- as.character(qry)
+    # these will prevent vectorisation, so replace them:
+    qry <- gsub("&&", "&", qry, fixed = TRUE)
+    qry <- gsub("||", "|", qry, fixed = TRUE)
+    # format nicely, setting spaces around operators
+    qry <- gsub(" *([&|+-/*^><==]+) *", " \\1 ", qry)
+    qry <- gsub(" ?, ?", ", ", qry)
+    qry <- gsub("'", "\"", qry, fixed = TRUE)
+    out[[i]]$query <- as.expression(qry)
+    
+    # Resulting rule
+    result <- dots[[i]][[3]]
+    stop_ifnot(deparse(result) %like% "==", 
+               "the result of rule ", i, " (the part after the `~`) must contain `==`, such as in `... ~ ampicillin == \"R\"`, see `?custom_eucast_rules`")
+    result_group <- as.character(result)[[2]]
+    if (paste0(toupper(result_group), "S") %in% DEFINED_AB_GROUPS) {
+      # support for e.g. 'aminopenicillin' if user meant 'aminopenicillins'
+      result_group <- paste0(result_group, "s")
+    }
+    if (toupper(result_group) %in% DEFINED_AB_GROUPS) {
+      result_group <- eval(parse(text = toupper(result_group)), envir = asNamespace("AMR"))
+    } else {
+      result_group <- tryCatch(
+        suppressWarnings(as.ab(result_group,
+                               fast_mode = TRUE,
+                               info = FALSE, 
+                               flag_multiple_results = FALSE)),
+        error = function(e) NA_character_)
+    }
+    
+    stop_if(any(is.na(result_group)),
+            "this result of rule ", i, " could not be translated to a single antimicrobial agent/group: \"", 
+            as.character(result)[[2]], "\".\n\nThe input can be a name or code of an antimicrobial agent, or be one of: ", 
+            vector_or(tolower(DEFINED_AB_GROUPS), quotes = FALSE), ".")
+    result_value <- as.character(result)[[3]]
+    result_value[result_value == "NA"] <- NA
+    stop_ifnot(result_value %in% c("R", "S", "I", NA),
+               "the resulting value of rule ", i, " must be either \"R\", \"S\", \"I\" or NA")
+    result_value <- as.rsi(result_value)
+    
+    out[[i]]$result_group <- result_group
+    out[[i]]$result_value <- result_value
+  }
+  
+  names(out) <- paste0("rule", seq_len(n_dots))
+  set_clean_class(out, new_class = c("custom_eucast_rules", "list"))
+}
+
+#' @method c custom_eucast_rules
+#' @noRd
+#' @export
+c.custom_eucast_rules <- function(x, ...) {
+  if (length(list(...)) == 0) {
+    return(x)
+  }
+  out <- unclass(x)
+  for (e in list(...)) {
+    out <- c(out, unclass(e))
+  }
+  names(out) <- paste0("rule", seq_len(length(out)))
+  set_clean_class(out, new_class = c("custom_eucast_rules", "list"))
+}
+
+#' @method as.list custom_eucast_rules
+#' @noRd
+#' @export
+as.list.custom_eucast_rules <- function(x, ...) {
+  c(x, ...)
+}
+
+#' @method print custom_eucast_rules
+#' @export
+#' @noRd
+print.custom_eucast_rules <- function(x, ...) {
+  cat("A set of custom EUCAST rules:\n")
+  for (i in seq_len(length(x))) {
+    rule <- x[[i]]
+    rule$query <- format_custom_query_rule(rule$query)
+    if (rule$result_value == "R") {
+      val <- font_rsi_R_bg(font_black(" R "))
+    } else if (rule$result_value == "S") {
+      val <- font_rsi_S_bg(font_black(" S "))
+    } else {
+      val <- font_rsi_I_bg(font_black(" I "))
+    }
+    agents <- paste0(font_blue(ab_name(rule$result_group, language = NULL, tolower = TRUE),
+                               collapse = NULL),
+                     " (", rule$result_group, ")")
+    agents <- sort(agents)
+    rule_if <- word_wrap(paste0(i, ". ", font_bold("If "), font_blue(rule$query), font_bold(" then "),
+                            "set to {result}:"),
+                     extra_indent = 5)
+    rule_if <- gsub("{result}", val, rule_if, fixed = TRUE)
+    rule_then <- paste0("     ", word_wrap(paste0(agents, collapse = ", "), extra_indent = 5))
+    cat("\n  ", rule_if, "\n", rule_then, "\n", sep = "")
+  }
+}
+
+run_custom_eucast_rules <- function(df, rule, info) {
+  n_dots <- length(rule)
+  stop_if(n_dots == 0, "no custom rules set", call = -2)
+  out <- character(length = NROW(df))
+  reasons <- character(length = NROW(df))
+  for (i in seq_len(n_dots)) {
+    qry <- tryCatch(eval(parse(text = rule[[i]]$query), envir = df, enclos = parent.frame()),
+                    error = function(e) { 
+                      pkg_env$err_msg <- e$message
+                      return("error")
+                    })
+    if (identical(qry, "error")) {
+      warning_("in custom_eucast_rules(): rule ", i, 
+               " (`", as.character(rule[[i]]$query), "`) was ignored because of this error message: ",
+               pkg_env$err_msg,
+               call = FALSE, 
+               add_fn = font_red)
+      next
+    }
+    stop_ifnot(is.logical(qry), "in custom_eucast_rules(): rule ", i, " (`", rule[[i]]$query, 
+               "`) must return `TRUE` or `FALSE`, not ", 
+               format_class(class(qry), plural = FALSE), call = FALSE)
+    
+    new_eucasts <- which(qry == TRUE & out == "")
+    
+    if (info == TRUE) {
+      cat(word_wrap("- Custom EUCAST rule ", i, ": `", as.character(rule[[i]]$query),
+                    "` (", length(new_eucasts),  " rows matched)"), "\n", sep = "")
+    }
+    val <- rule[[i]]$value
+    out[new_eucasts] <- val
+    reasons[new_eucasts] <- paste0("matched rule ", gsub("rule", "", names(rule)[i]), ": ", as.character(rule[[i]]$query))
+  }
+  out[out == ""] <- "Negative"
+  reasons[out == "Negative"] <- "no rules matched"
+  
+  if (isTRUE(attributes(rule)$as_factor)) {
+    out <- factor(out, levels = attributes(rule)$values, ordered = TRUE)
+  }
+  
+  columns_nonsusceptible <- as.data.frame(t(df[, is.rsi(df)] == "R"))
+  columns_nonsusceptible <- vapply(FUN.VALUE = character(1), 
+                                   columns_nonsusceptible, 
+                                   function(x) paste0(rownames(columns_nonsusceptible)[which(x)], collapse = " "))
+  columns_nonsusceptible[is.na(out)] <- NA_character_
+  
+  data.frame(row_number = seq_len(NROW(df)),
+             EUCAST = out,
+             reason = reasons,
+             columns_nonsusceptible = columns_nonsusceptible,
+             stringsAsFactors = FALSE)
+}
+
+format_custom_query_rule <- function(query, colours = has_colour()) {
+  query <- gsub(" & ", font_black(font_bold(" and ")), query, fixed = TRUE)
+  query <- gsub(" | ", font_black(" or "), query, fixed = TRUE)
+  query <- gsub(" + ", font_black(" plus "), query, fixed = TRUE)
+  query <- gsub(" - ", font_black(" minus "), query, fixed = TRUE)
+  query <- gsub(" / ", font_black(" divided by "), query, fixed = TRUE)
+  query <- gsub(" * ", font_black(" times "), query, fixed = TRUE)
+  query <- gsub(" == ", font_black(" is "), query, fixed = TRUE)
+  query <- gsub(" > ", font_black(" is higher than "), query, fixed = TRUE)
+  query <- gsub(" < ", font_black(" is lower than "), query, fixed = TRUE)
+  query <- gsub(" >= ", font_black(" is higher than or equal to "), query, fixed = TRUE)
+  query <- gsub(" <= ", font_black(" is lower than or equal to "), query, fixed = TRUE)
+  query <- gsub(" ^ ", font_black(" to the power of "), query, fixed = TRUE)
+  query <- gsub(" %in% ", font_black(" is one of "), query, fixed = TRUE)
+  query <- gsub(" %like% ", font_black(" resembles "), query, fixed = TRUE)
+  if (colours == TRUE) {
+    query <- gsub('"R"', font_rsi_R_bg(font_black(" R ")), query, fixed = TRUE)
+    query <- gsub('"S"', font_rsi_S_bg(font_black(" S ")), query, fixed = TRUE)
+    query <- gsub('"I"', font_rsi_I_bg(font_black(" I ")), query, fixed = TRUE)
+  }
+  # replace the black colour 'stops' with blue colour 'starts'
+  query <- gsub("\033[39m", "\033[34m", as.character(query), fixed = TRUE)
+  # start with blue
+  query <- paste0("\033[34m", query)
+  if (colours == FALSE) {
+    query <- font_stripstyle(query)
+  }
+  query
+}
@@ -98,7 +98,7 @@
 #' @details 
 #' Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.
 #' 
-#' For example, *Staphylococcus pettenkoferi* was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (\doi{10.1016/s0732-8893(02)00399-1}), but it was not before 2007 that a publication in IJSEM followed (\doi{10.1099/ijs.0.64381-0}). Consequently, the AMR package returns 2007 for `mo_year("S. pettenkoferi")`.
+#' For example, *Staphylococcus pettenkoferi* was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (\doi{10.1016/s0732-8893(02)00399-1}), but it was not before 2007 that a publication in IJSEM followed (\doi{10.1099/ijs.0.64381-0}). Consequently, the `AMR` package returns 2007 for `mo_year("S. pettenkoferi")`.
 #' 
 #' ## Manual additions
 #' For convenience, some entries were added manually:
@@ -45,3 +45,71 @@ p_symbol <- function(p, emptychar = " ") {
  
  s
 }
+
+#' @name AMR-deprecated
+#' @export
+key_antibiotics <- function(x = NULL,
+                            col_mo = NULL,
+                            universal_1 = guess_ab_col(x, "amoxicillin"),
+                            universal_2 = guess_ab_col(x, "amoxicillin/clavulanic acid"),
+                            universal_3 = guess_ab_col(x, "cefuroxime"),
+                            universal_4 = guess_ab_col(x, "piperacillin/tazobactam"),
+                            universal_5 = guess_ab_col(x, "ciprofloxacin"),
+                            universal_6 = guess_ab_col(x, "trimethoprim/sulfamethoxazole"),
+                            GramPos_1 = guess_ab_col(x, "vancomycin"),
+                            GramPos_2 = guess_ab_col(x, "teicoplanin"),
+                            GramPos_3 = guess_ab_col(x, "tetracycline"),
+                            GramPos_4 = guess_ab_col(x, "erythromycin"),
+                            GramPos_5 = guess_ab_col(x, "oxacillin"),
+                            GramPos_6 = guess_ab_col(x, "rifampin"),
+                            GramNeg_1 = guess_ab_col(x, "gentamicin"),
+                            GramNeg_2 = guess_ab_col(x, "tobramycin"),
+                            GramNeg_3 = guess_ab_col(x, "colistin"),
+                            GramNeg_4 = guess_ab_col(x, "cefotaxime"),
+                            GramNeg_5 = guess_ab_col(x, "ceftazidime"),
+                            GramNeg_6 = guess_ab_col(x, "meropenem"),
+                            warnings = TRUE,
+                            ...) {
+  
+  .Deprecated(old = "key_antibiotics()",
+              new = "key_antimicrobials()",
+              package = "AMR")
+  
+  if (is_null_or_grouped_tbl(x)) {
+    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
+    # is also fix for using a grouped df as input (a dot as first argument)
+    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
+  }
+
+  key_antimicrobials(x = x, 
+                     col_mo = col_mo, 
+                     universal = c(universal_1, universal_2, universal_3, universal_4, universal_5, universal_6),
+                     gram_negative = c(GramNeg_1, GramNeg_2, GramNeg_3, GramNeg_4, GramNeg_5, GramNeg_6),
+                     gram_positive = c(GramPos_1, GramPos_2, GramPos_3, GramPos_4, GramPos_5, GramPos_6),
+                     antifungal = NULL,
+                     only_rsi_columns = FALSE,
+                     ...)
+}
+
+#' @name AMR-deprecated
+#' @export
+key_antibiotics_equal <- function(y,
+                                  z,
+                                  type = "keyantimicrobials",
+                                  ignore_I = TRUE,
+                                  points_threshold = 2,
+                                  info = FALSE,
+                                  na.rm = TRUE,
+                                  ...) {
+  
+  .Deprecated(old = "key_antibiotics_equal()",
+              new = "antimicrobials_equal()",
+              package = "AMR")
+  
+  antimicrobials_equal(y = y,
+                       z = z,
+                       type = type,
+                       ignore_I = ignore_I,
+                       points_threshold = points_threshold,
+                       info = info)
+}
@@ -28,7 +28,7 @@
 #' These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument `episode_days`. This can be used to determine clinical episodes for any epidemiological analysis. The [get_episode()] function returns the index number of the episode per group, while the [is_new_episode()] function returns values `TRUE`/`FALSE` to indicate whether an item in a vector is the start of a new episode.
 #' @inheritSection lifecycle Stable Lifecycle
 #' @param x vector of dates (class `Date` or `POSIXt`)
-#' @param episode_days required episode length in days, can also be less than a day, see *Details*
+#' @param episode_days required episode length in days, can also be less than a day or `Inf`, see *Details*
 #' @param ... currently not used
 #' @details 
 #' Dates are first sorted from old to new. The oldest date will mark the start of the first episode. After this date, the next date will be marked that is at least `episode_days` days later than the start of the first episode. From that second marked date on, the next date will be marked that is at least `episode_days` days later than the start of the second episode which will be the start of the third episode, and so on. Before the vector is being returned, the original order will be restored.
@@ -88,7 +88,8 @@
 #'   # grouping on patients and microorganisms leads to the same results
 #'   # as first_isolate():
 #'   x <- example_isolates %>%
-#'     filter(first_isolate(., include_unknown = TRUE))
+#'     filter_first_isolate(include_unknown = TRUE,
+#'                          method = "episode-based")
 #'     
 #'   y <- example_isolates %>%
 #'     group_by(patient_id, mo) %>%
@@ -105,7 +106,7 @@
 #' }
 get_episode <- function(x, episode_days, ...) {
  meet_criteria(x, allow_class = c("Date", "POSIXt"))
-  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
  
  exec_episode(type = "sequential",
               x = x, 
@@ -117,7 +118,7 @@ get_episode <- function(x, episode_days, ...) {
 #' @export
 is_new_episode <- function(x, episode_days, ...) {
  meet_criteria(x, allow_class = c("Date", "POSIXt"))
-  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
  
  exec_episode(type = "logical",
               x = x, 
@@ -51,7 +51,7 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
 #' @inheritSection lifecycle Stable Lifecycle
 #' @param x data with antibiotic columns, such as `amox`, `AMX` and `AMC`
 #' @param info a logical to indicate whether progress should be printed to the console, defaults to only print while in interactive sessions
-#' @param rules a character vector that specifies which rules should be applied. Must be one or more of `"breakpoints"`, `"expert"`, `"other"`, `"all"`, and defaults to `c("breakpoints", "expert")`. The default value can be set to another value, e.g. using `options(AMR_eucastrules = "all")`.
+#' @param rules a character vector that specifies which rules should be applied. Must be one or more of `"breakpoints"`, `"expert"`, `"other"`, `"custom"`, `"all"`, and defaults to `c("breakpoints", "expert")`. The default value can be set to another value, e.g. using `options(AMR_eucastrules = "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 either `r vector_or(names(EUCAST_VERSION_BREAKPOINTS), reverse = TRUE)`.
 #' @param version_expertrules the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be either `r vector_or(names(EUCAST_VERSION_EXPERT_RULES), reverse = TRUE)`.
@@ -60,12 +60,26 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
 #' @param ab any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
 #' @param administration route of administration, either `r vector_or(dosage$administration)`
 #' @param only_rsi_columns a logical to indicate whether only antibiotic columns must be detected that were transformed to class `<rsi>` (see [as.rsi()]) on beforehand (defaults to `FALSE`)
+#' @param custom_rules custom rules to apply, created with [custom_eucast_rules()]
 #' @inheritParams first_isolate
 #' @details
 #' **Note:** This function does not translate MIC values to RSI values. Use [as.rsi()] for that. \cr
-#' **Note:** When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance.
+#' **Note:** When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance. \cr
+
 #'
-#' The file containing all EUCAST rules is located here: <https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv>.
+#' The file containing all EUCAST rules is located here: <https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv>.  **Note:** Old taxonomic names are replaced with the current taxonomy where applicable. For example, *Ochrobactrum anthropi* was renamed to *Brucella anthropi* in 2020; the original EUCAST rules v3.1 and v3.2 did not yet contain this new taxonomic name. The file used as input for this `AMR` package contains the taxonomy updated until [`r CATALOGUE_OF_LIFE$yearmonth_LPSN`][catalogue_of_life()].
+#' 
+#' ## Custom Rules
+#' 
+#' Custom rules can be created using [custom_eucast_rules()], e.g.:
+#' 
+#' ```
+#' x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
+#'                          AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+#'
+#' eucast_rules(example_isolates, rules = "custom", custom_rules = x)
+#' ```
+#' 
 #' 
 #' ## 'Other' Rules
 #' 
@@ -149,19 +163,34 @@ eucast_rules <- function(x,
                         version_expertrules = 3.2,
                         ampc_cephalosporin_resistance = NA,
                         only_rsi_columns = FALSE,
+                         custom_rules = NULL,
                         ...) {
  meet_criteria(x, allow_class = "data.frame")
  meet_criteria(col_mo, allow_class = "character", has_length = 1, is_in = colnames(x), allow_NULL = TRUE)
  meet_criteria(info, allow_class = "logical", has_length = 1)
-  meet_criteria(rules, allow_class = "character", has_length = c(1, 2, 3, 4), is_in = c("breakpoints", "expert", "other", "all"))
+  meet_criteria(rules, allow_class = "character", has_length = c(1, 2, 3, 4, 5), is_in = c("breakpoints", "expert", "other", "all", "custom"))
  meet_criteria(verbose, allow_class = "logical", has_length = 1)
  meet_criteria(version_breakpoints, allow_class = c("numeric", "integer"), has_length = 1, is_in = as.double(names(EUCAST_VERSION_BREAKPOINTS)))
  meet_criteria(version_expertrules, allow_class = c("numeric", "integer"), has_length = 1, is_in = as.double(names(EUCAST_VERSION_EXPERT_RULES)))
  meet_criteria(ampc_cephalosporin_resistance, allow_class = c("logical", "character", "rsi"), has_length = 1, allow_NA = TRUE, allow_NULL = TRUE)
  meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
+  meet_criteria(custom_rules, allow_class = "custom_eucast_rules", allow_NULL = TRUE)
+  
+  if ("custom" %in% rules & is.null(custom_rules)) {
+    warning_("No custom rules were set with the `custom_rules` argument",
+             call = FALSE,
+             immediate = TRUE)
+    rules <- rules[rules != "custom"]
+    if (length(rules) == 0) {
+      if (info == TRUE) {
+        message_("No other rules were set, returning original data", add_fn = font_red, as_note = FALSE)
+      }
+      return(x)
+    }
+  }
  
  x_deparsed <- deparse(substitute(x))
-  if (length(x_deparsed) > 1 || !all(x_deparsed %like% "[a-z]+")) {
+  if (length(x_deparsed) > 1 || any(x_deparsed %unlike% "[a-z]+")) {
    x_deparsed <- "your_data"
  }
  
@@ -196,8 +225,6 @@ eucast_rules <- function(x,
  if (is.null(col_mo)) {
    col_mo <- search_type_in_df(x = x, type = "mo", info = info)
    stop_if(is.null(col_mo), "`col_mo` must be set")
-  } else {
-    stop_ifnot(col_mo %in% colnames(x), "column '", col_mo, "' (`col_mo`) not found")
  }
  
  decimal.mark <- getOption("OutDec")
@@ -263,238 +290,13 @@ eucast_rules <- function(x,
                            info = info,
                            only_rsi_columns = only_rsi_columns,
                            ...)
-
-  AMC <- cols_ab["AMC"]
-  AMK <- cols_ab["AMK"]
-  AMP <- cols_ab["AMP"]
-  AMX <- cols_ab["AMX"]
-  APL <- cols_ab["APL"]
-  APX <- cols_ab["APX"]
-  ATM <- cols_ab["ATM"]
-  AVB <- cols_ab["AVB"]
-  AVO <- cols_ab["AVO"]
-  AZD <- cols_ab["AZD"]
-  AZL <- cols_ab["AZL"]
-  AZM <- cols_ab["AZM"]
-  BAM <- cols_ab["BAM"]
-  BPR <- cols_ab["BPR"]
-  CAC <- cols_ab["CAC"]
-  CAT <- cols_ab["CAT"]
-  CAZ <- cols_ab["CAZ"]
-  CCP <- cols_ab["CCP"]
-  CCV <- cols_ab["CCV"]
-  CCX <- cols_ab["CCX"]
-  CDC <- cols_ab["CDC"]
-  CDR <- cols_ab["CDR"]
-  CDZ <- cols_ab["CDZ"]
-  CEC <- cols_ab["CEC"]
-  CED <- cols_ab["CED"]
-  CEI <- cols_ab["CEI"]
-  CEM <- cols_ab["CEM"]
-  CEP <- cols_ab["CEP"]
-  CFM <- cols_ab["CFM"]
-  CFM1 <- cols_ab["CFM1"]
-  CFP <- cols_ab["CFP"]
-  CFR <- cols_ab["CFR"]
-  CFS <- cols_ab["CFS"]
-  CFZ <- cols_ab["CFZ"]
-  CHE <- cols_ab["CHE"]
-  CHL <- cols_ab["CHL"]
-  CIC <- cols_ab["CIC"]
-  CID <- cols_ab["CID"]
-  CIP <- cols_ab["CIP"]
-  CLI <- cols_ab["CLI"]
-  CLM <- cols_ab["CLM"]
-  CLO <- cols_ab["CLO"]
-  CLR <- cols_ab["CLR"]
-  CMX <- cols_ab["CMX"]
-  CMZ <- cols_ab["CMZ"]
-  CND <- cols_ab["CND"]
-  COL <- cols_ab["COL"]
-  CPD <- cols_ab["CPD"]
-  CPI <- cols_ab["CPI"]
-  CPL <- cols_ab["CPL"]
-  CPM <- cols_ab["CPM"]
-  CPO <- cols_ab["CPO"]
-  CPR <- cols_ab["CPR"]
-  CPT <- cols_ab["CPT"]
-  CPX <- cols_ab["CPX"]
-  CRB <- cols_ab["CRB"]
-  CRD <- cols_ab["CRD"]
-  CRN <- cols_ab["CRN"]
-  CRO <- cols_ab["CRO"]
-  CSL <- cols_ab["CSL"]
-  CTB <- cols_ab["CTB"]
-  CTC <- cols_ab["CTC"]
-  CTF <- cols_ab["CTF"]
-  CTL <- cols_ab["CTL"]
-  CTS <- cols_ab["CTS"]
-  CTT <- cols_ab["CTT"]
-  CTX <- cols_ab["CTX"]
-  CTZ <- cols_ab["CTZ"]
-  CXM <- cols_ab["CXM"]
-  CYC <- cols_ab["CYC"]
-  CZA <- cols_ab["CZA"]
-  CZD <- cols_ab["CZD"]
-  CZO <- cols_ab["CZO"]
-  CZP <- cols_ab["CZP"]
-  CZX <- cols_ab["CZX"]
-  DAL <- cols_ab["DAL"]
-  DAP <- cols_ab["DAP"]
-  DIC <- cols_ab["DIC"]
-  DIR <- cols_ab["DIR"]
-  DIT <- cols_ab["DIT"]
-  DIX <- cols_ab["DIX"]
-  DIZ <- cols_ab["DIZ"]
-  DKB <- cols_ab["DKB"]
-  DOR <- cols_ab["DOR"]
-  DOX <- cols_ab["DOX"]
-  ENX <- cols_ab["ENX"]
-  EPC <- cols_ab["EPC"]
-  ERY <- cols_ab["ERY"]
-  ETP <- cols_ab["ETP"]
-  FEP <- cols_ab["FEP"]
-  FLC <- cols_ab["FLC"]
-  FLE <- cols_ab["FLE"]
-  FLR1 <- cols_ab["FLR1"]
-  FOS <- cols_ab["FOS"]
-  FOV <- cols_ab["FOV"]
-  FOX <- cols_ab["FOX"]
-  FOX1 <- cols_ab["FOX1"]
-  FUS <- cols_ab["FUS"]
-  GAT <- cols_ab["GAT"]
-  GEM <- cols_ab["GEM"]
-  GEN <- cols_ab["GEN"]
-  GRX <- cols_ab["GRX"]
-  HAP <- cols_ab["HAP"]
-  HET <- cols_ab["HET"]
-  IPM <- cols_ab["IPM"]
-  ISE <- cols_ab["ISE"]
-  JOS <- cols_ab["JOS"]
-  KAN <- cols_ab["KAN"]
-  LEN <- cols_ab["LEN"]
-  LEX <- cols_ab["LEX"]
-  LIN <- cols_ab["LIN"]
-  LNZ <- cols_ab["LNZ"]
-  LOM <- cols_ab["LOM"]
-  LOR <- cols_ab["LOR"]
-  LTM <- cols_ab["LTM"]
-  LVX <- cols_ab["LVX"]
-  MAN <- cols_ab["MAN"]
-  MCM <- cols_ab["MCM"]
-  MEC <- cols_ab["MEC"]
-  MEM <- cols_ab["MEM"]
-  MET <- cols_ab["MET"]
-  MEV <- cols_ab["MEV"]
-  MEZ <- cols_ab["MEZ"]
-  MFX <- cols_ab["MFX"]
-  MID <- cols_ab["MID"]
-  MNO <- cols_ab["MNO"]
-  MTM <- cols_ab["MTM"]
-  NAC <- cols_ab["NAC"]
-  NAF <- cols_ab["NAF"]
-  NAL <- cols_ab["NAL"]
-  NEO <- cols_ab["NEO"]
-  NET <- cols_ab["NET"]
-  NIT <- cols_ab["NIT"]
-  NOR <- cols_ab["NOR"]
-  NOV <- cols_ab["NOV"]
-  NVA <- cols_ab["NVA"]
-  OFX <- cols_ab["OFX"]
-  OLE <- cols_ab["OLE"]
-  ORI <- cols_ab["ORI"]
-  OXA <- cols_ab["OXA"]
-  PAZ <- cols_ab["PAZ"]
-  PEF <- cols_ab["PEF"]
-  PEN <- cols_ab["PEN"]
-  PHE <- cols_ab["PHE"]
-  PHN <- cols_ab["PHN"]
-  PIP <- cols_ab["PIP"]
-  PLB <- cols_ab["PLB"]
-  PME <- cols_ab["PME"]
-  PNM <- cols_ab["PNM"]
-  PRC <- cols_ab["PRC"]
-  PRI <- cols_ab["PRI"]
-  PRL <- cols_ab["PRL"]
-  PRP <- cols_ab["PRP"]
-  PRU <- cols_ab["PRU"]
-  PVM <- cols_ab["PVM"]
-  QDA <- cols_ab["QDA"]
-  RAM <- cols_ab["RAM"]
-  RFL <- cols_ab["RFL"]
-  RID <- cols_ab["RID"]
-  RIF <- cols_ab["RIF"]
-  ROK <- cols_ab["ROK"]
-  RST <- cols_ab["RST"]
-  RXT <- cols_ab["RXT"]
-  SAM <- cols_ab["SAM"]
-  SBC <- cols_ab["SBC"]
-  SDI <- cols_ab["SDI"]
-  SDM <- cols_ab["SDM"]
-  SIS <- cols_ab["SIS"]
-  SLF <- cols_ab["SLF"]
-  SLF1 <- cols_ab["SLF1"]
-  SLF10 <- cols_ab["SLF10"]
-  SLF11 <- cols_ab["SLF11"]
-  SLF12 <- cols_ab["SLF12"]
-  SLF13 <- cols_ab["SLF13"]
-  SLF2 <- cols_ab["SLF2"]
-  SLF3 <- cols_ab["SLF3"]
-  SLF4 <- cols_ab["SLF4"]
-  SLF5 <- cols_ab["SLF5"]
-  SLF6 <- cols_ab["SLF6"]
-  SLF7 <- cols_ab["SLF7"]
-  SLF8 <- cols_ab["SLF8"]
-  SLF9 <- cols_ab["SLF9"]
-  SLT1 <- cols_ab["SLT1"]
-  SLT2 <- cols_ab["SLT2"]
-  SLT3 <- cols_ab["SLT3"]
-  SLT4 <- cols_ab["SLT4"]
-  SLT5 <- cols_ab["SLT5"]
-  SLT6 <- cols_ab["SLT6"]
-  SMX <- cols_ab["SMX"]
-  SPI <- cols_ab["SPI"]
-  SPX <- cols_ab["SPX"]
-  SRX <- cols_ab["SRX"]
-  STR <- cols_ab["STR"]
-  STR1 <- cols_ab["STR1"]
-  SUD <- cols_ab["SUD"]
-  SUL <- cols_ab["SUL"]
-  SUT <- cols_ab["SUT"]
-  SXT <- cols_ab["SXT"]
-  SZO <- cols_ab["SZO"]
-  TAL <- cols_ab["TAL"]
-  TAZ <- cols_ab["TAZ"]
-  TCC <- cols_ab["TCC"]
-  TCM <- cols_ab["TCM"]
-  TCY <- cols_ab["TCY"]
-  TEC <- cols_ab["TEC"]
-  TEM <- cols_ab["TEM"]
-  TGC <- cols_ab["TGC"]
-  THA <- cols_ab["THA"]
-  TIC <- cols_ab["TIC"]
-  TIO <- cols_ab["TIO"]
-  TLT <- cols_ab["TLT"]
-  TLV <- cols_ab["TLV"]
-  TMP <- cols_ab["TMP"]
-  TMX <- cols_ab["TMX"]
-  TOB <- cols_ab["TOB"]
-  TRL <- cols_ab["TRL"]
-  TVA <- cols_ab["TVA"]
-  TZD <- cols_ab["TZD"]
-  TZP <- cols_ab["TZP"]
-  VAN <- cols_ab["VAN"]
  
-  ab_missing <- function(ab) {
-    all(ab %in% c(NULL, NA))
-  }
-  
-  if (ab_missing(AMP) & !ab_missing(AMX)) {
+  if (!"AMP" %in% names(cols_ab) & "AMX" %in% names(cols_ab)) {
    # ampicillin column is missing, but amoxicillin is available
    if (info == TRUE) {
-      message_("Using column '", font_bold(AMX), "' as input for ampicillin since many EUCAST rules depend on it.")
+      message_("Using column '", cols_ab[names(cols_ab) == "AMX"], "' as input for ampicillin since many EUCAST rules depend on it.")
    }
-    AMP <- AMX
+    cols_ab <- c(cols_ab, c(AMP = unname(cols_ab[names(cols_ab) == "AMX"])))
  }
  
  # data preparation ----
@@ -502,40 +304,23 @@ eucast_rules <- function(x,
    message_("Preparing data...", appendLF = FALSE, as_note = FALSE)
  }
  
-  # nolint start
-  # antibiotic classes ----
-  aminoglycosides <- c(AMK, DKB, GEN, ISE, KAN, NEO, NET, RST, SIS, STR, STR1, TOB)
-  aminopenicillins <- c(AMP, AMX)
-  carbapenems <- c(DOR, ETP, IPM, MEM, MEV)
-  cephalosporins <- c(CDZ, CCP, CAC, CEC, CFR, RID, MAN, CTZ, CZD, CZO, CDR, DIT, FEP, CAT, CFM, CMX, CMZ, DIZ, CID, CFP, CSL, CND, CTX, CTT, CTF, FOX, CPM, CPO, CPD, CPR, CRD, CFS, CPT, CAZ, CCV, CTL, CTB, CZX, BPR, CFM1, CEI, CRO, CXM, LEX, CEP, HAP, CED, LTM, LOR)
-  cephalosporins_1st <- c(CAC, CFR, RID, CTZ, CZD, CZO, CRD, CTL, LEX, CEP, HAP, CED)
-  cephalosporins_2nd <- c(CEC, MAN, CMZ, CID, CND, CTT, CTF, FOX, CPR, CXM, LOR)
-  cephalosporins_3rd <- c(CDZ, CCP, CCX, CDR, DIT, DIX, CAT, CPI, CFM, CMX, DIZ, CFP, CSL, CTX, CTC, CTS, CHE, FOV, CFZ, CPM, CPD, CPX, CDC, CFS, CAZ, CZA, CCV, CEM, CPL, CTB, TIO, CZX, CZP, CRO, LTM)
-  cephalosporins_except_CAZ <- cephalosporins[cephalosporins != ifelse(is.null(CAZ), "", CAZ)]
-  fluoroquinolones <- c(CIP, ENX, FLE, GAT, GEM, GRX, LVX, LOM, MFX, NOR, OFX, PAZ, PEF, PRU, RFL, SPX, TMX, TVA)
-  glycopeptides <- c(AVO, NVA, RAM, TEC, TCM, VAN) # dalba/orita/tela are in lipoglycopeptides
-  lincosamides <- c(CLI, LIN, PRL)
-  lipoglycopeptides <- c(DAL, ORI, TLV)
-  macrolides <- c(AZM, CLR, DIR, ERY, FLR1, JOS, MID, MCM, OLE, ROK, RXT, SPI, TLT, TRL)
-  oxazolidinones <- c(CYC, LNZ, THA, TZD)
-  polymyxins <- c(PLB, COL)
-  streptogramins <- c(QDA, PRI)
-  tetracyclines <- c(DOX, MNO, TCY) # since EUCAST v3.1 tigecycline (TGC) is set apart
-  ureidopenicillins <- c(PIP, TZP, AZL, MEZ)
-  all_betalactams <- c(aminopenicillins, cephalosporins, carbapenems, ureidopenicillins, AMC, OXA, FLC, PEN)
-  # nolint end
-  
  # Some helper functions ---------------------------------------------------
-  get_antibiotic_columns <- function(x, df) {
-    x <- trimws(unlist(strsplit(x, ",", fixed = TRUE)))
-    y <- character(0)
-    for (i in seq_len(length(x))) {
-      if (is.function(get(x[i]))) {
-        stop("Column ", x[i], " is also a function. Please create an issue on github.com/msberends/AMR/issues.")
+  get_antibiotic_columns <- function(x, cols_ab) {
+    x <- strsplit(x, ", *")[[1]]
+    x_new <- character()
+    for (val in x) {
+      if (toupper(val) %in% ls(envir = asNamespace("AMR"))) {
+        # antibiotic group names, as defined in data-raw/_internals.R, such as `CARBAPENEMS`
+        val <- eval(parse(text = toupper(val)), envir = asNamespace("AMR"))
+      } else if (toupper(val) %in% AB_lookup$ab) {
+        # separate drugs, such as `AMX`
+        val <- as.ab(val)
+      } else {
+        stop_("antimicrobial agent (group) not found in EUCAST rules file: ", val, call = FALSE)
      }
-      y <- c(y, tryCatch(get(x[i]), error = function(e) ""))
+      x_new <- c(x_new, val)
    }
-    y[y != "" & y %in% colnames(df)]
+    cols_ab[match(x_new, names(cols_ab))]
  }
  markup_italics_where_needed <- function(x) {
    # returns names found in family, genus or species as italics
@@ -553,7 +338,7 @@ eucast_rules <- function(x,
      strsplit(",") %pm>%
      unlist() %pm>%
      trimws() %pm>%
-      vapply(FUN.VALUE = character(1), function(x) if (x %in% antibiotics$ab) ab_name(x, language = NULL, tolower = TRUE) else x) %pm>%
+      vapply(FUN.VALUE = character(1), function(x) if (x %in% antibiotics$ab) ab_name(x, language = NULL, tolower = TRUE, fast_mode = TRUE) else x) %pm>%
      sort() %pm>%
      paste(collapse = ", ")
    x <- gsub("_", " ", x, fixed = TRUE)
@@ -633,8 +418,11 @@ eucast_rules <- function(x,
    pm_distinct(`.rowid`, .keep_all = TRUE) %pm>% 
    as.data.frame(stringsAsFactors = FALSE)
  x[, col_mo] <- as.mo(as.character(x[, col_mo, drop = TRUE]))
-  x <- x %pm>%
-    left_join_microorganisms(by = col_mo, suffix = c("_oldcols", ""))
+  # rename col_mo to prevent interference with joined columns
+  colnames(x)[colnames(x) == col_mo] <- ".col_mo"
+  col_mo <- ".col_mo"
+  # join to microorganisms data set
+  x <- left_join_microorganisms(x, by = col_mo, suffix = c("_oldcols", ""))
  x$gramstain <- mo_gramstain(x[, col_mo, drop = TRUE], language = NULL)
  x$genus_species <- paste(x$genus, x$species)
  if (info == TRUE & NROW(x) > 10000) {
@@ -662,33 +450,47 @@ eucast_rules <- function(x,
                         font_red(paste0("v", utils::packageDescription("AMR")$Version, ", ", 
                                         format(as.Date(utils::packageDescription("AMR")$Date), format = "%Y"))), "), see ?eucast_rules\n"))))
    }
-    
    ab_enzyme <- subset(antibiotics, name %like% "/")[, c("ab", "name")]
-    ab_enzyme$base_name <- gsub("^([a-zA-Z0-9]+).*", "\\1", ab_enzyme$name)
-    ab_enzyme$base_ab <- as.ab(ab_enzyme$base_name)
+    colnames(ab_enzyme) <- c("enzyme_ab", "enzyme_name")
+    ab_enzyme$base_name <- gsub("^([a-zA-Z0-9]+).*", "\\1", ab_enzyme$enzyme_name)
+    ab_enzyme$base_ab <- antibiotics[match(ab_enzyme$base_name, antibiotics$name), "ab", drop = TRUE]
+    ab_enzyme <- subset(ab_enzyme, !is.na(base_ab))
+    # make ampicillin and amoxicillin interchangable
+    ampi <- subset(ab_enzyme, base_ab == "AMX")
+    ampi$base_ab <- "AMP"
+    ampi$base_name <- ab_name("AMP", language = NULL)
+    amox <- subset(ab_enzyme, base_ab == "AMP")
+    amox$base_ab <- "AMX"
+    amox$base_name <- ab_name("AMX", language = NULL)
+    # merge and sort
+    ab_enzyme <- rbind(ab_enzyme, ampi, amox)
+    ab_enzyme <- ab_enzyme[order(ab_enzyme$enzyme_name), ]
+    
    for (i in seq_len(nrow(ab_enzyme))) {
-      if (all(c(ab_enzyme[i, ]$ab, ab_enzyme[i, ]$base_ab) %in% names(cols_ab), na.rm = TRUE)) {
-        ab_name_base <- ab_name(cols_ab[ab_enzyme[i, ]$base_ab], language = NULL, tolower = TRUE)
-        ab_name_enzyme <- ab_name(cols_ab[ab_enzyme[i, ]$ab], language = NULL, tolower = TRUE)
+      # check if both base and base + enzyme inhibitor are part of the data set
+      if (all(c(ab_enzyme$base_ab[i], ab_enzyme$enzyme_ab[i]) %in% names(cols_ab), na.rm = TRUE)) {
+        col_base <- unname(cols_ab[ab_enzyme$base_ab[i]])
+        col_enzyme <- unname(cols_ab[ab_enzyme$enzyme_ab[i]])
        
        # Set base to R where base + enzyme inhibitor is R ----
-        rule_current <- paste0("Set ", ab_name_base, " (", cols_ab[ab_enzyme[i, ]$base_ab], ") = R where ",
-                               ab_name_enzyme, " (", cols_ab[ab_enzyme[i, ]$ab], ") = R")
+        rule_current <- paste0(ab_enzyme$base_name[i], " ('", font_bold(col_base), "') = R if ",
+                               tolower(ab_enzyme$enzyme_name[i]), " ('", font_bold(col_enzyme), "') = R")
        if (info == TRUE) {
-          cat(word_wrap(rule_current))
-          cat("\n")
+          cat(word_wrap(rule_current, 
+                        width = getOption("width") - 30,
+                        extra_indent = 6))
        }
        run_changes <- edit_rsi(x = x,
-                                col_mo = col_mo,
                                to = "R",
                                rule = c(rule_current, "Other rules", "",
                                         paste0("Non-EUCAST: AMR package v", utils::packageDescription("AMR")$Version)),
-                                rows = which(as.rsi_no_warning(x[, cols_ab[ab_enzyme[i, ]$ab]]) == "R"),
-                                cols = cols_ab[ab_enzyme[i, ]$base_ab],
+                                rows = which(as.rsi_no_warning(x[, col_enzyme, drop = TRUE]) == "R"),
+                                cols = col_base,
                                last_verbose_info = verbose_info,
                                original_data = x.bak,
                                warned = warned,
-                                info = info)
+                                info = info,
+                                verbose = verbose)
        n_added <- n_added + run_changes$added
        n_changed <- n_changed + run_changes$changed
        verbose_info <- run_changes$verbose_info
@@ -704,23 +506,25 @@ eucast_rules <- function(x,
        }
        
        # Set base + enzyme inhibitor to S where base is S ----
-        rule_current <- paste0("Set ", ab_name_enzyme, " (", cols_ab[ab_enzyme[i, ]$ab], ") = S where ",
-                               ab_name_base, " (", cols_ab[ab_enzyme[i, ]$base_ab], ") = S")
+        rule_current <- paste0(ab_enzyme$enzyme_name[i], " ('", font_bold(col_enzyme), "') = S if ",
+                               tolower(ab_enzyme$base_name[i]), " ('", font_bold(col_base), "') = S")
+
        if (info == TRUE) {
-          cat(word_wrap(rule_current))
-          cat("\n")
+          cat(word_wrap(rule_current, 
+                        width = getOption("width") - 30,
+                        extra_indent = 6))
        }
        run_changes <- edit_rsi(x = x,
-                                col_mo = col_mo,
                                to = "S",
                                rule = c(rule_current, "Other rules", "", 
                                         paste0("Non-EUCAST: AMR package v", utils::packageDescription("AMR")$Version)),
-                                rows = which(as.rsi_no_warning(x[, cols_ab[ab_enzyme[i, ]$base_ab]]) == "S"),
-                                cols = cols_ab[ab_enzyme[i, ]$ab],
+                                rows = which(as.rsi_no_warning(x[, col_base, drop = TRUE]) == "S"),
+                                cols = col_enzyme,
                                last_verbose_info = verbose_info,
                                original_data = x.bak,
                                warned = warned,
-                                info = info)
+                                info = info,
+                                verbose = verbose)
        n_added <- n_added + run_changes$added
        n_changed <- n_changed + run_changes$changed
        verbose_info <- run_changes$verbose_info
@@ -740,10 +544,17 @@ eucast_rules <- function(x,
  } else {
    if (info == TRUE) {
      cat("\n")
-      message_("Skipping inheritance rules defined by this package, such as setting trimethoprim (TMP) = R where trimethoprim/sulfamethoxazole (SXT) = R. Use `eucast_rules(..., rules = \"all\")` to also apply those rules.")
+      message_("Skipping inheritance rules defined by this AMR package, such as setting trimethoprim (TMP) = R where trimethoprim/sulfamethoxazole (SXT) = R. Add \"other\" or \"all\" to the `rules` argument to apply those rules.")
    }
  }
  
+  if (!any(c("all", "custom") %in% rules) & !is.null(custom_rules)) {
+    if (info == TRUE) {
+      message_("Skipping custom EUCAST rules, since the `rules` argument does not contain \"custom\".")
+    }
+    custom_rules <- NULL
+  }
+  
  # Official EUCAST rules ---------------------------------------------------
  eucast_notification_shown <- FALSE
  if (!is.null(list(...)$eucast_rules_df)) {
@@ -757,19 +568,19 @@ eucast_rules <- function(x,
  # filter on user-set guideline versions ----
  if (any(c("all", "breakpoints") %in% rules)) {
    eucast_rules_df <- subset(eucast_rules_df,
-                              !reference.rule_group %like% "breakpoint" |
+                              reference.rule_group %unlike% "breakpoint" |
                                (reference.rule_group %like% "breakpoint" & reference.version == version_breakpoints))
  }
  if (any(c("all", "expert") %in% rules)) {
    eucast_rules_df <- subset(eucast_rules_df,
-                              !reference.rule_group %like% "expert" |
+                              reference.rule_group %unlike% "expert" |
                                (reference.rule_group %like% "expert" & reference.version == version_expertrules))
  }
  # filter out AmpC de-repressed cephalosporin-resistant mutants ----
  # cefotaxime, ceftriaxone, ceftazidime
  if (is.null(ampc_cephalosporin_resistance) || isFALSE(ampc_cephalosporin_resistance)) {
    eucast_rules_df <- subset(eucast_rules_df,
-                              !reference.rule %like% "ampc")
+                              reference.rule %unlike% "ampc")
  } else {
    if (isTRUE(ampc_cephalosporin_resistance)) {
      ampc_cephalosporin_resistance <- "R"
@@ -777,6 +588,7 @@ eucast_rules <- function(x,
    eucast_rules_df[which(eucast_rules_df$reference.rule %like% "ampc"), "to_value"] <- as.character(ampc_cephalosporin_resistance)
  }
  
+  # Go over all rules and apply them ----
  for (i in seq_len(nrow(eucast_rules_df))) {
    
    rule_previous <- eucast_rules_df[max(1, i - 1), "reference.rule", drop = TRUE]
@@ -784,6 +596,14 @@ eucast_rules <- function(x,
    rule_next <- eucast_rules_df[min(nrow(eucast_rules_df), i + 1), "reference.rule", drop = TRUE]
    rule_group_previous <- eucast_rules_df[max(1, i - 1), "reference.rule_group", drop = TRUE]
    rule_group_current <- eucast_rules_df[i, "reference.rule_group", drop = TRUE]
+    # don't apply rules if user doesn't want to apply them
+    if (rule_group_current %like% "breakpoint" & !any(c("all", "breakpoints") %in% rules)) {
+      next
+    }
+    if (rule_group_current %like% "expert" & !any(c("all", "expert") %in% rules)) {
+      next
+    }
+    
    if (isFALSE(info) | isFALSE(verbose)) {
      rule_text <- ""
    } else {
@@ -804,17 +624,9 @@ eucast_rules <- function(x,
      rule_next <- ""
    }
    
-    # don't apply rules if user doesn't want to apply them
-    if (rule_group_current %like% "breakpoint" & !any(c("all", "breakpoints") %in% rules)) {
-      next
-    }
-    if (rule_group_current %like% "expert" & !any(c("all", "expert") %in% rules)) {
-      next
-    }
-    
    if (info == TRUE) {
      # Print EUCAST intro ------------------------------------------------------
-      if (!rule_group_current %like% "other" & eucast_notification_shown == FALSE) {
+      if (rule_group_current %unlike% "other" & eucast_notification_shown == FALSE) {
        cat(
          paste0("\n", font_grey(strrep("-", 0.95 * options()$width)), "\n",
                 word_wrap("Rules by the ", font_bold("European Committee on Antimicrobial Susceptibility Testing (EUCAST)")), "\n", 
@@ -899,26 +711,26 @@ eucast_rules <- function(x,
    source_value <- trimws(unlist(strsplit(eucast_rules_df[i, "have_these_values", drop = TRUE], ",", fixed = TRUE)))
    target_antibiotics <- eucast_rules_df[i, "then_change_these_antibiotics", drop = TRUE]
    target_value <- eucast_rules_df[i, "to_value", drop = TRUE]
-    
+
    if (is.na(source_antibiotics)) {
      rows <- tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value),
                       error = function(e) integer(0))
    } else {
-      source_antibiotics <- get_antibiotic_columns(source_antibiotics, x)
+      source_antibiotics <- get_antibiotic_columns(source_antibiotics, cols_ab)
      if (length(source_value) == 1 & length(source_antibiotics) > 1) {
        source_value <- rep(source_value, length(source_antibiotics))
      }
      if (length(source_antibiotics) == 0) {
        rows <- integer(0)
      } else if (length(source_antibiotics) == 1) {
-        rows <-  tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
-                                & as.rsi_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]),
-                          error = function(e) integer(0))
+        rows <- tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
+                               & as.rsi_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]),
+                         error = function(e) integer(0))
      } else if (length(source_antibiotics) == 2) {
-        rows <-  tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
-                                & as.rsi_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]
-                                & as.rsi_no_warning(x[, source_antibiotics[2L]]) == source_value[2L]),
-                          error = function(e) integer(0))
+        rows <- tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
+                               & as.rsi_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]
+                               & as.rsi_no_warning(x[, source_antibiotics[2L]]) == source_value[2L]),
+                         error = function(e) integer(0))
        # nolint start
      # } else if (length(source_antibiotics) == 3) {
      #   rows <-  tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value
@@ -932,12 +744,11 @@ eucast_rules <- function(x,
      }
    }
    
-    cols <- get_antibiotic_columns(target_antibiotics, x)
+    cols <- get_antibiotic_columns(target_antibiotics, cols_ab)
    
    # Apply rule on data ------------------------------------------------------
    # this will return the unique number of changes
    run_changes <- edit_rsi(x = x,
-                            col_mo = col_mo,
                            to = target_value,
                            rule = c(rule_text, rule_group_current, rule_current, 
                                     ifelse(rule_group_current %like% "breakpoint",
@@ -948,7 +759,8 @@ eucast_rules <- function(x,
                            last_verbose_info = verbose_info,
                            original_data = x.bak,
                            warned = warned,
-                            info = info)
+                            info = info,
+                            verbose = verbose)
    n_added <- n_added + run_changes$added
    n_changed <- n_changed + run_changes$changed
    verbose_info <- run_changes$verbose_info
@@ -962,6 +774,60 @@ eucast_rules <- function(x,
      n_added <- 0
      n_changed <- 0
    }
+  } # end of going over all rules
+
+  # Apply custom rules ----
+  if (!is.null(custom_rules)) {
+    if (info == TRUE) {
+      cat("\n")
+      cat(font_bold("Custom EUCAST rules, set by user"), "\n")
+    }
+    for (i in seq_len(length(custom_rules))) {
+      rule <- custom_rules[[i]]
+      rows <- which(eval(parse(text = rule$query), envir = x))
+      cols <- as.character(rule$result_group)
+      cols <- c(cols[cols %in% colnames(x)],               # direct column names
+                unname(cols_ab[names(cols_ab) %in% cols])) # based on previous cols_ab finding
+      cols <- unique(cols)
+      target_value <- as.character(rule$result_value)
+      rule_text <- paste0("report as '", target_value, "' when ",
+                          format_custom_query_rule(rule$query, colours = FALSE), ": ",
+                          get_antibiotic_names(cols))
+      if (info == TRUE) {
+        # print rule
+        cat(markup_italics_where_needed(word_wrap(format_custom_query_rule(rule$query, colours = FALSE), 
+                                                  width = getOption("width") - 30,
+                                                  extra_indent = 6)))
+        warned <- FALSE
+      }
+      run_changes <- edit_rsi(x = x,
+                              to = target_value,
+                              rule = c(rule_text, 
+                                       "Custom EUCAST rules",
+                                       paste0("Custom EUCAST rule ", i),
+                                       paste0("Object '", deparse(substitute(custom_rules)), 
+                                              "' consisting of ", length(custom_rules), " custom rules")),
+                              rows = rows,
+                              cols = cols,
+                              last_verbose_info = verbose_info,
+                              original_data = x.bak,
+                              warned = warned,
+                              info = info,
+                              verbose = verbose)
+      n_added <- n_added + run_changes$added
+      n_changed <- n_changed + run_changes$changed
+      verbose_info <- run_changes$verbose_info
+      x <- run_changes$output
+      warn_lacking_rsi_class <- c(warn_lacking_rsi_class, run_changes$rsi_warn)
+      # Print number of new changes ---------------------------------------------
+      if (info == TRUE & rule_next != rule_current) {
+        # print only on last one of rules in this group
+        txt_ok(n_added = n_added, n_changed = n_changed, warned = warned)
+        # and reset counters
+        n_added <- 0
+        n_changed <- 0
+      }
+    }
  }
  
  # Print overview ----------------------------------------------------------
@@ -1080,16 +946,16 @@ eucast_rules <- function(x,
 }

 # helper function for editing the table ----
-edit_rsi <- function(x, 
-                     col_mo,
-                     to, 
-                     rule, 
+edit_rsi <- function(x,
+                     to,
+                     rule,
                     rows,
                     cols,
-                     last_verbose_info, 
+                     last_verbose_info,
                     original_data,
                     warned,
-                     info) {
+                     info,
+                     verbose) {
  cols <- unique(cols[!is.na(cols) & !is.null(cols)])
  
  # for Verbose Mode, keep track of all changes and return them
@@ -1146,7 +1012,7 @@ edit_rsi <- function(x,
    )
    
    track_changes$output <- new_edits
-    if (isTRUE(info) && !isTRUE(all.equal(x, track_changes$output))) {
+    if ((info == TRUE | verbose == TRUE) && !isTRUE(all.equal(x, track_changes$output))) {
      get_original_rows <- function(rowids) {
        as.integer(rownames(original_data[which(original_data$.rowid %in% rowids), , drop = FALSE]))
      }
@@ -425,7 +425,7 @@ find_ab_group <- function(ab_class) {

 find_ab_names <- function(ab_group, n = 3) {
  ab_group <- gsub("[^a-zA-Z0-9]", ".*", ab_group)
-  drugs <- antibiotics[which(antibiotics$group %like% ab_group & !antibiotics$ab %like% "[0-9]$"), ]$name
+  drugs <- antibiotics[which(antibiotics$group %like% ab_group & antibiotics$ab %unlike% "[0-9]$"), ]$name
  paste0(sort(ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE),
                      tolower = TRUE, language = NULL)), 
         collapse = ", ")
@@ -34,62 +34,91 @@
 #' @param col_testcode column name of the test codes. Use `col_testcode = NULL` to **not** exclude certain test codes (such as test codes for screening). In that case `testcodes_exclude` will be ignored.
 #' @param col_specimen column name of the specimen type or group
 #' @param col_icu column name of the logicals (`TRUE`/`FALSE`) whether a ward or department is an Intensive Care Unit (ICU)
-#' @param col_keyantibiotics column name of the key antibiotics to determine first (weighted) isolates, see [key_antibiotics()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use `col_keyantibiotics = FALSE` to prevent this.
+#' @param col_keyantimicrobials (only useful when `method = "phenotype-based"`) column name of the key antimicrobials to determine first (weighted) isolates, see [key_antimicrobials()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use `col_keyantimicrobials = FALSE` to prevent this. Can also be the output of [key_antimicrobials()].
 #' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see *Source*. 
 #' @param testcodes_exclude character vector with test codes that should be excluded (case-insensitive)
 #' @param icu_exclude logical to indicate whether ICU isolates should be excluded (rows with value `TRUE` in the column set with `col_icu`)
 #' @param specimen_group value in the column set with `col_specimen` to filter on
-#' @param type type to determine weighed isolates; can be `"keyantibiotics"` or `"points"`, see *Details*
-#' @param ignore_I logical to indicate whether antibiotic interpretations with `"I"` will be ignored when `type = "keyantibiotics"`, see *Details*
-#' @param points_threshold points until the comparison of key antibiotics will lead to inclusion of an isolate when `type = "points"`, see *Details*
-#' @param info print progress
+#' @param type type to determine weighed isolates; can be `"keyantimicrobials"` or `"points"`, see *Details*
+#' @param method the algorithm to apply, either `"phenotype-based"`, `"episode-based"`, `"patient-based"` or `"isolate-based"` (can be abbreviated), see *Details*
+#' @param ignore_I logical to indicate whether antibiotic interpretations with `"I"` will be ignored when `type = "keyantimicrobials"`, see *Details*
+#' @param points_threshold minimum number of points to require before differences in the antibiogram will lead to inclusion of an isolate when `type = "points"`, see *Details*
+#' @param info a [logical] to indicate info should be printed, defaults to `TRUE` only in interactive mode
 #' @param include_unknown logical to indicate whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
 #' @param include_untested_rsi logical to indicate whether also rows without antibiotic results are still eligible for becoming a first isolate. Use `include_untested_rsi = FALSE` to always return `FALSE` for such rows. This checks the data set for columns of class `<rsi>` and consequently requires transforming columns with antibiotic results using [as.rsi()] first.
-#' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], or arguments passed on to [key_antibiotics()] when using [filter_first_weighted_isolate()]
+#' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], or arguments passed on to [key_antimicrobials()] otherwise (such as `universal`, `gram_negative`, `gram_positive`)
 #' @details 
+#' To conduct epidemiological analyses on antimicrobial resistance data, only so-called first isolates should be included to prevent overestimation and underestimation of antimicrobial resistance. Different algorithms can be used to do so, see below.
+#' 
 #' These functions are context-aware. This means that then the `x` argument can be left blank, see *Examples*.
 #' 
 #' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but more efficient for data sets containing microorganism codes or names.
 #' 
 #' All isolates with a microbial ID of `NA` will be excluded as first isolate.
 #' 
-#' ## Why this is so Important
-#' To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode [(Hindler *et al.* 2007)](https://pubmed.ncbi.nlm.nih.gov/17304462/). If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all *S. aureus* isolates would be overestimated, because you included this MRSA more than once. It would be [selection bias](https://en.wikipedia.org/wiki/Selection_bias).
-#'
-#' ## `filter_*()` Shortcuts
-#'
-#' The functions [filter_first_isolate()] and [filter_first_weighted_isolate()] are helper functions to quickly filter on first isolates.
+#' ## Different algorithms
 #' 
-#' The function [filter_first_isolate()] is essentially equal to either:
+#' According to Hindler *et al.* (2007, \doi{10.1086/511864}), there are different algorithms to select first isolates with increasing reliability: isolate-based, patient-based, episode-based and phenotype-based. All algorithms select on a combination of the taxonomic genus and species (not subspecies). 
 #' 
-#' ```
-#'   x[first_isolate(x, ...), ]
-#'   
-#'   x %>% filter(first_isolate(...))
-#' ```
+#' All mentioned algorithms are covered in the [first_isolate()] function:
 #' 
-#' The function [filter_first_weighted_isolate()] is essentially equal to:
 #' 
-#' ```
-#'   x %>%
-#'     mutate(keyab = key_antibiotics(.)) %>%
-#'     mutate(only_weighted_firsts = first_isolate(x,
-#'                                                 col_keyantibiotics = "keyab", ...)) %>%
-#'     filter(only_weighted_firsts == TRUE) %>%
-#'     select(-only_weighted_firsts, -keyab)
-#' ```
-#' @section Key Antibiotics:
-#' There are two ways to determine whether isolates can be included as first weighted isolates which will give generally the same results:
-#'
-#' 1. Using `type = "keyantibiotics"` and argument `ignore_I`
+#' | **Algorithm**                                    | **Function to apply**                                 |
+#' |--------------------------------------------------|-------------------------------------------------------|
+#' | Isolate-based                                    | `first_isolate(x, method = "isolate-based")`          |
+#' | *(= all isolates)*                               |                                                       |
+#' |                                                  |                                                       |
+#' |                                                  |                                                       |
+#' | Patient-based                                    | `first_isolate(x, method = "patient-based")`          |
+#' | *(= first isolate per patient)*                  |                                                       |
+#' |                                                  |                                                       |
+#' |                                                  |                                                       |
+#' | Episode-based                                    | `first_isolate(x, method = "episode-based")`, or:     |
+#' | *(= first isolate per episode)*                  |                                                       |
+#' | - 7-Day interval from initial isolate            | - `first_isolate(x, method = "e", episode_days = 7)`  |
+#' | - 30-Day interval from initial isolate           | - `first_isolate(x, method = "e", episode_days = 30)` |
+#' |                                                  |                                                       |
+#' |                                                  |                                                       |
+#' | Phenotype-based                                  | `first_isolate(x, method = "phenotype-based")`, or:   |
+#' | *(= first isolate per phenotype)*                |                                                       |
+#' | - Major difference in any antimicrobial result   | - `first_isolate(x, type = "points")`                 |
+#' | - Any difference in key antimicrobial results    | - `first_isolate(x, type = "keyantimicrobials")`      |
 #' 
-#'    Any difference from S to R (or vice versa) will (re)select an isolate as a first weighted isolate. With `ignore_I = FALSE`, also differences from I to S|R (or vice versa) will lead to this. This is a reliable method and 30-35 times faster than method 2. Read more about this in the [key_antibiotics()] function.
+#' ### Isolate-based
+#' 
+#' This algorithm does not require any selection, as all isolates should be included. It does, however, respect all arguments set in the [first_isolate()] function. For example, the default setting for `include_unknown` (`FALSE`) will omit selection of rows without a microbial ID.
+#' 
+#' ### Patient-based
+#' 
+#' To include every genus-species combination per patient once, set the `episode_days` to `Inf`. Although often inappropriate, this algorithm makes sure that no duplicate isolates are selected from the same patient.
+#' 
+#' ### Episode-based
+#' 
+#' To include every genus-species combination per patient episode once, set the `episode_days` to a sensible number of days. Depending on the type of analysis, this could be 14, 30, 60 or 365. Short episodes are common for analysing specific hospital or ward data, long episodes are common for analysing regional and national data.
+#' 
+#' This is the most common algorithm to correct for duplicate isolates. Patients are categorised into episodes based on their ID and dates (e.g., the date of specimen receipt or laboratory result). While this is a common algorithm, it does not take into account antimicrobial test results. This means that e.g. a methicillin-resistant *Staphylococcus aureus* (MRSA) isolate cannot be differentiated from a wildtype *Staphylococcus aureus* isolate.
+#' 
+#' ### Phenotype-based
+#' 
+#' This is a more reliable algorithm, since it also *weighs* the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram:
+#' 
+#' 1. Using `type = "points"` and argument `points_threshold`
+#' 
+#'    This method weighs *all* antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as 0.5 points, a difference from S to R (or vice versa) counts as 1 point. When the sum of points exceeds `points_threshold`, which defaults to `2`, an isolate will be selected as a first weighted isolate.
 #'    
-#' 2. Using `type = "points"` and argument `points_threshold`
+#'    All antimicrobials are internally selected using the [all_antimicrobials()] function. The output of this function does not need to be passed to the [first_isolate()] function.
 #' 
-#'    A difference from I to S|R (or vice versa) means 0.5 points, a difference from S to R (or vice versa) means 1 point. When the sum of points exceeds `points_threshold`, which defaults to `2`, an isolate will be (re)selected as a first weighted isolate.
+#'       
+#' 2. Using `type = "keyantimicrobials"` and argument `ignore_I`
+#' 
+#'    This method only weighs specific antimicrobial agents, called *key antimicrobials*. Any difference from S to R (or vice versa) in these key antimicrobials will select an isolate as a first weighted isolate. With `ignore_I = FALSE`, also differences from I to S or R (or vice versa) will lead to this. 
+#'    
+#'    Key antimicrobials are internally selected using the [key_antimicrobials()] function, but can also be added manually as a variable to the data and set in the `col_keyantimicrobials` argument. Another option is to pass the output of the [key_antimicrobials()] function directly to the `col_keyantimicrobials` argument.
+#'    
+#'    
+#' The default algorithm is phenotype-based (using `type = "points"`) and episode-based (using `episode_days = 365`). This makes sure that every genus-species combination is selected per patient once per year, while taking into account all antimicrobial test results.
 #' @rdname first_isolate
-#' @seealso [key_antibiotics()]
+#' @seealso [key_antimicrobials()]
 #' @export
 #' @return A [`logical`] vector
 #' @source Methodology of this function is strictly based on:
@@ -101,7 +130,6 @@
 #' # See ?example_isolates.
 #' 
 #' example_isolates[first_isolate(example_isolates), ]
-#' 
 #' \donttest{
 #' # faster way, only works in R 3.2 and later:
 #' example_isolates[first_isolate(), ]
@@ -139,7 +167,7 @@
 #'  
 #'   # Have a look at A and B.
 #'   # B is more reliable because every isolate is counted only once.
-#'   # Gentamicin resistance in hospital D appears to be 3.7% higher than
+#'   # Gentamicin resistance in hospital D appears to be 4.2% higher than
 #'   # when you (erroneously) would have used all isolates for analysis.
 #' }
 #' }
@@ -150,18 +178,32 @@ first_isolate <- function(x = NULL,
                          col_testcode = NULL,
                          col_specimen = NULL,
                          col_icu = NULL,
-                          col_keyantibiotics = NULL,
+                          col_keyantimicrobials = NULL,
                          episode_days = 365,
                          testcodes_exclude = NULL,
                          icu_exclude = FALSE,
                          specimen_group = NULL,
-                          type = "keyantibiotics",
+                          type = "points",
+                          method = c("phenotype-based", "episode-based", "patient-based", "isolate-based"),
                          ignore_I = TRUE,
                          points_threshold = 2,
                          info = interactive(),
                          include_unknown = FALSE,
                          include_untested_rsi = TRUE,
                          ...) {
+  
+  dots <- unlist(list(...))
+  if (length(dots) != 0) {
+    # backwards compatibility with old arguments
+    dots.names <- names(dots)
+    if ("filter_specimen" %in% dots.names) {
+      specimen_group <- dots[which(dots.names == "filter_specimen")]
+    }
+    if ("col_keyantibiotics" %in% dots.names) {
+      col_keyantimicrobials <- dots[which(dots.names == "col_keyantibiotics")]
+    }
+  }
+  
  if (is_null_or_grouped_tbl(x)) {
    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
    # is also fix for using a grouped df as input (a dot as first argument)
@@ -177,11 +219,27 @@ first_isolate <- function(x = NULL,
  }
  meet_criteria(col_specimen, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
  meet_criteria(col_icu, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
-  if (isFALSE(col_keyantibiotics)) {
-    col_keyantibiotics <- NULL
+  # method
+  if (missing(method)) {
+    method <- method[1L]
  }
-  meet_criteria(col_keyantibiotics, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
-  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based", "p", "e", "i"))
+  # key antimicrobials
+  if (length(col_keyantimicrobials) > 1) {
+    meet_criteria(col_keyantimicrobials, allow_class = "character", has_length = nrow(x))
+    x$keyabcol <- col_keyantimicrobials
+    col_keyantimicrobials <- "keyabcol"
+  } else {
+    if (isFALSE(col_keyantimicrobials)) {
+      col_keyantimicrobials <- NULL
+      # method cannot be phenotype-based anymore
+      if (method %in% c("phenotype-based", "p")) {
+        method <- "episode-based"
+      }
+    }
+    meet_criteria(col_keyantimicrobials, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
+  }
+  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
  meet_criteria(testcodes_exclude, allow_class = "character", allow_NULL = TRUE)
  meet_criteria(icu_exclude, allow_class = "logical", has_length = 1)
  meet_criteria(specimen_group, allow_class = "character", has_length = 1, allow_NULL = TRUE)
@@ -192,21 +250,23 @@ first_isolate <- function(x = NULL,
  meet_criteria(include_unknown, allow_class = "logical", has_length = 1)
  meet_criteria(include_untested_rsi, allow_class = "logical", has_length = 1)
  
+  method[method == "p"] <- "phenotype-based"
+  method[method == "e"] <- "episode-based"
+  method[method == "i"] <- "isolate-based"
+  if (info == TRUE) {
+    message_(paste0("Determining first isolates using the '", font_bold(method), "' method",
+                    ifelse(method %in% c("episode-based", "phenotype-based"),
+                           ifelse(is.infinite(episode_days),
+                                  " without a specified episode length",
+                                  paste(" and an episode length of", episode_days, "days")),
+                           "")),
+             as_note = FALSE,
+             add_fn = font_black)
+  }
+  
  # remove data.table, grouping from tibbles, etc.
  x <- as.data.frame(x, stringsAsFactors = FALSE)
  
-  dots <- unlist(list(...))
-  if (length(dots) != 0) {
-    # backwards compatibility with old arguments
-    dots.names <- names(dots)
-    if ("filter_specimen" %in% dots.names) {
-      specimen_group <- dots[which(dots.names == "filter_specimen")]
-    }
-    if ("tbl" %in% dots.names) {
-      x <- dots[which(dots.names == "tbl")]
-    }
-  }
-  
  # try to find columns based on type
  # -- mo
  if (is.null(col_mo)) {
@@ -214,6 +274,37 @@ first_isolate <- function(x = NULL,
    stop_if(is.null(col_mo), "`col_mo` must be set")
  }
  
+  # methods ----
+  if (method == "isolate-based") {
+    episode_days <- Inf
+    col_keyantimicrobials <- NULL
+    x$dummy_dates <- Sys.Date()
+    col_date <- "dummy_dates"
+    x$dummy_patients <- paste("dummy", seq_len(nrow(x))) # all 'patients' must be unique
+    col_patient_id <- "dummy_patients"
+  } else if (method == "patient-based") {
+    episode_days <- Inf
+    col_keyantimicrobials <- NULL
+  } else if (method == "episode-based") {
+    col_keyantimicrobials <- NULL
+  } else if (method == "phenotype-based") {
+    if (missing(type) & !is.null(col_keyantimicrobials)) {
+      # type = "points" is default, but not set explicitly, while col_keyantimicrobials is
+      type <- "keyantimicrobials"
+    }
+    if (type == "points") {
+      x$keyantimicrobials <- all_antimicrobials(x, only_rsi_columns = FALSE)
+      col_keyantimicrobials <- "keyantimicrobials"
+    } else if (type == "keyantimicrobials" & is.null(col_keyantimicrobials)) {
+      col_keyantimicrobials <- search_type_in_df(x = x, type = "keyantibiotics")
+      if (is.null(col_keyantimicrobials)) {
+        # still not found as a column, create it ourselves
+        x$keyantimicrobials <- key_antimicrobials(x, only_rsi_columns = FALSE, col_mo = col_mo, ...)
+        col_keyantimicrobials <- "keyantimicrobials"
+      }
+    }
+  }
+  
  # -- date
  if (is.null(col_date)) {
    col_date <- search_type_in_df(x = x, type = "date")
@@ -232,11 +323,6 @@ first_isolate <- function(x = NULL,
    }
    stop_if(is.null(col_patient_id), "`col_patient_id` must be set")
  }
-  
-  # -- key antibiotics
-  if (is.null(col_keyantibiotics)) {
-    col_keyantibiotics <- search_type_in_df(x = x, type = "keyantibiotics")
-  }

  # -- specimen
  if (is.null(col_specimen) & !is.null(specimen_group)) {
@@ -256,7 +342,7 @@ first_isolate <- function(x = NULL,
  check_columns_existance(col_mo)
  check_columns_existance(col_testcode)
  check_columns_existance(col_icu)
-  check_columns_existance(col_keyantibiotics)
+  check_columns_existance(col_keyantimicrobials)
  
  # convert dates to Date
  dates <- as.Date(x[, col_date, drop = TRUE])
@@ -275,7 +361,7 @@ first_isolate <- function(x = NULL,
  }
  # remove testcodes
  if (!is.null(testcodes_exclude) & info == TRUE) {
-    message_("[Criterion] Exclude test codes: ", toString(paste0("'", testcodes_exclude, "'")),
+    message_("Excluding test codes: ", toString(paste0("'", testcodes_exclude, "'")),
             add_fn = font_black,
             as_note = FALSE)
  }
@@ -288,13 +374,13 @@ first_isolate <- function(x = NULL,
  if (!is.null(specimen_group)) {
    check_columns_existance(col_specimen, x)
    if (info == TRUE) {
-      message_("[Criterion] Exclude other than specimen group '", specimen_group, "'",
+      message_("Excluding other than specimen group '", specimen_group, "'",
               add_fn = font_black,
               as_note = FALSE)
    }
  }
-  if (!is.null(col_keyantibiotics)) {
-    x$newvar_key_ab <- x[, col_keyantibiotics, drop = TRUE]
+  if (!is.null(col_keyantimicrobials)) {
+    x$newvar_key_ab <- x[, col_keyantimicrobials, drop = TRUE]
  }
  
  if (is.null(testcodes_exclude)) {
@@ -335,7 +421,7 @@ first_isolate <- function(x = NULL,
  }
  if (row.start == row.end) {
    if (info == TRUE) {
-      message_("=> Found ", font_bold("1 isolate"), ", as the data only contained 1 row", 
+      message_("=> Found ", font_bold("1 first isolate"), ", as the data only contained 1 row", 
               add_fn = font_black,
               as_note = FALSE)
    }
@@ -343,7 +429,7 @@ first_isolate <- function(x = NULL,
  }
  if (length(c(row.start:row.end)) == pm_n_distinct(x[c(row.start:row.end), col_mo, drop = TRUE])) {
    if (info == TRUE) {
-      message_("=> Found ", font_bold(paste(length(c(row.start:row.end)), "isolates")),
+      message_("=> Found ", font_bold(paste(length(c(row.start:row.end)), "first isolates")),
               ", as all isolates were different microorganisms",
               add_fn = font_black,
               as_note = FALSE)
@@ -372,18 +458,18 @@ first_isolate <- function(x = NULL,
                                           }))
  
  weighted.notice <- ""
-  if (!is.null(col_keyantibiotics)) {
+  if (!is.null(col_keyantimicrobials)) {
    weighted.notice <- "weighted "
    if (info == TRUE) {
-      if (type == "keyantibiotics") {
-        message_("[Criterion] Base inclusion on key antibiotics, ",
+      if (type == "keyantimicrobials") {
+        message_("Basing inclusion on key antimicrobials, ",
                 ifelse(ignore_I == FALSE, "not ", ""),
                 "ignoring I",
                 add_fn = font_black,
                 as_note = FALSE)
      }
      if (type == "points") {
-        message_("[Criterion] Base inclusion on key antibiotics, using points threshold of "
+        message_("Basing inclusion on all antimicrobial results, using a points threshold of "
                 , points_threshold,
                 add_fn = font_black,
                 as_note = FALSE)
@@ -391,12 +477,12 @@ first_isolate <- function(x = NULL,
    }
    type_param <- type
    
-    x$other_key_ab <- !key_antibiotics_equal(y = x$newvar_key_ab,
-                                             z = pm_lag(x$newvar_key_ab),
-                                             type = type_param,
-                                             ignore_I = ignore_I,
-                                             points_threshold = points_threshold,
-                                             info = info)
+    x$other_key_ab <- !antimicrobials_equal(y = x$newvar_key_ab,
+                                            z = pm_lag(x$newvar_key_ab),
+                                            type = type_param,
+                                            ignore_I = ignore_I,
+                                            points_threshold = points_threshold,
+                                            na.rm = TRUE)
    # with key antibiotics
    x$newvar_first_isolate <- pm_if_else(x$newvar_row_index_sorted >= row.start &
                                           x$newvar_row_index_sorted <= row.end &
@@ -423,12 +509,12 @@ first_isolate <- function(x = NULL,
  }
  if (!is.null(col_icu)) {
    if (icu_exclude == TRUE) {
-      message_("[Criterion] Exclude isolates from ICU.",
+      message_("Excluding isolates from ICU.",
               add_fn = font_black,
               as_note = FALSE)
      x[which(as.logical(x[, col_icu, drop = TRUE])), "newvar_first_isolate"] <- FALSE
    } else {
-      message_("[Criterion] Include isolates from ICU.",
+      message_("Including isolates from ICU.",
               add_fn = font_black,
               as_note = FALSE)
    }
@@ -453,7 +539,8 @@ first_isolate <- function(x = NULL,
            paste0('"', x, '"')
          }
        })
-        cat("\nGroup: ", paste0(names(group), " = ", group, collapse = ", "), "\n", sep = "")
+        message_("\nGroup: ", paste0(names(group), " = ", group, collapse = ", "), "\n",
+                 as_note = FALSE)
      }
    }
  }
@@ -491,10 +578,10 @@ first_isolate <- function(x = NULL,
    n_found <- sum(x$newvar_first_isolate, na.rm = TRUE)
    p_found_total <- percentage(n_found / nrow(x[which(!is.na(x$newvar_mo)), , drop = FALSE]), digits = 1)
    p_found_scope <- percentage(n_found / scope.size, digits = 1)
-    if (!p_found_total %like% "[.]") {
+    if (p_found_total %unlike% "[.]") {
      p_found_total <- gsub("%", ".0%", p_found_total, fixed = TRUE)
    }
-    if (!p_found_scope %like% "[.]") {
+    if (p_found_scope %unlike% "[.]") {
      p_found_scope <- gsub("%", ".0%", p_found_scope, fixed = TRUE)
    }
    # mark up number of found
@@ -502,11 +589,11 @@ first_isolate <- function(x = NULL,
    if (p_found_total != p_found_scope) {
      msg_txt <- paste0("=> Found ",
                        font_bold(paste0(n_found, " first ", weighted.notice, "isolates")),
-                        " (", p_found_scope, " within scope and ", p_found_total, " of total where a microbial ID was available)")
+                        " (", method, ", ", p_found_scope, " within scope and ", p_found_total, " of total where a microbial ID was available)")
    } else {
      msg_txt <- paste0("=> Found ",
                        font_bold(paste0(n_found, " first ", weighted.notice, "isolates")),
-                        " (", p_found_total, " of total where a microbial ID was available)")
+                        " (", method, ", ", p_found_total, " of total where a microbial ID was available)")
    }
    message_(msg_txt, add_fn = font_black, as_note = FALSE)
  }
@@ -521,6 +608,7 @@ filter_first_isolate <- function(x = NULL,
                                 col_date = NULL,
                                 col_patient_id = NULL,
                                 col_mo = NULL,
+                                 method = "episode-based",
                                 ...) {
  if (is_null_or_grouped_tbl(x)) {
    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
@@ -531,11 +619,13 @@ filter_first_isolate <- function(x = NULL,
  meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
  meet_criteria(col_patient_id, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
  meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
-
+  meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based"))
+  
  subset(x, first_isolate(x = x,
                          col_date = col_date,
                          col_patient_id = col_patient_id,
                          col_mo = col_mo,
+                          method = method,
                          ...))
 }

@@ -545,7 +635,7 @@ filter_first_weighted_isolate <- function(x = NULL,
                                          col_date = NULL,
                                          col_patient_id = NULL,
                                          col_mo = NULL,
-                                          col_keyantibiotics = NULL,
+                                          method = "phenotype-based",
                                          ...) {
  if (is_null_or_grouped_tbl(x)) {
    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
@@ -556,22 +646,12 @@ filter_first_weighted_isolate <- function(x = NULL,
  meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
  meet_criteria(col_patient_id, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
  meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
-  meet_criteria(col_keyantibiotics, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
-
-  y <- x
-  if (is.null(col_keyantibiotics)) {
-    # first try to look for it
-    col_keyantibiotics <- search_type_in_df(x = x, type = "keyantibiotics")
-    # still NULL? Then create it since we are calling filter_first_WEIGHTED_isolate()
-    if (is.null(col_keyantibiotics)) {
-      y$keyab <- suppressMessages(key_antibiotics(x,
-                                                  col_mo = col_mo,
-                                                  ...))
-      col_keyantibiotics <- "keyab"
-    }
-  }
+  meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based"))
  
-  subset(x, first_isolate(x = y,
+  subset(x, first_isolate(x = x,
                          col_date = col_date,
-                          col_patient_id = col_patient_id))
+                          col_patient_id = col_patient_id,
+                          col_mo = col_mo,
+                          method = method,
+                          ...))
 }
@@ -66,6 +66,7 @@ globalVariables(c(".rowid",
                  "antibiotics",
                  "atc_group1",
                  "atc_group2",
+                  "base_ab",
                  "code",
                  "cols",
                  "count",
@@ -102,6 +102,7 @@ get_column_abx <- function(x,
                           verbose = FALSE,
                           info = TRUE,
                           only_rsi_columns = FALSE,
+                           sort = TRUE,
                           ...) {
  meet_criteria(x, allow_class = "data.frame")
  meet_criteria(soft_dependencies, allow_class = "character", allow_NULL = TRUE)
@@ -109,6 +110,7 @@ get_column_abx <- function(x,
  meet_criteria(verbose, allow_class = "logical", has_length = 1)
  meet_criteria(info, allow_class = "logical", has_length = 1)
  meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
+  meet_criteria(sort, allow_class = "logical", has_length = 1)
  
  if (info == TRUE) {
    message_("Auto-guessing columns suitable for analysis", appendLF = FALSE, as_note = FALSE)
@@ -186,11 +188,15 @@ get_column_abx <- function(x,
  }
  
  # sort on name
-  x <- x[order(names(x), x)]
+  if (sort == TRUE) {
+    x <- x[order(names(x), x)]
+  }
  duplicates <- c(x[duplicated(x)], x[duplicated(names(x))]) 
  duplicates <- duplicates[unique(names(duplicates))]
  x <- c(x[!names(x) %in% names(duplicates)], duplicates)
-  x <- x[order(names(x), x)]
+  if (sort == TRUE) {
+    x <- x[order(names(x), x)]
+  }
  
  # succeeded with auto-guessing
  if (info == TRUE) {
@@ -279,7 +279,7 @@ check_groups_before_join <- function(x, fn) {
  if (is.data.frame(x) && !is.null(attributes(x)$groups)) {
    x <- pm_ungroup(x)
    attr(x, "groups") <- NULL
-    class(x) <- class(x)[!class(x) %like% "group"]
+    class(x) <- class(x)[class(x) %unlike% "group"]
    warning_("Groups are dropped, since the ", fn, "() function relies on merge() from base R.", call = FALSE)
  }
  x
@@ -1,380 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Data Analysis for R                   #
-#                                                                      #
-# SOURCE                                                               #
-# https://github.com/msberends/AMR                                     #
-#                                                                      #
-# LICENCE                                                              #
-# (c) 2018-2021 Berends MS, Luz CF et al.                              #
-# Developed at the University of Groningen, the Netherlands, in        #
-# collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
-#                                                                      #
-# This R package is free software; you can freely use and distribute   #
-# it for both personal and commercial purposes under the terms of the  #
-# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
-# the Free Software Foundation.                                        #
-# We created this package for both routine data analysis and academic  #
-# research and it was publicly released in the hope that it will be    #
-# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
-#                                                                      #
-# Visit our website for the full manual and a complete tutorial about  #
-# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
-# ==================================================================== #
-
-#' Key Antibiotics for First (Weighted) Isolates
-#'
-#' These function can be used to determine first isolates (see [first_isolate()]). Using key antibiotics to determine first isolates is more reliable than without key antibiotics. These selected isolates can then be called first 'weighted' isolates.
-#' @inheritSection lifecycle Stable Lifecycle
-#' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank to determine automatically
-#' @param y,z character vectors to compare
-#' @inheritParams first_isolate
-#' @param universal_1,universal_2,universal_3,universal_4,universal_5,universal_6 column names of **broad-spectrum** antibiotics, case-insensitive. See details for which antibiotics will be used at default (which are guessed with [guess_ab_col()]).
-#' @param GramPos_1,GramPos_2,GramPos_3,GramPos_4,GramPos_5,GramPos_6 column names of antibiotics for **Gram-positives**, case-insensitive. See details for which antibiotics will be used at default (which are guessed with [guess_ab_col()]).
-#' @param GramNeg_1,GramNeg_2,GramNeg_3,GramNeg_4,GramNeg_5,GramNeg_6 column names of antibiotics for **Gram-negatives**, case-insensitive. See details for which antibiotics will be used at default (which are guessed with [guess_ab_col()]).
-#' @param warnings give a warning about missing antibiotic columns (they will be ignored)
-#' @param ... other arguments passed on to functions
-#' @details 
-#' The [key_antibiotics()] function is context-aware. This means that then the `x` argument can be left blank, see *Examples*.
-#' 
-#' The function [key_antibiotics()] returns a character vector with 12 antibiotic results for every isolate. These isolates can then be compared using [key_antibiotics_equal()], to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (`"."`) by [key_antibiotics()] and ignored by [key_antibiotics_equal()].
-#' 
-#' The [first_isolate()] function only uses this function on the same microbial species from the same patient. Using this, e.g. an MRSA will be included after a susceptible *S. aureus* (MSSA) is found within the same patient episode. Without key antibiotic comparison it would not. See [first_isolate()] for more info.
-#'
-#' At default, the antibiotics that are used for **Gram-positive bacteria** are:
-#' - Amoxicillin
-#' - Amoxicillin/clavulanic acid
-#' - Cefuroxime
-#' - Piperacillin/tazobactam
-#' - Ciprofloxacin
-#' - Trimethoprim/sulfamethoxazole
-#' - Vancomycin
-#' - Teicoplanin
-#' - Tetracycline
-#' - Erythromycin
-#' - Oxacillin
-#' - Rifampin
-#'
-#' At default the antibiotics that are used for **Gram-negative bacteria** are:
-#' - Amoxicillin
-#' - Amoxicillin/clavulanic acid
-#' - Cefuroxime
-#' - Piperacillin/tazobactam
-#' - Ciprofloxacin
-#' - Trimethoprim/sulfamethoxazole
-#' - Gentamicin
-#' - Tobramycin
-#' - Colistin
-#' - Cefotaxime
-#' - Ceftazidime
-#' - Meropenem
-#' 
-#' The function [key_antibiotics_equal()] checks the characters returned by [key_antibiotics()] for equality, and returns a [`logical`] vector.
-#' @inheritSection first_isolate Key Antibiotics
-#' @rdname key_antibiotics
-#' @export
-#' @seealso [first_isolate()]
-#' @inheritSection AMR Read more on Our Website!
-#' @examples
-#' # `example_isolates` is a data set available in the AMR package.
-#' # See ?example_isolates.
-#' 
-#' # output of the `key_antibiotics()` function could be like this:
-#' strainA <- "SSSRR.S.R..S"
-#' strainB <- "SSSIRSSSRSSS"
-#'
-#' # those strings can be compared with:
-#' key_antibiotics_equal(strainA, strainB)
-#' # TRUE, because I is ignored (as well as missing values)
-#'
-#' key_antibiotics_equal(strainA, strainB, ignore_I = FALSE)
-#' # FALSE, because I is not ignored and so the 4th character differs
-#'
-#' \donttest{
-#' if (require("dplyr")) {
-#'   # set key antibiotics to a new variable
-#'   my_patients <- example_isolates %>%
-#'     mutate(keyab = key_antibiotics()) %>% # no need to define `x`
-#'     mutate(
-#'       # now calculate first isolates
-#'       first_regular = first_isolate(col_keyantibiotics = FALSE),
-#'       # and first WEIGHTED isolates
-#'       first_weighted = first_isolate(col_keyantibiotics = "keyab")
-#'     )
-#'  
-#'   # Check the difference, in this data set it results in a lot more isolates:
-#'   sum(my_patients$first_regular, na.rm = TRUE)
-#'   sum(my_patients$first_weighted, na.rm = TRUE)
-#' }
-#' }
-key_antibiotics <- function(x = NULL,
-                            col_mo = NULL,
-                            universal_1 = guess_ab_col(x, "amoxicillin"),
-                            universal_2 = guess_ab_col(x, "amoxicillin/clavulanic acid"),
-                            universal_3 = guess_ab_col(x, "cefuroxime"),
-                            universal_4 = guess_ab_col(x, "piperacillin/tazobactam"),
-                            universal_5 = guess_ab_col(x, "ciprofloxacin"),
-                            universal_6 = guess_ab_col(x, "trimethoprim/sulfamethoxazole"),
-                            GramPos_1 = guess_ab_col(x, "vancomycin"),
-                            GramPos_2 = guess_ab_col(x, "teicoplanin"),
-                            GramPos_3 = guess_ab_col(x, "tetracycline"),
-                            GramPos_4 = guess_ab_col(x, "erythromycin"),
-                            GramPos_5 = guess_ab_col(x, "oxacillin"),
-                            GramPos_6 = guess_ab_col(x, "rifampin"),
-                            GramNeg_1 = guess_ab_col(x, "gentamicin"),
-                            GramNeg_2 = guess_ab_col(x, "tobramycin"),
-                            GramNeg_3 = guess_ab_col(x, "colistin"),
-                            GramNeg_4 = guess_ab_col(x, "cefotaxime"),
-                            GramNeg_5 = guess_ab_col(x, "ceftazidime"),
-                            GramNeg_6 = guess_ab_col(x, "meropenem"),
-                            warnings = TRUE,
-                            ...) {
-  if (is_null_or_grouped_tbl(x)) {
-    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
-    # is also fix for using a grouped df as input (a dot as first argument)
-    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
-  }
-  meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
-  meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(universal_1, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(universal_2, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(universal_3, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(universal_4, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(universal_5, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(universal_6, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramPos_1, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramPos_2, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramPos_3, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramPos_4, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramPos_5, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramPos_6, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramNeg_1, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramNeg_2, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramNeg_3, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramNeg_4, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramNeg_5, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(GramNeg_6, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(warnings, allow_class = "logical", has_length = 1)
-  
-  # force regular data.frame, not a tibble or data.table
-  x <- as.data.frame(x, stringsAsFactors = FALSE)
-  
-  dots <- unlist(list(...))
-  if (length(dots) != 0) {
-    # backwards compatibility with old arguments
-    dots.names <- names(dots)
-    if ("info" %in% dots.names) {
-      warnings <- dots[which(dots.names == "info")]
-    }
-  }
-  
-  # try to find columns based on type
-  # -- mo
-  if (is.null(col_mo)) {
-    col_mo <- search_type_in_df(x = x, type = "mo")
-    stop_if(is.null(col_mo), "`col_mo` must be set")
-  } else {
-    stop_ifnot(col_mo %in% colnames(x), "column '", col_mo, "' (`col_mo`) not found")
-  }
-  
-  # check columns
-  col.list <- c(universal_1, universal_2, universal_3, universal_4, universal_5, universal_6,
-                GramPos_1, GramPos_2, GramPos_3, GramPos_4, GramPos_5, GramPos_6,
-                GramNeg_1, GramNeg_2, GramNeg_3, GramNeg_4, GramNeg_5, GramNeg_6)
-  check_available_columns <- function(x, col.list, warnings = TRUE) {
-    # check columns
-    col.list <- col.list[!is.na(col.list) & !is.null(col.list)]
-    names(col.list) <- col.list
-    col.list.bak <- col.list
-    # are they available as upper case or lower case then?
-    for (i in seq_len(length(col.list))) {
-      if (is.null(col.list[i]) | isTRUE(is.na(col.list[i]))) {
-        col.list[i] <- NA
-      } else if (toupper(col.list[i]) %in% colnames(x)) {
-        col.list[i] <- toupper(col.list[i])
-      } else if (tolower(col.list[i]) %in% colnames(x)) {
-        col.list[i] <- tolower(col.list[i])
-      } else if (!col.list[i] %in% colnames(x)) {
-        col.list[i] <- NA
-      }
-    }
-    if (!all(col.list %in% colnames(x))) {
-      if (warnings == TRUE) {
-        warning_("Some columns do not exist and will be ignored: ",
-                 col.list.bak[!(col.list %in% colnames(x))] %pm>% toString(),
-                 ".\nTHIS MAY STRONGLY INFLUENCE THE OUTCOME.",
-                 immediate = TRUE,
-                 call = FALSE)
-      }
-    }
-    col.list
-  }
-  
-  col.list <- check_available_columns(x = x, col.list = col.list, warnings = warnings)
-  universal_1 <- col.list[universal_1]
-  universal_2 <- col.list[universal_2]
-  universal_3 <- col.list[universal_3]
-  universal_4 <- col.list[universal_4]
-  universal_5 <- col.list[universal_5]
-  universal_6 <- col.list[universal_6]
-  GramPos_1 <- col.list[GramPos_1]
-  GramPos_2 <- col.list[GramPos_2]
-  GramPos_3 <- col.list[GramPos_3]
-  GramPos_4 <- col.list[GramPos_4]
-  GramPos_5 <- col.list[GramPos_5]
-  GramPos_6 <- col.list[GramPos_6]
-  GramNeg_1 <- col.list[GramNeg_1]
-  GramNeg_2 <- col.list[GramNeg_2]
-  GramNeg_3 <- col.list[GramNeg_3]
-  GramNeg_4 <- col.list[GramNeg_4]
-  GramNeg_5 <- col.list[GramNeg_5]
-  GramNeg_6 <- col.list[GramNeg_6]
-  
-  universal <- c(universal_1, universal_2, universal_3,
-                 universal_4, universal_5, universal_6)
-  
-  gram_positive <- c(universal,
-                     GramPos_1, GramPos_2, GramPos_3,
-                     GramPos_4, GramPos_5, GramPos_6)
-  gram_positive <- gram_positive[!is.null(gram_positive)]
-  gram_positive <- gram_positive[!is.na(gram_positive)]
-  if (length(gram_positive) < 12 & message_not_thrown_before("key_antibiotics.grampos")) {
-    warning_("Only using ", length(gram_positive), " different antibiotics as key antibiotics for Gram-positives. See ?key_antibiotics.", call = FALSE)
-    remember_thrown_message("key_antibiotics.grampos")
-  }
-  
-  gram_negative <- c(universal,
-                     GramNeg_1, GramNeg_2, GramNeg_3,
-                     GramNeg_4, GramNeg_5, GramNeg_6)
-  gram_negative <- gram_negative[!is.null(gram_negative)]
-  gram_negative <- gram_negative[!is.na(gram_negative)]
-  if (length(gram_negative) < 12 & message_not_thrown_before("key_antibiotics.gramneg")) {
-    warning_("Only using ", length(gram_negative), " different antibiotics as key antibiotics for Gram-negatives. See ?key_antibiotics.", call = FALSE)
-    remember_thrown_message("key_antibiotics.gramneg")
-  }
-  
-  x[, col_mo] <- as.mo(x[, col_mo, drop = TRUE])
-  x$gramstain <- mo_gramstain(x[, col_mo, drop = TRUE], language = NULL)
-  x$key_ab <- NA_character_
-  
-  # Gram +
-  x$key_ab <- pm_if_else(x$gramstain == "Gram-positive",
-                      tryCatch(apply(X = x[, gram_positive],
-                                     MARGIN = 1,
-                                     FUN = function(x) paste(x, collapse = "")),
-                               error = function(e) paste0(rep(".", 12), collapse = "")),
-                      x$key_ab)
-  
-  # Gram -
-  x$key_ab <- pm_if_else(x$gramstain == "Gram-negative",
-                      tryCatch(apply(X = x[, gram_negative],
-                                     MARGIN = 1,
-                                     FUN = function(x) paste(x, collapse = "")),
-                               error = function(e) paste0(rep(".", 12), collapse = "")),
-                      x$key_ab)
-  
-  # format
-  key_abs <- toupper(gsub("[^SIR]", ".", gsub("(NA|NULL)", ".", x$key_ab)))
-  
-  if (pm_n_distinct(key_abs) == 1) {
-    warning_("No distinct key antibiotics determined.", call = FALSE)
-  }
-  
-  key_abs
-  
-}
-
-#' @rdname key_antibiotics
-#' @export
-key_antibiotics_equal <- function(y,
-                                  z,
-                                  type = c("keyantibiotics", "points"),
-                                  ignore_I = TRUE,
-                                  points_threshold = 2,
-                                  info = FALSE) {
-  meet_criteria(y, allow_class = "character")
-  meet_criteria(z, allow_class = "character")
-  meet_criteria(type, allow_class = "character", has_length = c(1, 2))
-  meet_criteria(ignore_I, allow_class = "logical", has_length = 1)
-  meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
-  meet_criteria(info, allow_class = "logical", has_length = 1)
-  
-  stop_ifnot(length(y) == length(z), "length of `y` and `z` must be equal")
-  # y is active row, z is lag
-  x <- y
-  y <- z
-  
-  type <- type[1]
-  
-  # only show progress bar on points or when at least 5000 isolates
-  info_needed <- info == TRUE & (type == "points" | length(x) > 5000)
-  
-  result <- logical(length(x))
-  
-  if (info_needed == TRUE) {
-    p <- progress_ticker(length(x))
-    on.exit(close(p))
-  }
-  
-  for (i in seq_len(length(x))) {
-    
-    if (info_needed == TRUE) {
-      p$tick()
-    }
-    
-    if (is.na(x[i])) {
-      x[i] <- ""
-    }
-    if (is.na(y[i])) {
-      y[i] <- ""
-    }
-    
-    if (x[i] == y[i]) {
-      
-      result[i] <- TRUE
-      
-    } else if (nchar(x[i]) != nchar(y[i])) {
-      
-      result[i] <- FALSE
-      
-    } else {
-      
-      x_split <- strsplit(x[i], "")[[1]]
-      y_split <- strsplit(y[i], "")[[1]]
-      
-      if (type == "keyantibiotics") {
-        
-        if (ignore_I == TRUE) {
-          x_split[x_split == "I"] <- "."
-          y_split[y_split == "I"] <- "."
-        }
-        
-        y_split[x_split == "."] <- "."
-        x_split[y_split == "."] <- "."
-        
-        result[i] <- all(x_split == y_split)
-        
-      } else if (type == "points") {
-        # count points for every single character:
-        # - no change is 0 points
-        # - I <-> S|R is 0.5 point
-        # - S|R <-> R|S is 1 point
-        # use the levels of as.rsi (S = 1, I = 2, R = 3)
-        
-        suppressWarnings(x_split <- x_split %pm>% as.rsi() %pm>% as.double())
-        suppressWarnings(y_split <- y_split %pm>% as.rsi() %pm>% as.double())
-        
-        points <- (x_split - y_split) %pm>% abs() %pm>% sum(na.rm = TRUE) / 2
-        result[i] <- points >= points_threshold
-        
-      } else {
-        stop("`", type, '` is not a valid value for type, must be "points" or "keyantibiotics". See ?key_antibiotics')
-      }
-    }
-  }
-  if (info_needed == TRUE) {
-    close(p)
-  }
-  result
-}
@@ -0,0 +1,328 @@
+# ==================================================================== #
+# TITLE                                                                #
+# Antimicrobial Resistance (AMR) Data Analysis for R                   #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# LICENCE                                                              #
+# (c) 2018-2021 Berends MS, Luz CF et al.                              #
+# Developed at the University of Groningen, the Netherlands, in        #
+# collaboration with non-profit organisations Certe Medical            #
+# Diagnostics & Advice, and University Medical Center Groningen.       # 
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+#' (Key) Antimicrobials for First Weighted Isolates
+#'
+#' These functions can be used to determine first weighted isolates by considering the phenotype for isolate selection (see [first_isolate()]). Using a phenotype-based method to determine first isolates is more reliable than methods that disregard phenotypes.
+#' @inheritSection lifecycle Stable Lifecycle
+#' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank to determine automatically
+#' @param y,z character vectors to compare
+#' @inheritParams first_isolate
+#' @param universal names of **broad-spectrum** antimicrobial agents, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
+#' @param gram_negative names of antibiotic agents for **Gram-positives**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
+#' @param gram_positive names of antibiotic agents for **Gram-negatives**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
+#' @param antifungal names of antifungal agents for **fungi**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
+#' @param only_rsi_columns a logical to indicate whether only columns must be included that were transformed to class `<rsi>` (see [as.rsi()]) on beforehand (defaults to `FALSE`)
+#' @param ... ignored, allows for future extensions
+#' @details 
+#' The [key_antimicrobials()] and [all_antimicrobials()] functions are context-aware. This means that then the `x` argument can be left blank, see *Examples*.
+#' 
+#' The function [key_antimicrobials()] returns a character vector with 12 antimicrobial results for every isolate. The function [all_antimicrobials()] returns a character vector with all antimicrobial results for every isolate. These vectors can then be compared using [antimicrobials_equal()], to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (`"."`) by [key_antimicrobials()] and ignored by [antimicrobials_equal()].
+#' 
+#' Please see the [first_isolate()] function how these important functions enable the 'phenotype-based' method for determination of first isolates.
+#'
+#' The default antimicrobial agents used for **all rows** (set in `universal`) are:
+#' 
+#' - Ampicillin
+#' - Amoxicillin/clavulanic acid
+#' - Cefuroxime
+#' - Ciprofloxacin
+#' - Piperacillin/tazobactam
+#' - Trimethoprim/sulfamethoxazole
+#'
+#' The default antimicrobial agents used for **Gram-negative bacteria** (set in `gram_negative`) are:
+#' 
+#' - Cefotaxime
+#' - Ceftazidime
+#' - Colistin
+#' - Gentamicin
+#' - Meropenem
+#' - Tobramycin
+#'
+#' The default antimicrobial agents used for **Gram-positive bacteria** (set in `gram_positive`) are:
+#' 
+#' - Erythromycin
+#' - Oxacillin
+#' - Rifampin
+#' - Teicoplanin
+#' - Tetracycline
+#' - Vancomycin
+#' 
+#' 
+#' The default antimicrobial agents used for **fungi** (set in `antifungal`) are:
+#' 
+#' - Anidulafungin
+#' - Caspofungin
+#' - Fluconazole
+#' - Miconazole
+#' - Nystatin
+#' - Voriconazole
+#' @rdname key_antimicrobials
+#' @export
+#' @seealso [first_isolate()]
+#' @inheritSection AMR Read more on Our Website!
+#' @examples
+#' # `example_isolates` is a data set available in the AMR package.
+#' # See ?example_isolates.
+#' 
+#' # output of the `key_antimicrobials()` function could be like this:
+#' strainA <- "SSSRR.S.R..S"
+#' strainB <- "SSSIRSSSRSSS"
+#'
+#' # those strings can be compared with:
+#' antimicrobials_equal(strainA, strainB, type = "keyantimicrobials")
+#' # TRUE, because I is ignored (as well as missing values)
+#'
+#' antimicrobials_equal(strainA, strainB, type = "keyantimicrobials", ignore_I = FALSE)
+#' # FALSE, because I is not ignored and so the 4th character differs
+#'
+#' \donttest{
+#' if (require("dplyr")) {
+#'   # set key antibiotics to a new variable
+#'   my_patients <- example_isolates %>%
+#'     mutate(keyab = key_antimicrobials(antifungal = NULL)) %>% # no need to define `x`
+#'     mutate(
+#'       # now calculate first isolates
+#'       first_regular = first_isolate(col_keyantimicrobials = FALSE),
+#'       # and first WEIGHTED isolates
+#'       first_weighted = first_isolate(col_keyantimicrobials = "keyab")
+#'     )
+#'  
+#'   # Check the difference, in this data set it results in more isolates:
+#'   sum(my_patients$first_regular, na.rm = TRUE)
+#'   sum(my_patients$first_weighted, na.rm = TRUE)
+#' }
+#' }
+key_antimicrobials <- function(x = NULL,
+                               col_mo = NULL,
+                               universal = c("ampicillin", "amoxicillin/clavulanic acid", "cefuroxime",
+                                             "piperacillin/tazobactam", "ciprofloxacin", "trimethoprim/sulfamethoxazole"),
+                               gram_negative = c("gentamicin", "tobramycin", "colistin",
+                                                 "cefotaxime", "ceftazidime", "meropenem"),
+                               gram_positive = c("vancomycin", "teicoplanin", "tetracycline",
+                                                 "erythromycin", "oxacillin", "rifampin"),
+                               antifungal = c("anidulafungin", "caspofungin", "fluconazole",
+                                              "miconazole", "nystatin", "voriconazole"),
+                               only_rsi_columns = FALSE,
+                               ...) {
+  if (is_null_or_grouped_tbl(x)) {
+    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
+    # is also fix for using a grouped df as input (a dot as first argument)
+    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
+  }
+  meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
+  meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE, is_in = colnames(x))
+  meet_criteria(universal, allow_class = "character", allow_NULL = TRUE)
+  meet_criteria(gram_negative, allow_class = "character", allow_NULL = TRUE)
+  meet_criteria(gram_positive, allow_class = "character", allow_NULL = TRUE)
+  meet_criteria(antifungal, allow_class = "character", allow_NULL = TRUE)
+  meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
+  
+  # force regular data.frame, not a tibble or data.table
+  x <- as.data.frame(x, stringsAsFactors = FALSE)
+  cols <- get_column_abx(x, info = FALSE, only_rsi_columns = only_rsi_columns)
+  
+  # try to find columns based on type
+  # -- mo
+  if (is.null(col_mo)) {
+    col_mo <- search_type_in_df(x = x, type = "mo", info = FALSE)
+  }
+  if (is.null(col_mo)) {
+    warning_("No column found for `col_mo`, ignoring antibiotics set in `gram_negative` and `gram_positive`, and antimycotics set in `antifungal`", call = FALSE)
+    gramstain <- NA_character_
+    kingdom <- NA_character_
+  } else {
+    x.mo <- as.mo(x[, col_mo, drop = TRUE])
+    gramstain <- mo_gramstain(x.mo, language = NULL)
+    kingdom <- mo_kingdom(x.mo, language = NULL)
+  }
+  
+  AMR_string <- function(x, values, name, filter, cols = cols) {
+    if (is.null(values)) {
+      return(rep(NA_character_, length(which(filter))))
+    }
+    
+    values_old_length <- length(values)
+    values <- as.ab(values, flag_multiple_results = FALSE, info = FALSE)
+    values <- cols[names(cols) %in% values]
+    values_new_length <- length(values)
+    
+    if (values_new_length < values_old_length &
+        any(filter, na.rm = TRUE) &
+        message_not_thrown_before(paste0("key_antimicrobials.", name))) {
+      warning_(ifelse(values_new_length == 0,
+                      "No columns available ",
+                      paste0("Only using ", values_new_length, " out of ", values_old_length, " defined columns ")),
+               "as key antimicrobials for ", name, "s. See ?key_antimicrobials.",
+               call = FALSE)
+      remember_thrown_message(paste0("key_antimicrobials.", name))
+    }
+    
+    generate_antimcrobials_string(x[which(filter), c(universal, values), drop = FALSE])
+  }
+  
+  if (is.null(universal)) {
+    universal <- character(0)
+  } else {
+    universal <- as.ab(universal, flag_multiple_results = FALSE, info = FALSE)
+    universal <- cols[names(cols) %in% universal]
+  }
+  
+  key_ab <- rep(NA_character_, nrow(x))
+  
+  key_ab[which(gramstain == "Gram-negative")] <- AMR_string(x = x,
+                                                            values = gram_negative,
+                                                            name = "Gram-negative",
+                                                            filter = gramstain == "Gram-negative",
+                                                            cols = cols)
+  
+  key_ab[which(gramstain == "Gram-positive")] <- AMR_string(x = x,
+                                                            values = gram_positive,
+                                                            name = "Gram-positive",
+                                                            filter = gramstain == "Gram-positive",
+                                                            cols = cols)
+  
+  key_ab[which(kingdom == "Fungi")] <- AMR_string(x = x,
+                                                  values = antifungal,
+                                                  name = "antifungal",
+                                                  filter = kingdom == "Fungi",
+                                                  cols = cols)
+  
+  # back-up - only use `universal`
+  key_ab[which(is.na(key_ab))] <- AMR_string(x = x,
+                                             values = character(0),
+                                             name = "",
+                                             filter = is.na(key_ab),
+                                             cols = cols)
+  
+  if (length(unique(key_ab)) == 1) {
+    warning_("No distinct key antibiotics determined.", call = FALSE)
+  }
+  
+  key_ab
+}
+
+#' @rdname key_antimicrobials
+#' @export
+all_antimicrobials <- function(x = NULL,
+                               only_rsi_columns = FALSE,
+                               ...) {
+  if (is_null_or_grouped_tbl(x)) {
+    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
+    # is also fix for using a grouped df as input (a dot as first argument)
+    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
+  }
+  meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
+  meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
+  
+  # force regular data.frame, not a tibble or data.table
+  x <- as.data.frame(x, stringsAsFactors = FALSE)
+  cols <- get_column_abx(x, only_rsi_columns = only_rsi_columns, info = FALSE, sort = FALSE)
+  
+  generate_antimcrobials_string(x[ , cols, drop = FALSE])
+}
+
+generate_antimcrobials_string <- function(df) {
+  if (NCOL(df) == 0) {
+    return(rep("", NROW(df)))
+  }
+  if (NROW(df) == 0) {
+    return(character(0))
+  }
+  out <- tryCatch(
+    do.call(paste0,
+            lapply(as.list(df),
+                   function(x) {
+                     x <- toupper(as.character(x))
+                     x[!x %in% c("R", "S", "I")] <- "."
+                     paste(x)
+                   })),
+    error = function(e) rep(strrep(".", NCOL(df)), NROW(df)))
+  out
+}
+
+#' @rdname key_antimicrobials
+#' @param info unused - previously used to indicate whether a progress bar should print
+#' @export
+antimicrobials_equal <- function(y,
+                                  z,
+                                  type = c("points", "keyantimicrobials"),
+                                  ignore_I = TRUE,
+                                  points_threshold = 2,
+                                  info = FALSE,
+                                  ...) {
+  meet_criteria(y, allow_class = "character")
+  meet_criteria(z, allow_class = "character")
+  stop_if(missing(type), "argument \"type\" is missing, with no default")
+  meet_criteria(type, allow_class = "character", has_length = 1, is_in = c("points", "keyantimicrobials"))
+  meet_criteria(ignore_I, allow_class = "logical", has_length = 1)
+  meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(info, allow_class = "logical", has_length = 1)
+  stop_ifnot(length(y) == length(z), "length of `y` and `z` must be equal")
+
+  key2rsi <- function(val) {
+    as.double(as.rsi(gsub(".", NA_character_, unlist(strsplit(val, "")), fixed = TRUE)))
+  }
+  y <- lapply(y, key2rsi)
+  z <- lapply(z, key2rsi)
+  
+  determine_equality <- function(a, b, type, points_threshold, ignore_I) {
+    if (length(a) != length(b)) {
+      # incomparable, so not equal
+      return(FALSE)
+    }
+    # ignore NAs on both sides
+    NA_ind <- which(is.na(a) | is.na(b))
+    a[NA_ind] <- NA_real_
+    b[NA_ind] <- NA_real_
+    
+    if (type == "points") {
+      # count points for every single character:
+      # - no change is 0 points
+      # - I <-> S|R is 0.5 point
+      # - S|R <-> R|S is 1 point
+      # use the levels of as.rsi (S = 1, I = 2, R = 3)
+      # and divide by 2 (S = 0.5, I = 1, R = 1.5)
+      (sum(abs(a - b), na.rm = TRUE) / 2) < points_threshold
+    } else {
+      if (ignore_I == TRUE) {
+        ind <- which(a == 2 | b == 2) # since as.double(as.rsi("I")) == 2
+        a[ind] <- NA_real_
+        b[ind] <- NA_real_
+      }
+      all(a == b, na.rm = TRUE)
+    }
+  }
+  out <- unlist(mapply(FUN = determine_equality,
+                       y,
+                       z,
+                       MoreArgs = list(type = type,
+                                       points_threshold = points_threshold,
+                                       ignore_I = ignore_I),
+                       SIMPLIFY = FALSE,
+                       USE.NAMES = FALSE))
+  out[is.na(y) | is.na(z)] <- NA
+  out
+}
@@ -23,30 +23,29 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #

-#' Pattern Matching with Keyboard Shortcut
+#' Vectorised Pattern Matching with Keyboard Shortcut
 #'
 #' Convenient wrapper around [grepl()] to match a pattern: `x %like% pattern`. It always returns a [`logical`] vector and is always case-insensitive (use `x %like_case% pattern` for case-sensitive matching). Also, `pattern` can be as long as `x` to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.
 #' @inheritSection lifecycle Stable Lifecycle
 #' @param x a character vector where matches are sought, or an object which can be coerced by [as.character()] to a character vector.
-#' @param pattern a character string containing a regular expression (or [character] string for `fixed = TRUE`) to be matched in the given character vector. Coerced by [as.character()] to a character string if possible.  If a [character] vector of length 2 or more is supplied, the first element is used with a warning.
+#' @param pattern a character vector containing regular expressions (or a [character] string for `fixed = TRUE`) to be matched in the given character vector. Coerced by [as.character()] to a character string if possible.
 #' @param ignore.case if `FALSE`, the pattern matching is *case sensitive* and if `TRUE`, case is ignored during matching.
-#' @return A [`logical`] vector
+#' @return A [logical] vector
 #' @name like
 #' @rdname like
 #' @export
 #' @details
-#' The `%like%` function:
-#' * Is case-insensitive (use `%like_case%` for case-sensitive matching)
-#' * Supports multiple patterns
-#' * Checks if `pattern` is a regular expression and sets `fixed = TRUE` if not, to greatly improve speed
-#' * Always uses compatibility with Perl
+#' These [like()] and `%like%`/`%unlike%` functions:
+#' * Are case-insensitive (use `%like_case%`/`%unlike_case%` for case-sensitive matching)
+#' * Support multiple patterns
+#' * Check if `pattern` is a valid regular expression and sets `fixed = TRUE` if not, to greatly improve speed (vectorised over `pattern`)
+#' * Always use compatibility with Perl unless `fixed = TRUE`, to greatly improve speed
 #' 
-#' Using RStudio? The text `%like%` can also be directly inserted in your code from the Addins menu and can have its own Keyboard Shortcut like `Ctrl+Shift+L` or `Cmd+Shift+L` (see `Tools` > `Modify Keyboard Shortcuts...`).
-#' @source Idea from the [`like` function from the `data.table` package](https://github.com/Rdatatable/data.table/blob/master/R/like.R)
+#' Using RStudio? The `%like%`/`%unlike%` functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like `Shift+Ctrl+L` or `Shift+Cmd+L` (see menu `Tools` > `Modify Keyboard Shortcuts...`). If you keep pressing your shortcut, the inserted text will be iterated over `%like%` -> `%unlike%` -> `%like_case%` -> `%unlike_case%`.
+#' @source Idea from the [`like` function from the `data.table` package](https://github.com/Rdatatable/data.table/blob/ec1259af1bf13fc0c96a1d3f9e84d55d8106a9a4/R/like.R), although altered as explained in *Details*.
 #' @seealso [grepl()]
 #' @inheritSection AMR Read more on Our Website!
 #' @examples
-#' # simple test
 #' a <- "This is a test"
 #' b <- "TEST"
 #' a %like% b
@@ -59,16 +58,23 @@
 #' b <- c(     "case",           "diff",      "yet")
 #' a %like% b
 #' #> TRUE TRUE TRUE
+#' a %unlike% b
+#' #> FALSE FALSE FALSE
+#' 
 #' a[1] %like% b
 #' #> TRUE FALSE FALSE
 #' a %like% b[1]
 #' #> TRUE FALSE FALSE
 #' 
 #' # get isolates whose name start with 'Ent' or 'ent'
+#' example_isolates[which(mo_name(example_isolates$mo) %like% "^ent"), ]
 #' \donttest{
+#' # faster way, only works in R 3.2 and later:
+#' example_isolates[which(mo_name() %like% "^ent"), ]
+#' 
 #' if (require("dplyr")) {
 #'   example_isolates %>%
-#'     filter(mo_name(mo) %like% "^ent")
+#'     filter(mo_name() %like% "^ent")
 #' }
 #' }
 like <- function(x, pattern, ignore.case = TRUE) {
@@ -79,9 +85,10 @@ like <- function(x, pattern, ignore.case = TRUE) {
  if (all(is.na(x))) {
    return(rep(FALSE, length(x)))
  }
-  
-  # set to fixed if no regex found
-  fixed <- !any(is_possibly_regex(pattern))
+
+  # set to fixed if no valid regex (vectorised)
+  fixed <- !is_valid_regex(pattern)
+
  if (ignore.case == TRUE) {
    # set here, otherwise if fixed = TRUE, this warning will be thrown: argument `ignore.case = TRUE` will be ignored
    x <- tolower(x)
@@ -91,21 +98,26 @@ like <- function(x, pattern, ignore.case = TRUE) {
  if (is.factor(x)) {
    x <- as.character(x)
  }
-  
+
  if (length(pattern) == 1) {
    grepl(pattern, x, ignore.case = FALSE, fixed = fixed, perl = !fixed)
  } else {
    if (length(x) == 1) {
      x <- rep(x, length(pattern))
    } else if (length(pattern) != length(x)) {
-      stop_("arguments `x` and `pattern` must be of same length, or either one must be 1")
+      stop_("arguments `x` and `pattern` must be of same length, or either one must be 1 ",
+            "(`x` has length ", length(x), " and `pattern` has length ", length(pattern), ")")
    }
    unlist(
-      Map(f = grepl,
-          pattern,
-          x,
-          MoreArgs = list(ignore.case = FALSE, fixed = fixed, perl = !fixed)),
-      use.names = FALSE)
+      mapply(FUN = grepl,
+             x = x,
+             pattern = pattern,
+             fixed = fixed,
+             perl = !fixed,
+             MoreArgs = list(ignore.case = FALSE),
+             SIMPLIFY = FALSE,
+             USE.NAMES = FALSE)
+    )
  }
 }

@@ -117,6 +129,14 @@ like <- function(x, pattern, ignore.case = TRUE) {
  like(x, pattern, ignore.case = TRUE)
 }

+#' @rdname like
+#' @export
+"%unlike%" <- function(x, pattern) {
+  meet_criteria(x, allow_NA = TRUE)
+  meet_criteria(pattern, allow_NA = FALSE)
+  !like(x, pattern, ignore.case = TRUE)
+}
+
 #' @rdname like
 #' @export
 "%like_case%" <- function(x, pattern) {
@@ -124,3 +144,11 @@ like <- function(x, pattern, ignore.case = TRUE) {
  meet_criteria(pattern, allow_NA = FALSE)
  like(x, pattern, ignore.case = FALSE)
 }
+
+#' @rdname like
+#' @export
+"%unlike_case%" <- function(x, pattern) {
+  meet_criteria(x, allow_NA = TRUE)
+  meet_criteria(pattern, allow_NA = FALSE)
+  !like(x, pattern, ignore.case = FALSE)
+}
@@ -78,7 +78,7 @@
 #' 
 #' Custom guidelines can be set with the [custom_mdro_guideline()] function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.
 #' 
-#' If you are familiar with `case_when()` of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation':
+#' If you are familiar with the [`case_when()`][dplyr::case_when()] function of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule is written *before* the tilde (`~`) and the consequence of the rule is written *after* the tilde:
 #' 
 #' ```
 #' custom <- custom_mdro_guideline(CIP == "R" & age > 60 ~ "Elderly Type A",
@@ -102,10 +102,22 @@
 #' The outcome of the function can be used for the `guideline` argument in the [mdro()] function:
 #' 
 #' ```
-#' x <- mdro(example_isolates, guideline = custom)
+#' x <- mdro(example_isolates,
+#'           guideline = custom)
 #' table(x)
-#' #> Elderly Type A Elderly Type B       Negative 
-#' #>             43            891           1066 
+#' #>       Negative Elderly Type A Elderly Type B
+#' #>           1070            198            732
+#' ```
+#' 
+#' Rules can also be combined with other custom rules by using [c()]:
+#' 
+#' ```
+#' x <- mdro(example_isolates,
+#'           guideline = c(custom, 
+#'                         custom_mdro_guideline(ERY == "R" & age > 50 ~ "Elderly Type C")))
+#' table(x)
+#' #>       Negative Elderly Type A Elderly Type B Elderly Type C 
+#' #>            961            198            732            109
 #' ```
 #' 
 #' The rules set (the `custom` object in this case) could be exported to a shared file location using [saveRDS()] if you collaborate with multiple users. The custom rules set could then be imported using [readRDS()].
@@ -246,7 +258,7 @@ mdro <- function(x = NULL,
      txt <- word_wrap(txt)
      cat(txt, "\n", sep = "")
    }
-    x <- run_custom_mdro_guideline(x, guideline)
+    x <- run_custom_mdro_guideline(df = x, guideline = guideline, info = info)
    if (info.bak == TRUE) {
      cat(group_msg)
      if (sum(!is.na(x$MDRO)) == 0) {
@@ -299,7 +311,6 @@ mdro <- function(x = NULL,
    col_mo <- "mo"
  }
  stop_if(is.null(col_mo), "`col_mo` must be set")
-  stop_ifnot(col_mo %in% colnames(x), "column '", col_mo, "' (`col_mo`) not found")
  
  if (guideline$code == "cmi2012") {
    guideline$name <- "Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance."
@@ -749,7 +760,11 @@ mdro <- function(x = NULL,
      row_filter <- x[which(row_filter), "row_number", drop = TRUE]
      rows <- rows[rows %in% row_filter]
      x[rows, "MDRO"] <<- to
-      x[rows, "reason"] <<- paste0(any_all, " of the required antibiotics ", ifelse(any_all == "any", "is", "are"), " R")
+      x[rows, "reason"] <<- paste0(any_all, 
+                                   " of the required antibiotics ",
+                                   ifelse(any_all == "any", "is", "are"),
+                                   " R",
+                                   ifelse(!isTRUE(combine_SI), " or I", ""))
    }
  }
  trans_tbl2 <- function(txt, rows, lst) {
@@ -802,6 +817,9 @@ mdro <- function(x = NULL,
  }
  
  x[, col_mo] <- as.mo(as.character(x[, col_mo, drop = TRUE]))
+  # rename col_mo to prevent interference with joined columns
+  colnames(x)[colnames(x) == col_mo] <- ".col_mo"
+  col_mo <- ".col_mo"
  # join to microorganisms data set
  x <- left_join_microorganisms(x, by = col_mo)
  x$MDRO <- ifelse(!is.na(x$genus), 1, NA_integer_)
@@ -1015,7 +1033,10 @@ mdro <- function(x = NULL,
    # PDR (=4): all agents are R 
    x[which(x$classes_affected == 999 & x$classes_in_guideline == x$classes_available), "MDRO"] <- 4
    if (verbose == TRUE) {
-      x[which(x$MDRO == 4), "reason"] <- paste("all antibiotics in all", x$classes_in_guideline[which(x$MDRO == 4)], "classes were tested R or I")
+      x[which(x$MDRO == 4), "reason"] <- paste("all antibiotics in all",
+                                               x$classes_in_guideline[which(x$MDRO == 4)], 
+                                               "classes were tested R",
+                                               ifelse(!isTRUE(combine_SI), " or I", ""))
    }
    
    # not enough classes available
@@ -1378,7 +1399,12 @@ mdro <- function(x = NULL,
  # some more info on negative results
  if (verbose == TRUE) {
    if (guideline$code == "cmi2012") {
-      x[which(x$MDRO == 1 & !is.na(x$classes_affected)), "reason"] <- paste0(x$classes_affected[which(x$MDRO == 1 & !is.na(x$classes_affected))], " of ", x$classes_available[which(x$MDRO == 1 & !is.na(x$classes_affected))], " available classes contain R or I (3 required for MDR)")
+      x[which(x$MDRO == 1 & !is.na(x$classes_affected)), "reason"] <- paste0(x$classes_affected[which(x$MDRO == 1 & !is.na(x$classes_affected))],
+                                                                             " of ",
+                                                                             x$classes_available[which(x$MDRO == 1 & !is.na(x$classes_affected))],
+                                                                             " available classes contain R",
+                                                                             ifelse(!isTRUE(combine_SI), " or I", ""),
+                                                                             " (3 required for MDR)")
    } else {
      x[which(x$MDRO == 1), "reason"] <- "too few antibiotics are R"
    }
@@ -1419,8 +1445,10 @@ mdro <- function(x = NULL,
  }
  
  if (verbose == TRUE) {
+    colnames(x)[colnames(x) == col_mo] <- "microorganism"
+    x$microorganism <- mo_name(x$microorganism, language = NULL)
    x[, c("row_number",
-          col_mo,
+          "microorganism",
          "MDRO",
          "reason",
          "columns_nonsusceptible"), 
@@ -1434,6 +1462,8 @@ mdro <- function(x = NULL,
 #' @rdname mdro
 #' @export
 custom_mdro_guideline <- function(..., as_factor = TRUE) {
+  meet_criteria(as_factor, allow_class = "logical", has_length = 1)
+  
  dots <- tryCatch(list(...),
                   error = function(e) "error")
  stop_if(identical(dots, "error"),
@@ -1470,11 +1500,49 @@ custom_mdro_guideline <- function(..., as_factor = TRUE) {
  
  names(out) <- paste0("rule", seq_len(n_dots))
  out <- set_clean_class(out, new_class = c("custom_mdro_guideline", "list"))
-  attr(out, "values") <- c("Negative", vapply(FUN.VALUE = character(1), out, function(x) x$value))
+  attr(out, "values") <- unname(c("Negative", vapply(FUN.VALUE = character(1), unclass(out), function(x) x$value)))
  attr(out, "as_factor") <- as_factor
  out
 }

+#' @method c custom_mdro_guideline
+#' @noRd
+#' @export
+c.custom_mdro_guideline <- function(x, ..., as_factor = NULL) {
+  if (length(list(...)) == 0) {
+    return(x)
+  }
+  if (!is.null(as_factor)) {
+    meet_criteria(as_factor, allow_class = "logical", has_length = 1)
+  } else {
+    as_factor <- attributes(x)$as_factor
+  }
+  for (g in list(...)) {
+    stop_ifnot(inherits(g, "custom_mdro_guideline"),
+               "for combining custom MDRO guidelines, all rules must be created with `custom_mdro_guideline()`",
+               call = FALSE)
+    vals <- attributes(x)$values
+    if (!all(attributes(g)$values %in% vals)) {
+      vals <- unname(unique(c(vals, attributes(g)$values)))
+    }
+    attributes(g) <- NULL
+    x <- c(unclass(x), unclass(g))
+    attr(x, "values") <- vals
+  }
+  names(x) <- paste0("rule", seq_len(length(x)))
+  x <- set_clean_class(x, new_class = c("custom_mdro_guideline", "list"))
+  attr(x, "values") <- vals
+  attr(x, "as_factor") <- as_factor
+  x
+}
+
+#' @method as.list custom_mdro_guideline
+#' @noRd
+#' @export
+as.list.custom_mdro_guideline <- function(x, ...) {
+  c(x, ...)
+}
+
 #' @method print custom_mdro_guideline
 #' @export
 #' @noRd
@@ -1482,23 +1550,10 @@ print.custom_mdro_guideline <- function(x, ...) {
  cat("A set of custom MDRO rules:\n")
  for (i in seq_len(length(x))) {
    rule <- x[[i]]
-    rule$query <- gsub(" & ", font_black(font_italic(" and ")), rule$query, fixed = TRUE)
-    rule$query <- gsub(" | ", font_black(" or "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" + ", font_black(" plus "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" - ", font_black(" minus "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" / ", font_black(" divided by "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" * ", font_black(" times "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" == ", font_black(" is "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" > ", font_black(" is higher than "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" < ", font_black(" is lower than "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" >= ", font_black(" is higher than or equal to "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" <= ", font_black(" is lower than or equal to "), rule$query, fixed = TRUE)
-    rule$query <- gsub(" ^ ", font_black(" to the power of "), rule$query, fixed = TRUE)
-    # replace the black colour 'stops' with blue colour 'starts'
-    rule$query <- gsub("\033[39m", "\033[34m", as.character(rule$query), fixed = TRUE)
-    cat("  ", i, ". ", font_blue(rule$query), font_bold(" -> "), font_red(rule$value), "\n", sep = "")
+    rule$query <- format_custom_query_rule(rule$query)
+    cat("  ", i, ". ", font_bold("If "), font_blue(rule$query), font_bold(" then: "), font_red(rule$value), "\n", sep = "")
  }
-  cat("  ", i + 1, ". Otherwise", font_bold(" -> "), font_red(paste0("Negative")), "\n", sep = "")
+  cat("  ", i + 1, ". ", font_bold("Otherwise: "), font_red(paste0("Negative")), "\n", sep = "")
  cat("\nUnmatched rows will return ", font_red("NA"), ".\n", sep = "")
  if (isTRUE(attributes(x)$as_factor)) {
    cat("Results will be of class <factor>, with ordered levels: ", paste0(attributes(x)$values, collapse = " < "), "\n", sep = "")
@@ -1507,7 +1562,7 @@ print.custom_mdro_guideline <- function(x, ...) {
  }
 }

-run_custom_mdro_guideline <- function(df, guideline) {
+run_custom_mdro_guideline <- function(df, guideline, info) {
  n_dots <- length(guideline)
  stop_if(n_dots == 0, "no custom guidelines set", call = -2)
  out <- character(length = NROW(df))
@@ -1520,7 +1575,7 @@ run_custom_mdro_guideline <- function(df, guideline) {
                    })
    if (identical(qry, "error")) {
      warning_("in custom_mdro_guideline(): rule ", i, 
-               " (`", guideline[[i]]$query, "`) was ignored because of this error message: ",
+               " (`", as.character(guideline[[i]]$query), "`) was ignored because of this error message: ",
               pkg_env$err_msg,
               call = FALSE, 
               add_fn = font_red)
@@ -1529,9 +1584,16 @@ run_custom_mdro_guideline <- function(df, guideline) {
    stop_ifnot(is.logical(qry), "in custom_mdro_guideline(): rule ", i, " (`", guideline[[i]]$query, 
               "`) must return `TRUE` or `FALSE`, not ", 
               format_class(class(qry), plural = FALSE), call = FALSE)
+    
+    new_mdros <- which(qry == TRUE & out == "")
+    
+    if (info == TRUE) {
+      cat(word_wrap("- Custom MDRO rule ", i, ": `", as.character(guideline[[i]]$query),
+                    "` (", length(new_mdros),  " rows matched)"), "\n", sep = "")
+    }
    val <- guideline[[i]]$value
-    out[which(qry)] <- val
-    reasons[which(qry)] <- paste0("matched rule ", gsub("rule", "", names(guideline)[i]), ": ", as.character(guideline[[i]]$query))
+    out[new_mdros] <- val
+    reasons[new_mdros] <- paste0("matched rule ", gsub("rule", "", names(guideline)[i]), ": ", as.character(guideline[[i]]$query))
  }
  out[out == ""] <- "Negative"
  reasons[out == "Negative"] <- "no rules matched"
@@ -1540,8 +1602,7 @@ run_custom_mdro_guideline <- function(df, guideline) {
    out <- factor(out, levels = attributes(guideline)$values, ordered = TRUE)
  }
  
-  rsi_cols <- vapply(FUN.VALUE = logical(1), df, function(x) is.rsi(x))
-  columns_nonsusceptible <- as.data.frame(t(df[, rsi_cols] == "R"))
+  columns_nonsusceptible <- as.data.frame(t(df[, is.rsi(df)] == "R"))
  columns_nonsusceptible <- vapply(FUN.VALUE = character(1), 
                                   columns_nonsusceptible, 
                                   function(x) paste0(rownames(columns_nonsusceptible)[which(x)], collapse = " "))
@@ -133,7 +133,7 @@ as.mic <- function(x, na.rm = FALSE) {
    # keep only one zero before dot
    x <- gsub("0+[.]", "0.", x, perl = TRUE)
    # starting 00 is probably 0.0 if there's no dot yet
-    x[!x %like% "[.]"] <- gsub("^00", "0.0", x[!x %like% "[.]"])
+    x[x %unlike% "[.]"] <- gsub("^00", "0.0", x[!x %like% "[.]"])
    # remove last zeroes
    x <- gsub("([.].?)0+$", "\\1", x, perl = TRUE)
    x <- gsub("(.*[.])0+$", "\\10", x, perl = TRUE)
@@ -38,6 +38,7 @@
 #' @param reference_df a [data.frame] to be used for extra reference when translating `x` to a valid [`mo`]. See [set_mo_source()] and [get_mo_source()] to automate the usage of your own codes (e.g. used in your analysis or organisation).
 #' @param ignore_pattern a regular expression (case-insensitive) of which all matches in `x` must return `NA`. This can be convenient to exclude known non-relevant input and can also be set with the option `AMR_ignore_pattern`, e.g. `options(AMR_ignore_pattern = "(not reported|contaminated flora)")`.
 #' @param language language to translate text like "no growth", which defaults to the system language (see [get_locale()])
+#' @param info a [logical] to indicate if a progress bar should be printed if more than 25 items are to be coerced, defaults to `TRUE` only in interactive mode
 #' @param ... other arguments passed on to functions
 #' @rdname as.mo
 #' @aliases mo
@@ -161,6 +162,7 @@ as.mo <- function(x,
                  reference_df = get_mo_source(),
                  ignore_pattern = getOption("AMR_ignore_pattern"),
                  language = get_locale(),
+                  info = interactive(),
                  ...) {
  meet_criteria(x, allow_class = c("mo", "data.frame", "list", "character", "numeric", "integer", "factor"), allow_NA = TRUE)
  meet_criteria(Becker, allow_class = c("logical", "character"), has_length = 1)
@@ -169,7 +171,8 @@ as.mo <- function(x,
  meet_criteria(reference_df, allow_class = "data.frame", allow_NULL = TRUE)
  meet_criteria(ignore_pattern, allow_class = "character", has_length = 1, allow_NULL = TRUE)
  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-
+  meet_criteria(info, allow_class = "logical", has_length = 1)
+  
  check_dataset_integrity()

  if (tryCatch(all(x[!is.na(x)] %in% MO_lookup$mo)
@@ -227,6 +230,7 @@ as.mo <- function(x,
                     reference_df = reference_df,
                     ignore_pattern = ignore_pattern,
                     language = language,
+                     info = info,
                     ...)
  }

@@ -253,6 +257,7 @@ exec_as.mo <- function(x,
                       Lancefield = FALSE,
                       allow_uncertain = TRUE,
                       reference_df = get_mo_source(),
+                       info = interactive(),
                       property = "mo",
                       initial_search = TRUE,
                       dyslexia_mode = FALSE,
@@ -600,7 +605,7 @@ exec_as.mo <- function(x,
      }
      
      if (initial_search == TRUE) {
-        progress <- progress_ticker(n = length(x[!already_known]), n_min = 25) # start if n >= 25
+        progress <- progress_ticker(n = length(x[!already_known]), n_min = 25, print = info) # start if n >= 25
        on.exit(close(progress))
      }
      
@@ -703,7 +708,7 @@ exec_as.mo <- function(x,
        
        # check for very small input, but ignore the O antigens of E. coli
        if (nchar(gsub("[^a-zA-Z]", "", x_trimmed[i])) < 3
-            & !toupper(x_backup_without_spp[i]) %like_case% "O?(26|103|104|104|111|121|145|157)") {
+            & toupper(x_backup_without_spp[i]) %unlike_case% "O?(26|103|104|104|111|121|145|157)") {
          # fewer than 3 chars and not looked for species, add as failure
          x[i] <- lookup(mo == "UNKNOWN")
          if (initial_search == TRUE) {
@@ -855,7 +860,7 @@ exec_as.mo <- function(x,
            x[i] <- lookup(genus == "Salmonella", uncertainty = -1)
            next
          } else if (x_backup[i] %like_case% "[sS]almonella [A-Z][a-z]+ ?.*" &
-                     !x_backup[i] %like% "t[iy](ph|f)[iy]") {
+                     x_backup[i] %unlike% "t[iy](ph|f)[iy]") {
            # Salmonella with capital letter species like "Salmonella Goettingen" - they're all S. enterica
            # except for S. typhi, S. paratyphi, S. typhimurium
            x[i] <- lookup(fullname == "Salmonella enterica", uncertainty = -1)
@@ -911,7 +916,7 @@ exec_as.mo <- function(x,
          # FIRST TRY FULLNAMES AND CODES ----
          # if only genus is available, return only genus
          
-          if (all(!c(x[i], b.x_trimmed) %like_case% " ")) {
+          if (all(c(x[i], b.x_trimmed) %unlike_case% " ")) {
            found <- lookup(fullname_lower %in% c(h.x_species, i.x_trimmed_species),
                            haystack = data_to_check)
            if (!is.na(found)) {
@@ -1118,8 +1123,8 @@ exec_as.mo <- function(x,
              if (isTRUE(debug)) {
                cat(font_bold("\n[ UNCERTAINTY LEVEL", now_checks_for_uncertainty_level, "] (3) look for genus only, part of name\n"))
              }
-              if (nchar(g.x_backup_without_spp) > 4 & !b.x_trimmed %like_case% " ") {
-                if (!b.x_trimmed %like_case% "^[A-Z][a-z]+") {
+              if (nchar(g.x_backup_without_spp) > 4 & b.x_trimmed %unlike_case% " ") {
+                if (b.x_trimmed %unlike_case% "^[A-Z][a-z]+") {
                  if (isTRUE(debug)) {
                    message("Running '", paste(b.x_trimmed, "species"), "'")
                  }
@@ -1263,7 +1268,7 @@ exec_as.mo <- function(x,
                                        stringsAsFactors = FALSE)
                return(found)
              }
-              if (b.x_trimmed %like_case% "(fungus|fungi)" & !b.x_trimmed %like_case% "fungiphrya") {
+              if (b.x_trimmed %like_case% "(fungus|fungi)" & b.x_trimmed %unlike_case% "fungiphrya") {
                found <- "F_FUNGUS"
                found_result <- found
                found <- lookup(mo == found)
@@ -1654,10 +1659,28 @@ pillar_shaft.mo <- function(x, ...) {
  out[!is.na(x)] <- gsub("^([A-Z]+_)(.*)", paste0(font_subtle("\\1"), "\\2"), out[!is.na(x)], perl = TRUE)
  # and grey out every _
  out[!is.na(x)] <- gsub("_", font_subtle("_"), out[!is.na(x)])
-
+  
  # markup NA and UNKNOWN
  out[is.na(x)] <- font_na("  NA")
  out[x == "UNKNOWN"] <- font_na("  UNKNOWN")
+  
+  if (!all(x[!is.na(x)] %in% MO_lookup$mo)) {
+    # markup old mo codes
+    out[!x %in% MO_lookup$mo] <- font_italic(font_na(x[!x %in% MO_lookup$mo], 
+                                                     collapse = NULL),
+                                             collapse = NULL)
+    # throw a warning with the affected column name
+    mo <- tryCatch(search_type_in_df(get_current_data(arg_name = "x", call = 0), type = "mo", info = FALSE),
+                   error = function(e) NULL)
+    if (!is.null(mo)) {
+      col <- paste0("Column '", mo, "'")
+    } else {
+      col <- "The data"
+    }
+    warning_(col, " contains old microbial codes (from a previous AMR package version). ",
+             "Please update your MO codes with `as.mo()`.",
+             call = FALSE)
+  }

  # make it always fit exactly
  max_char <- max(nchar(x))
@@ -1753,11 +1776,16 @@ summary.mo <- function(object, ...) {
 #' @export
 #' @noRd
 as.data.frame.mo <- function(x, ...) {
+  if (!all(x[!is.na(x)] %in% MO_lookup$mo)) {
+    warning_("The data contains old microbial codes (from a previous AMR package version). ",
+             "Please update your MO codes with `as.mo()`.",
+             call = FALSE)
+  }
  nm <- deparse1(substitute(x))
  if (!"nm" %in% names(list(...))) {
-    as.data.frame.vector(as.mo(x), ..., nm = nm)
+    as.data.frame.vector(x, ..., nm = nm)
  } else {
-    as.data.frame.vector(as.mo(x), ...)
+    as.data.frame.vector(x, ...)
  }
 }

@@ -1875,6 +1903,7 @@ print.mo_uncertainties <- function(x, ...) {
                           collapse = "")
      # after strwrap, make taxonomic names italic
      candidates <- gsub("([A-Za-z]+)", font_italic("\\1"), candidates, perl = TRUE)
+      candidates <- gsub(font_italic("and"), "and", candidates, fixed = TRUE)
      candidates <- gsub(paste(font_italic(c("Also", "matched"), collapse = NULL), collapse = " "),
                         "Also matched",
                         candidates, fixed = TRUE)
@@ -2028,13 +2057,15 @@ replace_old_mo_codes <- function(x, property) {
    x[which(!is.na(matched))] <- mo_new[which(!is.na(matched))]
    n_matched <- length(matched[!is.na(matched)])
    if (property != "mo") {
-      message_(font_blue("The input contained old microbial codes (from previous package versions). Please update your MO codes with `as.mo()`."))
+      message_(font_blue(paste0("The input contained ", n_matched,
+                                " old microbial code", ifelse(n_matched == 1, "", "s"),
+                                " (from a previous AMR package version). Please update your MO codes with `as.mo()`.")))
    } else {
-      if (n_matched == 1) {
-        message_(font_blue("1 old microbial code (from previous package versions) was updated to a current used MO code."))
-      } else {
-        message_(font_blue(n_matched, "old microbial codes (from previous package versions) were updated to current used MO codes.")) 
-      }
+      message_(font_blue(paste0(n_matched, " old microbial code", ifelse(n_matched == 1, "", "s"), 
+                                " (from a previous AMR package version) ", 
+                                ifelse(n_matched == 1, "was", "were"), 
+                                " updated to ", ifelse(n_matched == 1, "a ", ""), 
+                                "currently used MO code", ifelse(n_matched == 1, "", "s"), ".")))
    }
  }
  x
@@ -44,7 +44,7 @@
 #' * \ifelse{html}{\out{<i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
 #' * \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
 #' 
-#' The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. **Group 1** (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is *Enterococcus*, *Staphylococcus* or *Streptococcus*. This group consequently contains all common Gram-negative bacteria, such as *Pseudomonas* and *Legionella* and all species within the order Enterobacterales. **Group 2** consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is *Absidia*, *Acremonium*, *Actinotignum*, *Alternaria*, *Anaerosalibacter*, *Apophysomyces*, *Arachnia*, *Aspergillus*, *Aureobacterium*, *Aureobasidium*, *Bacteroides*, *Basidiobolus*, *Beauveria*, *Blastocystis*, *Branhamella*, *Calymmatobacterium*, *Candida*, *Capnocytophaga*, *Catabacter*, *Chaetomium*, *Chryseobacterium*, *Chryseomonas*, *Chrysonilia*, *Cladophialophora*, *Cladosporium*, *Conidiobolus*, *Cryptococcus*, *Curvularia*, *Exophiala*, *Exserohilum*, *Flavobacterium*, *Fonsecaea*, *Fusarium*, *Fusobacterium*, *Hendersonula*, *Hypomyces*, *Koserella*, *Lelliottia*, *Leptosphaeria*, *Leptotrichia*, *Malassezia*, *Malbranchea*, *Mortierella*, *Mucor*, *Mycocentrospora*, *Mycoplasma*, *Nectria*, *Ochroconis*, *Oidiodendron*, *Phoma*, *Piedraia*, *Pithomyces*, *Pityrosporum*, *Prevotella*, *Pseudallescheria*, *Rhizomucor*, *Rhizopus*, *Rhodotorula*, *Scolecobasidium*, *Scopulariopsis*, *Scytalidium*,*Sporobolomyces*, *Stachybotrys*, *Stomatococcus*, *Treponema*, *Trichoderma*, *Trichophyton*, *Trichosporon*, *Tritirachium* or *Ureaplasma*. **Group 3** consists of all other microorganisms.
+#' The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. **Group 1** (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is *Enterococcus*, *Staphylococcus* or *Streptococcus*. This group consequently contains all common Gram-negative bacteria, such as *Pseudomonas* and *Legionella* and all species within the order Enterobacterales. **Group 2** consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is *Absidia*, *Acremonium*, *Actinotignum*, *Alternaria*, *Anaerosalibacter*, *Apophysomyces*, *Arachnia*, *Aspergillus*, *Aureobacterium*, *Aureobasidium*, *Bacteroides*, *Basidiobolus*, *Beauveria*, *Blastocystis*, *Branhamella*, *Calymmatobacterium*, *Candida*, *Capnocytophaga*, *Catabacter*, *Chaetomium*, *Chryseobacterium*, *Chryseomonas*, *Chrysonilia*, *Cladophialophora*, *Cladosporium*, *Conidiobolus*, *Cryptococcus*, *Curvularia*, *Exophiala*, *Exserohilum*, *Flavobacterium*, *Fonsecaea*, *Fusarium*, *Fusobacterium*, *Hendersonula*, *Hypomyces*, *Koserella*, *Lelliottia*, *Leptosphaeria*, *Leptotrichia*, *Malassezia*, *Malbranchea*, *Mortierella*, *Mucor*, *Mycocentrospora*, *Mycoplasma*, *Nectria*, *Ochroconis*, *Oidiodendron*, *Phoma*, *Piedraia*, *Pithomyces*, *Pityrosporum*, *Prevotella*, *Pseudallescheria*, *Rhizomucor*, *Rhizopus*, *Rhodotorula*, *Scolecobasidium*, *Scopulariopsis*, *Scytalidium*, *Sporobolomyces*, *Stachybotrys*, *Stomatococcus*, *Treponema*, *Trichoderma*, *Trichophyton*, *Trichosporon*, *Tritirachium* or *Ureaplasma*. **Group 3** consists of all other microorganisms.
 #' 
 #' All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., `"E. coli"` will return the microbial ID of *Escherichia coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Escherichia coli"), 3)`}, a highly prevalent microorganism found in humans) and not *Entamoeba coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Entamoeba coli"), 3)`}, a less prevalent microorganism in humans), although the latter would alphabetically come first. 
 #' @export
@@ -723,20 +723,13 @@ mo_validate <- function(x, property, language, ...) {
    # special case for mo_* functions where class is already <mo>
    return(MO_lookup[match(x, MO_lookup$mo), property, drop = TRUE])
  }
-
+  
  # try to catch an error when inputting an invalid argument
  # so the 'call.' can be set to FALSE
  tryCatch(x[1L] %in% MO_lookup[1, property, drop = TRUE],
           error = function(e) stop(e$message, call. = FALSE))
-  
-  if (is.mo(x)
-      & !Becker %in% c(TRUE, "all")
-      & !Lancefield %in% c(TRUE, "all")) {
-    # this will not reset mo_uncertainties and mo_failures
-    # because it's already a valid MO
-    x <- exec_as.mo(x, property = property, initial_search = FALSE, language = language, ...)
-  } else if (!all(x %in% MO_lookup[, property, drop = TRUE])
-             | has_Becker_or_Lancefield) {
+
+  if (!all(x[!is.na(x)] %in% MO_lookup[, property, drop = TRUE]) | has_Becker_or_Lancefield) {
    x <- exec_as.mo(x, property = property, language = language, ...)
  }
  
@@ -93,6 +93,14 @@ plot.mic <- function(x,
  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
  meet_criteria(expand, allow_class = "logical", has_length = 1)
  
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
  if (length(colours_RSI) == 1) {
    colours_RSI <- rep(colours_RSI, 3)
  }
@@ -135,13 +143,14 @@ plot.mic <- function(x,
      legend_txt <- c(legend_txt, "Resistant")
      legend_col <- c(legend_col, colours_RSI[1])
    }
-    legend("top", 
+    legend("top",
           x.intersp = 0.5,
           legend = translate_AMR(legend_txt, language = language),
           fill = legend_col,
           horiz = TRUE,
-           cex = 0.75, 
-           box.lwd = 0, 
+           cex = 0.75,
+           box.lwd = 0,
+           box.col = "#FFFFFF55",
           bg = "#FFFFFF55")
  }
 }
@@ -170,6 +179,14 @@ barplot.mic <- function(height,
  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
  meet_criteria(expand, allow_class = "logical", has_length = 1)
  
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
  main <- gsub(" +", " ", paste0(main, collapse = " "))
  
  plot(x = height,
@@ -209,6 +226,14 @@ ggplot.mic <- function(data,
  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
  meet_criteria(expand, allow_class = "logical", has_length = 1)
  
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
  if ("main" %in% names(list(...))) {
    title <- list(...)$main
  }
@@ -285,6 +310,14 @@ plot.disk <- function(x,
  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
  meet_criteria(expand, allow_class = "logical", has_length = 1)
  
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
  if (length(colours_RSI) == 1) {
    colours_RSI <- rep(colours_RSI, 3)
  }
@@ -333,8 +366,9 @@ plot.disk <- function(x,
           legend = translate_AMR(legend_txt, language = language),
           fill = legend_col,
           horiz = TRUE,
-           cex = 0.75, 
-           box.lwd = 0, 
+           cex = 0.75,
+           box.lwd = 0,
+           box.col = "#FFFFFF55",
           bg = "#FFFFFF55")
  }
 }
@@ -363,6 +397,14 @@ barplot.disk <- function(height,
  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
  meet_criteria(expand, allow_class = "logical", has_length = 1)
  
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
  main <- gsub(" +", " ", paste0(main, collapse = " "))
  
  plot(x = height,
@@ -402,6 +444,14 @@ ggplot.disk <- function(data,
  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
  meet_criteria(expand, allow_class = "logical", has_length = 1)
  
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
  if ("main" %in% names(list(...))) {
    title <- list(...)$main
  }
@@ -454,79 +504,6 @@ ggplot.disk <- function(data,
    ggplot2::labs(title = title, x = xlab, y = ylab, subtitle = cols_sub$sub)
 }

-plot_prepare_table <- function(x, expand) {
-  if (is.mic(x)) {
-    if (expand == TRUE) {
-      # expand range for MIC by adding factors of 2 from lowest to highest so all MICs in between also print
-      extra_range <- max(x) / 2
-      while (min(extra_range) / 2 > min(x)) {
-        extra_range <- c(min(extra_range) / 2, extra_range)
-      }
-      nms <- extra_range
-      extra_range <- rep(0, length(extra_range))
-      names(extra_range) <- nms
-      x <- table(droplevels(x, as.mic = FALSE))
-      extra_range <- extra_range[!names(extra_range) %in% names(x)]
-      x <- as.table(c(x, extra_range))
-    } else {
-      x <- table(droplevels(x, as.mic = FALSE))
-    }
-    x <- x[order(as.double(as.mic(names(x))))]
-  } else if (is.disk(x)) {
-    if (expand == TRUE) {
-      # expand range for disks from lowest to highest so all mm's in between also print
-      extra_range <- rep(0, max(x) - min(x) - 1)
-      names(extra_range) <- seq(min(x) + 1, max(x) - 1)
-      x <- table(x)
-      extra_range <- extra_range[!names(extra_range) %in% names(x)]
-      x <- as.table(c(x, extra_range))
-    } else {
-      x <- table(x)
-    }
-    x <- x[order(as.double(names(x)))]
-  }
-  as.table(x)
-}
-
-plot_name_of_I <- function(guideline) {
-  if (!guideline %like% "CLSI" && as.double(gsub("[^0-9]+", "", guideline)) >= 2019) {
-    # interpretation since 2019
-    "Incr. exposure"
-  } else {
-    # interpretation until 2019
-    "Intermediate"
-  }
-}
-
-plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_RSI, fn, language, ...) {
-  guideline <- get_guideline(guideline, AMR::rsi_translation)
-  if (!is.null(mo) && !is.null(ab)) {
-    # interpret and give colour based on MIC values
-    mo <- as.mo(mo)
-    ab <- as.ab(ab)
-    rsi <- suppressWarnings(suppressMessages(as.rsi(fn(names(x)), mo = mo, ab = ab, guideline = guideline, ...)))
-    cols <- character(length = length(rsi))
-    cols[is.na(rsi)] <- "#BEBEBE"
-    cols[rsi == "R"] <- colours_RSI[1]
-    cols[rsi == "S"] <- colours_RSI[2]
-    cols[rsi == "I"] <- colours_RSI[3]
-    moname <- mo_name(mo, language = language)
-    abname <- ab_name(ab, language = language)
-    if (all(cols == "#BEBEBE")) {
-      message_("No ", guideline, " interpretations found for ", 
-               ab_name(ab, language = NULL, tolower = TRUE), " in ", moname)
-      guideline_txt <- ""
-    } else {
-      guideline_txt <- paste0("(", guideline, ")")
-    }
-    sub <- bquote(.(abname)~"in"~italic(.(moname))~.(guideline_txt))
-  } else {
-    cols <- "#BEBEBE"
-    sub <- NULL
-  }
-  list(cols = cols, count = as.double(x), sub = sub, guideline = guideline)
-}
-
 #' @method plot rsi
 #' @export
 #' @importFrom graphics plot text axis
@@ -599,6 +576,14 @@ barplot.rsi <- function(height,
  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
  meet_criteria(expand, allow_class = "logical", has_length = 1)
  
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
  if (length(colours_RSI) == 1) {
    colours_RSI <- rep(colours_RSI, 3)
  }
@@ -624,6 +609,7 @@ ggplot.rsi <- function(data,
                       xlab = "Antimicrobial Interpretation",
                       ylab = "Frequency",
                       colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
+                       language = get_locale(),
                       ...) {
  stop_ifnot_installed("ggplot2")
  meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
@@ -631,6 +617,14 @@ ggplot.rsi <- function(data,
  meet_criteria(xlab, allow_class = "character", has_length = 1)
  meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
  
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_AMR(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_AMR(xlab, language = language)
+  }
+  
  if ("main" %in% names(list(...))) {
    title <- list(...)$main
  }
@@ -658,3 +652,76 @@ ggplot.rsi <- function(data,
    ggplot2::labs(title = title, x = xlab, y = ylab) +
    ggplot2::theme(legend.position = "none")
 }
+
+plot_prepare_table <- function(x, expand) {
+  if (is.mic(x)) {
+    if (expand == TRUE) {
+      # expand range for MIC by adding factors of 2 from lowest to highest so all MICs in between also print
+      extra_range <- max(x) / 2
+      while (min(extra_range) / 2 > min(x)) {
+        extra_range <- c(min(extra_range) / 2, extra_range)
+      }
+      nms <- extra_range
+      extra_range <- rep(0, length(extra_range))
+      names(extra_range) <- nms
+      x <- table(droplevels(x, as.mic = FALSE))
+      extra_range <- extra_range[!names(extra_range) %in% names(x)]
+      x <- as.table(c(x, extra_range))
+    } else {
+      x <- table(droplevels(x, as.mic = FALSE))
+    }
+    x <- x[order(as.double(as.mic(names(x))))]
+  } else if (is.disk(x)) {
+    if (expand == TRUE) {
+      # expand range for disks from lowest to highest so all mm's in between also print
+      extra_range <- rep(0, max(x) - min(x) - 1)
+      names(extra_range) <- seq(min(x) + 1, max(x) - 1)
+      x <- table(x)
+      extra_range <- extra_range[!names(extra_range) %in% names(x)]
+      x <- as.table(c(x, extra_range))
+    } else {
+      x <- table(x)
+    }
+    x <- x[order(as.double(names(x)))]
+  }
+  as.table(x)
+}
+
+plot_name_of_I <- function(guideline) {
+  if (guideline %unlike% "CLSI" && as.double(gsub("[^0-9]+", "", guideline)) >= 2019) {
+    # interpretation since 2019
+    "Incr. exposure"
+  } else {
+    # interpretation until 2019
+    "Intermediate"
+  }
+}
+
+plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_RSI, fn, language, ...) {
+  guideline <- get_guideline(guideline, AMR::rsi_translation)
+  if (!is.null(mo) && !is.null(ab)) {
+    # interpret and give colour based on MIC values
+    mo <- as.mo(mo)
+    ab <- as.ab(ab)
+    rsi <- suppressWarnings(suppressMessages(as.rsi(fn(names(x)), mo = mo, ab = ab, guideline = guideline, ...)))
+    cols <- character(length = length(rsi))
+    cols[is.na(rsi)] <- "#BEBEBE"
+    cols[rsi == "R"] <- colours_RSI[1]
+    cols[rsi == "S"] <- colours_RSI[2]
+    cols[rsi == "I"] <- colours_RSI[3]
+    moname <- mo_name(mo, language = language)
+    abname <- ab_name(ab, language = language)
+    if (all(cols == "#BEBEBE")) {
+      message_("No ", guideline, " interpretations found for ", 
+               ab_name(ab, language = NULL, tolower = TRUE), " in ", moname)
+      guideline_txt <- ""
+    } else {
+      guideline_txt <- paste0("(", guideline, ")")
+    }
+    sub <- bquote(.(abname)~"-"~italic(.(moname))~.(guideline_txt))
+  } else {
+    cols <- "#BEBEBE"
+    sub <- NULL
+  }
+  list(cols = cols, count = as.double(x), sub = sub, guideline = guideline)
+}
@@ -263,9 +263,9 @@ as.rsi.default <- function(x, ...) {
    x[x == 2] <- "I"
    x[x == 3] <- "R"
    
-  } else if (!all(is.na(x)) && !identical(levels(x), c("S", "I", "R"))) {
-    
-    if (!any(x %like% "(R|S|I)", na.rm = TRUE)) {
+  } else if (!all(is.na(x)) && !identical(levels(x), c("S", "I", "R")) && !all(x %in% c("R", "S", "I", NA))) {
+
+    if (all(x %unlike% "(R|S|I)", na.rm = TRUE)) {
      # check if they are actually MICs or disks
      if (all_valid_mics(x)) {
        warning_("The input seems to be MIC values. Transform them with `as.mic()` before running `as.rsi()` to interpret them.")
@@ -683,7 +683,7 @@ get_guideline <- function(guideline, reference_data) {
  if (guideline_param %in% c("CLSI", "EUCAST")) {
    guideline_param <- rev(sort(subset(reference_data, guideline %like% guideline_param)$guideline))[1L]
  }
-  if (!guideline_param %like% " ") {
+  if (guideline_param %unlike% " ") {
    # like 'EUCAST2020', should be 'EUCAST 2020'
    guideline_param <- gsub("([a-z]+)([0-9]+)", "\\1 \\2", guideline_param, ignore.case = TRUE)
  }
@@ -776,7 +776,7 @@ exec_as.rsi <- function(method,
    any_is_intrinsic_resistant <- any_is_intrinsic_resistant | is_intrinsic_r
    
    if (isTRUE(add_intrinsic_resistance) & is_intrinsic_r) {
-      if (!guideline_coerced %like% "EUCAST") {
+      if (guideline_coerced %unlike% "EUCAST") {
        if (message_not_thrown_before("as.rsi2")) {
          warning_("Using 'add_intrinsic_resistance' is only useful when using EUCAST guidelines, since the rules for intrinsic resistance are based on EUCAST.", call = FALSE)
          remember_thrown_message("as.rsi2")
@@ -1027,10 +1027,8 @@ summary.rsi <- function(object, ...) {
 #' @method c rsi
 #' @export
 #' @noRd
-c.rsi <- function(x, ...) {
-  y <- unlist(lapply(list(...), as.character))
-  x <- as.character(x)
-  as.rsi(c(x, y))
+c.rsi <- function(...) {
+  as.rsi(unlist(lapply(list(...), as.character)))
 }

 #' @method unique rsi
@@ -157,11 +157,13 @@ translate_AMR <- function(from, language = get_locale(), only_unknown = FALSE, a
  df_trans$regular_expr[is.na(df_trans$regular_expr)] <- FALSE
  
  # check if text to look for is in one of the patterns
-  any_form_in_patterns <- tryCatch(any(from_unique %like% paste0("(", paste(df_trans$pattern, collapse = "|"), ")")),
-                                   error = function(e) {
-                                     warning_("Translation not possible. Please open an issue on GitHub (https://github.com/msberends/AMR/issues).", call = FALSE)
-                                     return(FALSE)
-                                   })
+  any_form_in_patterns <- tryCatch(
+    any(from_unique %like% paste0("(", paste(gsub(" +\\(.*", "", df_trans$pattern), collapse = "|"), ")")),
+    error = function(e) {
+      warning_("Translation not possible. Please open an issue on GitHub (https://github.com/msberends/AMR/issues).", call = FALSE)
+      return(FALSE)
+    })
+  
  if (NROW(df_trans) == 0 | !any_form_in_patterns) {
    return(from)
  }
@@ -170,7 +172,7 @@ translate_AMR <- function(from, language = get_locale(), only_unknown = FALSE, a
         function(i) from_unique_translated <<- gsub(pattern = df_trans$pattern[i],
                                                     replacement = df_trans[i, language, drop = TRUE],
                                                     x = from_unique_translated,
-                                                     ignore.case = !df_trans$case_sensitive[i], 
+                                                     ignore.case = !df_trans$case_sensitive[i] & df_trans$regular_expr[i], 
                                                     fixed = !df_trans$regular_expr[i],
                                                     perl = df_trans$regular_expr[i]))
  
@@ -61,20 +61,3 @@ pkg_env$mo_failed <- character(0)
    }
  }, silent = TRUE)
 }
-
-.onAttach <- function(...) {
-  # show notice in 10% of cases in interactive session
-  if (!interactive() || stats::runif(1) > 0.1 || isTRUE(as.logical(getOption("AMR_silentstart", FALSE)))) {
-    return()
-  }
-  packageStartupMessage(word_wrap("Thank you for using the AMR package! ",
-                                  "If you have a minute, please anonymously fill in this short questionnaire to improve the package and its functionalities: ",
-                                  font_blue("https://msberends.github.io/AMR/survey.html\n"),
-                                  "[prevent his notice with ",
-                                  font_bold("suppressPackageStartupMessages(library(AMR))"),
-                                  " or use ",
-                                  font_bold("options(AMR_silentstart = TRUE)"), "]"))
-}
-
-
-
@@ -143,6 +143,7 @@ reference:
    - "`as.mic`"
    - "`as.disk`"
    - "`eucast_rules`"
+    - "`custom_eucast_rules`"
    
  - title: "Analysing data: antimicrobial resistance"
    desc: >
@@ -154,7 +155,7 @@ reference:
    - "`count`"
    - "`is_new_episode`"
    - "`first_isolate`"
-    - "`key_antibiotics`"
+    - "`key_antimicrobials`"
    - "`mdro`"
    - "`count`"
    - "`plot`"
@@ -134,7 +134,7 @@ create_intr_resistance <- function() {



-# Save internal data sets to R/sysdata.rda --------------------------------
+# Save internal data to R/sysdata.rda -------------------------------------

 # See 'data-raw/eucast_rules.tsv' for the EUCAST reference file
 eucast_rules_file <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
@@ -188,6 +188,35 @@ AB_lookup <- create_AB_lookup()
 MO_lookup <- create_MO_lookup()
 MO.old_lookup <- create_MO.old_lookup()

+# antibiotic groups
+# (these will also be used for eucast_rules() and understanding data-raw/eucast_rules.tsv)
+globalenv_before_ab <- c(ls(envir = globalenv()), "globalenv_before_ab")
+AMINOGLYCOSIDES <- antibiotics %>% filter(group %like% "aminoglycoside") %>% pull(ab)
+AMINOPENICILLINS <- as.ab(c("AMP", "AMX"))
+CARBAPENEMS <- antibiotics %>% filter(group %like% "carbapenem") %>% pull(ab)
+CEPHALOSPORINS <- antibiotics %>% filter(group %like% "cephalosporin") %>% pull(ab)
+CEPHALOSPORINS_1ST <- antibiotics %>% filter(group %like% "cephalosporin.*1") %>% pull(ab)
+CEPHALOSPORINS_2ND <- antibiotics %>% filter(group %like% "cephalosporin.*2") %>% pull(ab)
+CEPHALOSPORINS_3RD <- antibiotics %>% filter(group %like% "cephalosporin.*3") %>% pull(ab)
+CEPHALOSPORINS_EXCEPT_CAZ <- CEPHALOSPORINS[CEPHALOSPORINS != "CAZ"]
+FLUOROQUINOLONES <- antibiotics %>% filter(atc_group2 %like% "fluoroquinolone") %>% pull(ab)
+LIPOGLYCOPEPTIDES <- as.ab(c("DAL", "ORI", "TLV")) # dalba/orita/tela
+GLYCOPEPTIDES <- antibiotics %>% filter(group %like% "glycopeptide") %>% pull(ab)
+GLYCOPEPTIDES_EXCEPT_LIPO <- GLYCOPEPTIDES[!GLYCOPEPTIDES %in% LIPOGLYCOPEPTIDES]
+LINCOSAMIDES <- antibiotics %>% filter(atc_group2 %like% "lincosamide") %>% pull(ab) %>% c("PRL")
+MACROLIDES <- antibiotics %>% filter(atc_group2 %like% "macrolide") %>% pull(ab)
+OXAZOLIDINONES <- antibiotics %>% filter(group %like% "oxazolidinone") %>% pull(ab)
+PENICILLINS <- antibiotics %>% filter(group %like% "penicillin") %>% pull(ab)
+POLYMYXINS <- antibiotics %>% filter(group %like% "polymyxin") %>% pull(ab)
+STREPTOGRAMINS <- antibiotics %>% filter(atc_group2 %like% "streptogramin") %>% pull(ab)
+TETRACYCLINES <- antibiotics %>% filter(atc_group2 %like% "tetracycline") %>% pull(ab)
+TETRACYCLINES_EXCEPT_TGC <- TETRACYCLINES[TETRACYCLINES != "TGC"]
+UREIDOPENICILLINS <- as.ab(c("PIP", "TZP", "AZL", "MEZ"))
+BETALACTAMS <- c(PENICILLINS, CEPHALOSPORINS, CARBAPENEMS)
+
+DEFINED_AB_GROUPS <- ls(envir = globalenv())
+DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab]
+
 # Export to package as internal data ----
 usethis::use_data(eucast_rules_file, 
                  translations_file,
@@ -199,6 +228,29 @@ usethis::use_data(eucast_rules_file,
                  AB_lookup,
                  MO_lookup,
                  MO.old_lookup,
+                  AMINOGLYCOSIDES,
+                  AMINOPENICILLINS,
+                  CARBAPENEMS,
+                  CEPHALOSPORINS,
+                  CEPHALOSPORINS_1ST,
+                  CEPHALOSPORINS_2ND,
+                  CEPHALOSPORINS_3RD,
+                  CEPHALOSPORINS_EXCEPT_CAZ,
+                  FLUOROQUINOLONES,
+                  LIPOGLYCOPEPTIDES,
+                  GLYCOPEPTIDES,
+                  GLYCOPEPTIDES_EXCEPT_LIPO,
+                  LINCOSAMIDES,
+                  MACROLIDES,
+                  OXAZOLIDINONES,
+                  PENICILLINS,
+                  POLYMYXINS,
+                  STREPTOGRAMINS,
+                  TETRACYCLINES,
+                  TETRACYCLINES_EXCEPT_TGC,
+                  UREIDOPENICILLINS,
+                  BETALACTAMS,
+                  DEFINED_AB_GROUPS,
                  internal = TRUE,
                  overwrite = TRUE,
                  version = 2,
@@ -1,7 +1,7 @@
 # -------------------------------------------------------------------------------------------------------------------------------
 # For editing this EUCAST reference file, these values can all be used for targeting antibiotics:
-# 'all_betalactams', 'aminoglycosides', 'aminopenicillins', 'carbapenems', 'cephalosporins', 'cephalosporins_1st', 'cephalosporins_2nd', 'cephalosporins_3rd', 'cephalosporins_except_CAZ',
-# 'fluoroquinolones', 'glycopeptides', 'lincosamides', 'lipoglycopeptides', 'macrolides', 'oxazolidinones', 'polymyxins', 'streptogramins', 'tetracyclines', 'ureidopenicillins',
+# 'betalactams', 'aminoglycosides', 'aminopenicillins', 'carbapenems', 'cephalosporins', 'cephalosporins_1st', 'cephalosporins_2nd', 'cephalosporins_3rd', 'cephalosporins_except_CAZ',
+# 'fluoroquinolones', 'glycopeptides', 'glycopeptides_except_lipo', 'lincosamides', 'lipoglycopeptides', 'macrolides', 'oxazolidinones', 'polymyxins', 'streptogramins', 'tetracyclines', 'tetracyclines_except_TGC', 'ureidopenicillins',
 # and all separate EARS-Net letter codes like 'AMC'. They can be separated by comma: 'AMC, fluoroquinolones'.
 # The 'if_mo_property' column can be any column name from the AMR::microorganisms data set, or "genus_species" or "gramstain".
 # The like.is.one_of column must be 'like' or 'is' or 'one_of' ('like' will read the 'this_value' column as regular expression)
@@ -14,7 +14,7 @@ order	is	Enterobacterales	AMP	I	AMX	I	Enterobacterales (Order)	Breakpoints	10
 order	is	Enterobacterales	AMP	R	AMX	R	Enterobacterales (Order)	Breakpoints	10	
 genus	is	Staphylococcus	PEN, FOX	S	AMP, AMX, PIP, TIC	S	Staphylococcus	Breakpoints	10	
 genus	is	Staphylococcus	PEN, FOX	R, S	OXA, FLC	S	Staphylococcus	Breakpoints	10	
-genus	is	Staphylococcus	FOX	R	all_betalactams	R	Staphylococcus	Breakpoints	10	
+genus	is	Staphylococcus	FOX	R	betalactams	R	Staphylococcus	Breakpoints	10	
 genus_species	is	Staphylococcus saprophyticus	AMP	S	AMX, AMC, PIP, TZP	S	Staphylococcus	Breakpoints	10	
 genus	is	Staphylococcus	FOX	S	carbapenems, cephalosporins_except_CAZ	S	Staphylococcus	Breakpoints	10	
 genus	is	Staphylococcus	FOX	I	carbapenems, cephalosporins_except_CAZ	I	Staphylococcus	Breakpoints	10	
@@ -120,7 +120,7 @@ order	is	Enterobacterales	AMP	I	AMX	I	Enterobacterales (Order)	Breakpoints	11
 order	is	Enterobacterales	AMP	R	AMX	R	Enterobacterales (Order)	Breakpoints	11	
 genus	is	Staphylococcus	PEN, FOX	S	AMP, AMX, PIP, TIC	S	Staphylococcus	Breakpoints	11	
 genus	is	Staphylococcus	PEN, FOX	R, S	OXA, FLC	S	Staphylococcus	Breakpoints	11	
-genus	is	Staphylococcus	FOX	R	all_betalactams	R	Staphylococcus	Breakpoints	11	
+genus	is	Staphylococcus	FOX	R	betalactams	R	Staphylococcus	Breakpoints	11	
 genus_species	is	Staphylococcus saprophyticus	AMP	S	AMX, AMC, PIP, TZP	S	Staphylococcus	Breakpoints	11	
 genus	is	Staphylococcus	FOX	S	carbapenems, cephalosporins_except_CAZ	S	Staphylococcus	Breakpoints	11	
 genus	is	Staphylococcus	FOX	I	carbapenems, cephalosporins_except_CAZ	I	Staphylococcus	Breakpoints	11	
@@ -224,7 +224,7 @@ genus_species	is	Burkholderia pseudomallei	TCY	R	DOX	R	Burkholderia pseudomallei
 genus	is	Bacillus	NOR	S	fluoroquinolones	S	Bacillus	Breakpoints	11	added in 11
 genus	is	Bacillus	NOR	I	fluoroquinolones	I	Bacillus	Breakpoints	11	added in 11
 genus	is	Bacillus	NOR	R	fluoroquinolones	R	Bacillus	Breakpoints	11	added in 11
-order	is	Enterobacterales			PEN, glycopeptides, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+order	is	Enterobacterales			PEN, glycopeptides_except_lipo, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 fullname	like	^Citrobacter (koseri|amalonaticus|sedlakii|farmeri|rodentium)			aminopenicillins, TIC	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 fullname	like	^Citrobacter (freundii|braakii|murliniae|werkmanii|youngae)			aminopenicillins, AMC, CZO, FOX	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Enterobacter cloacae			aminopenicillins, AMC, CZO, FOX	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
@@ -232,17 +232,17 @@ genus_species	is	Klebsiella aerogenes			aminopenicillins, AMC, CZO, FOX	R	Table
 genus_species	is	Escherichia hermannii			aminopenicillins, TIC	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Hafnia alvei			aminopenicillins, AMC, CZO, FOX	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus	is	Klebsiella			aminopenicillins, TIC	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Morganella morganii			aminopenicillins, AMC, CZO, tetracyclines, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Proteus mirabilis			tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Proteus penneri			aminopenicillins, CZO, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Proteus vulgaris			aminopenicillins, CZO, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Providencia rettgeri			aminopenicillins, AMC, CZO, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus_species	is	Providencia stuartii			aminopenicillins, AMC, CZO, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Morganella morganii			aminopenicillins, AMC, CZO, DOX, MNO, TCY, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Proteus mirabilis			DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Proteus penneri			aminopenicillins, CZO, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Proteus vulgaris			aminopenicillins, CZO, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Providencia rettgeri			aminopenicillins, AMC, CZO, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
+genus_species	is	Providencia stuartii			aminopenicillins, AMC, CZO, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus	is	Raoultella			aminopenicillins, TIC	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Serratia marcescens			aminopenicillins, AMC, CZO, FOX, CXM, DOX, TCY, polymyxins, NIT	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Yersinia enterocolitica			aminopenicillins, AMC, TIC, CZO, FOX	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
 genus_species	is	Yersinia pseudotuberculosis			PLB, COL	R	Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae)	Expert Rules	3.1	
-genus	one_of	Achromobacter, Acinetobacter, Alcaligenes, Bordetella, Burkholderia, Elizabethkingia, Flavobacterium, Ochrobactrum, Pseudomonas, Stenotrophomonas			PEN, FOX, CXM, glycopeptides, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
+genus	one_of	Achromobacter, Acinetobacter, Alcaligenes, Bordetella, Burkholderia, Elizabethkingia, Flavobacterium, Ochrobactrum, Pseudomonas, Stenotrophomonas			PEN, FOX, CXM, glycopeptides_except_lipo, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Acinetobacter baumannii			aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Acinetobacter pittii			aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Acinetobacter nosocomialis			aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
@@ -250,10 +250,10 @@ genus_species	is	Acinetobacter calcoaceticus			aminopenicillins, AMC, CZO, CTX,
 genus_species	is	Achromobacter xylosoxidans			aminopenicillins, CZO, CTX, CRO, ETP	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 fullname	like	^Burkholderia (ambifaria|anthina|arboris|cepacia|cenocepacia|contaminans|diffusa|dolosa|lata|latens|metallica|multivorans|paludis|pseudomultivorans|pyrrocinia|pseudomultivorans|seminalis|stabilis|stagnalis|territorii|ubonensis|vietnamiensis)			aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, ATM, ETP, CIP, CHL, aminoglycosides, TMP, FOS, polymyxins	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Elizabethkingia meningoseptica			aminopenicillins, AMC, TIC, CZO, CTX, CRO, CAZ, FEP, ATM, ETP, IPM, MEM, polymyxins	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
-genus_species	is	Ochrobactrum anthropi			aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
-genus_species	is	Pseudomonas aeruginosa			aminopenicillins, AMC, CZO, CTX, CRO, ETP, CHL, KAN, NEO, TMP, SXT, tetracyclines, TGC	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
+genus_species	is	Brucella anthropi			aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
+genus_species	is	Pseudomonas aeruginosa			aminopenicillins, AMC, CZO, CTX, CRO, ETP, CHL, KAN, NEO, TMP, SXT, DOX, MNO, TCY, TGC	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Stenotrophomonas maltophilia			aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, ATM, ETP, IPM, MEM, aminoglycosides, TMP, FOS, TCY	R	Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria	Expert Rules	3.1	
-genus	one_of	Haemophilus, Moraxella, Neisseria, Campylobacter			glycopeptides, LIN, DAP, LNZ	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
+genus	one_of	Haemophilus, Moraxella, Neisseria, Campylobacter			glycopeptides_except_lipo, LIN, DAP, LNZ	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Haemophilus influenzae			FUS, streptogramins	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
 genus_species	is	Moraxella catarrhalis			TMP	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
 genus	is	Neisseria			TMP	R	Table 03: Intrinsic resistance in other Gram-negative bacteria	Expert Rules	3.1	
@@ -279,8 +279,8 @@ genus_species	is	Enterococcus casseliflavus			FUS, CAZ, cephalosporins_except_CA
 genus_species	is	Enterococcus faecium			FUS, CAZ, cephalosporins_except_CAZ, aminoglycosides, macrolides, TMP, SXT	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus	is	Corynebacterium			FOS	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus_species	is	Listeria monocytogenes			cephalosporins	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
-genus	one_of	Leuconostoc, Pediococcus			glycopeptides	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
-genus	is	Lactobacillus			glycopeptides	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
+genus	one_of	Leuconostoc, Pediococcus			glycopeptides_except_lipo	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
+genus	is	Lactobacillus			glycopeptides_except_lipo	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus_species	is	Clostridium ramosum			VAN	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus_species	is	Clostridium innocuum			VAN	R	Table 04: Intrinsic resistance in Gram-positive bacteria	Expert Rules	3.1	
 genus_species	one_of	Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G	PEN	S	aminopenicillins, cephalosporins_except_CAZ, carbapenems	S	Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci	Expert Rules	3.1	
@@ -298,7 +298,7 @@ genus	is	Staphylococcus	MFX	R	fluoroquinolones	R	Table 13: Interpretive rules fo
 genus_species	is	Streptococcus pneumoniae	MFX	R	fluoroquinolones	R	Table 13: Interpretive rules for quinolones	Expert Rules	3.1	
 order	is	Enterobacterales	CIP	R	fluoroquinolones	R	Table 13: Interpretive rules for quinolones	Expert Rules	3.1	
 genus_species	is	Neisseria gonorrhoeae	CIP	R	fluoroquinolones	R	Table 13: Interpretive rules for quinolones	Expert Rules	3.1	
-order	is	Enterobacterales			PEN, glycopeptides, lipoglycopeptides, FUS, macrolides, lincosamides, streptogramins, RIF, oxazolidinones	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+order	is	Enterobacterales			PEN, glycopeptides_except_lipo, lipoglycopeptides, FUS, macrolides, lincosamides, streptogramins, RIF, oxazolidinones	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 fullname	like	^Citrobacter (koseri|amalonaticus|sedlakii|farmeri|rodentium)			aminopenicillins, TIC	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 fullname	like	^Citrobacter (freundii|braakii|murliniae|werkmanii|youngae)			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Enterobacter cloacae			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
@@ -308,13 +308,13 @@ genus_species	is	Klebsiella aerogenes			aminopenicillins, AMC, SAM, CZO, CEP, LE
 genus_species	is	Klebsiella oxytoca			aminopenicillins, TIC	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 fullname	like	^Klebsiella( pneumoniae| quasipneumoniae| variicola)?			aminopenicillins, TIC	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Leclercia adecarboxylata			FOS	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Morganella morganii			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, tetracyclines, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Morganella morganii			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, DOX, MNO, TCY, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Plesiomonas shigelloides			aminopenicillins, AMC, SAM	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Proteus mirabilis			tetracyclines, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Proteus penneri			aminopenicillins, CZO, CEP, LEX, CFR, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Proteus vulgaris			aminopenicillins, CZO, CEP, LEX, CFR, CXM, tetracyclines, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Providencia rettgeri			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, tetracyclines, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus_species	is	Providencia stuartii			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, tetracyclines, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Proteus mirabilis			DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Proteus penneri			aminopenicillins, CZO, CEP, LEX, CFR, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Proteus vulgaris			aminopenicillins, CZO, CEP, LEX, CFR, CXM, DOX, MNO, TCY, TGC, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Providencia rettgeri			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, DOX, MNO, TCY, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
+genus_species	is	Providencia stuartii			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, DOX, MNO, TCY, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus	is	Raoultella			aminopenicillins, TIC	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Serratia marcescens			aminopenicillins, AMC, SAM, CZO, CEP, LEX, CFR, FOX, CXM, DOX, TCY, polymyxins, NIT	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Yersinia enterocolitica			aminopenicillins, AMC, SAM, TIC, CZO, CEP, LEX, CFR, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
@@ -324,20 +324,20 @@ genus_species	is	Aeromonas veronii			aminopenicillins, AMC, SAM, FOX	R	Table 1:
 genus_species	is	Aeromonas dhakensis			aminopenicillins, AMC, SAM, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Aeromonas caviae			aminopenicillins, AMC, SAM, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
 genus_species	is	Aeromonas jandaei			aminopenicillins, AMC, SAM, TIC,  CZO, CEP, LEX, CFR, FOX	R	Table 1: Intrinsic resistance in Enterobacterales and Aeromonas spp.	Expert Rules	3.2	
-genus	one_of	Achromobacter, Acinetobacter, Alcaligenes, Bordetella, Burkholderia, Elizabethkingia, Flavobacterium, Ochrobactrum, Pseudomonas, Stenotrophomonas			PEN, cephalosporins_1st, cephalosporins_2nd, glycopeptides, lipoglycopeptides, FUS, macrolides, lincosamides, streptogramins, RIF, oxazolidinones	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	
+genus	one_of	Achromobacter, Acinetobacter, Alcaligenes, Bordetella, Burkholderia, Elizabethkingia, Flavobacterium, Ochrobactrum, Pseudomonas, Stenotrophomonas			PEN, cephalosporins_1st, cephalosporins_2nd, glycopeptides_except_lipo, lipoglycopeptides, FUS, macrolides, lincosamides, streptogramins, RIF, oxazolidinones	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	
 fullname	like	^Acinetobacter (baumannii|pittii|nosocomialis)			aminopenicillins, AMC, CRO, CTX, ATM, ETP, TMP, FOS, DOX, TCY	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 genus	is	Acinetobacter			DOX, TCY	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 genus_species	is	Achromobacter xylosoxidans 			aminopenicillins, CRO, CTX, ETP	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 fullname	like	^Burkholderia (ambifaria|anthina|arboris|cepacia|cenocepacia|contaminans|diffusa|dolosa|lata|latens|metallica|multivorans|paludis|pseudomultivorans|pyrrocinia|pseudomultivorans|seminalis|stabilis|stagnalis|territorii|ubonensis|vietnamiensis)			aminopenicillins, AMC, SAM, TIC, TCC, PIP, TZP, CRO, CTX, ATM, ETP, CIP, CHL, aminoglycosides, TMP, FOS, polymyxins	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 genus_species	is	Elizabethkingia meningoseptica			aminopenicillins, AMC, SAM, TIC, TCC, PIP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP, IPM, MEM, polymyxins	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
-genus_species	is	Ochrobactrum anthropi			aminopenicillins, AMC, SAM, TIC, TCC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
-genus_species	is	Pseudomonas aeruginosa			aminopenicillins, AMC, SAM, CTX, CRO, ETP, CHL, KAN, NEO, TMP, tetracyclines, TGC	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
+genus_species	is	Brucella anthropi			aminopenicillins, AMC, SAM, TIC, TCC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
+genus_species	is	Pseudomonas aeruginosa			aminopenicillins, AMC, SAM, CTX, CRO, ETP, CHL, KAN, NEO, TMP, DOX, MNO, TCY, TGC	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
 genus_species	is	Stenotrophomonas maltophilia			aminopenicillins, AMC, SAM, TIC, PIP, TZP, CRO, CTX, ATM, ETP, IPM, MEM, aminoglycosides, TMP, FOS, TCY	R	Table 2: Intrinsic resistance in non-fermentative gram-negative bacteria	Expert Rules	3.2	Additional rules from header added in separate rule (genus is one of…)
-genus_species	is	Haemophilus influenzae			FUS, streptogramins, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
-genus_species	is	Moraxella catarrhalis			TMP, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
-genus	is	Neisseria			TMP, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
-genus_species	is	Campylobacter fetus			FUS, streptogramins, TMP, NAL, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
-fullname	like	^Campylobacter (jejuni|coli)			FUS, streptogramins, TMP, glycopeptides, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+genus_species	is	Haemophilus influenzae			FUS, streptogramins, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+genus_species	is	Moraxella catarrhalis			TMP, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+genus	is	Neisseria			TMP, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+genus_species	is	Campylobacter fetus			FUS, streptogramins, TMP, NAL, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
+fullname	like	^Campylobacter (jejuni|coli)			FUS, streptogramins, TMP, glycopeptides_except_lipo, lipoglycopeptides, lincosamides, oxazolidinones	R	Table 3: Intrinsic resistance in other gram-negative bacteria	Expert Rules	3.2	
 gramstain	is	Gram-positive			ATM, TEM, polymyxins, NAL	R	Table 4: Intrinsic resistance in gram-positive bacteria	Expert Rules	3.2	
 genus_species	is	Staphylococcus saprophyticus			FUS, CAZ, FOS, NOV	R	Table 4: Intrinsic resistance in gram-positive bacteria	Expert Rules	3.2	
 genus_species	is	Staphylococcus cohnii			CAZ, NOV	R	Table 4: Intrinsic resistance in gram-positive bacteria	Expert Rules	3.2	
@@ -372,8 +372,8 @@ fullname	like	^(Serratia|Providencia|Morganella morganii)			TGC	R	Expert Rules o
 genus	is	Salmonella			cephalosporins_2nd	R	Expert Rules on Salmonella	Expert Rules	3.2	
 genus	is	Salmonella			aminoglycosides	R	Expert Rules on Salmonella	Expert Rules	3.2	
 genus	is	Salmonella	PEF	R	CIP	R	Expert Rules on Salmonella	Expert Rules	3.2	
-genus_species	is	Staphylococcus aureus	FOX1	R	all_betalactams	R	Expert Rules on Staphylococcus	Expert Rules	3.2	
-genus_species	is	Staphylococcus aureus	FOX1	S	all_betalactams	S	Expert Rules on Staphylococcus	Expert Rules	3.2	
+genus_species	is	Staphylococcus aureus	FOX1	R	betalactams	R	Expert Rules on Staphylococcus	Expert Rules	3.2	
+genus_species	is	Staphylococcus aureus	FOX1	S	betalactams	S	Expert Rules on Staphylococcus	Expert Rules	3.2	
 genus_species	one_of	Staphylococcus aureus, Staphylococcus lugdunensis	PEN	R	AMP, AMX, AZL, BAM, CRB, CRN, EPC, HET, MEC, MEZ, MTM, PIP, PME, PVM, SBC, TAL, TEM, TIC	R	Expert Rules on Staphylococcus	Expert Rules	3.2	all penicillins without beta-lactamse inhibitor
 genus	is	Staphylococcus	ERY, CLI	S	macrolides, lincosamides	S	Expert Rules on Staphylococcus	Expert Rules	3.2	
 genus	is	Staphylococcus	NOR	S	CIP, LVX, MFX, OFX	S	Expert Rules on Staphylococcus	Expert Rules	3.2	
@@ -400,7 +400,7 @@ genus_species	is	Streptococcus pneumoniae	TCY	S	DOX, MNO	S	Expert Rules on Strep
 genus_species	is	Streptococcus pneumoniae	TCY	R	DOX, MNO	R	Expert Rules on Streptococcus pneumoniae	Expert Rules	3.2	
 genus_species	is	Streptococcus pneumoniae	VAN	S	lipoglycopeptides	S	Expert Rules on Streptococcus pneumoniae	Expert Rules	3.2	
 fullname	like	^Streptococcus (anginosus|australis|bovis|constellatus|cristatus|equinus|gallolyticus|gordonii|infantarius|infantis|intermedius|mitis|mutans|oligofermentans|oralis|parasanguinis|peroris|pseudopneumoniae|salivarius|sanguinis|sinensis|sobrinus|thermophilus|vestibularis|viridans)$	PEN	S	aminopenicillins, CTX, CRO	S	Expert Rules on Viridans Group Streptococci	Expert Rules	3.2	
-genus_species	is	Haemophilus influenzae 	PEN	S	all_betalactams	S	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	
+genus_species	is	Haemophilus influenzae 	PEN	S	betalactams	S	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	
 genus_species	is	Haemophilus influenzae 	NAL	S	fluoroquinolones	S	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	
 genus_species	is	Haemophilus influenzae 	NAL	R	CIP, LVX, MFX	R	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	
 genus_species	is	Haemophilus influenzae 	TCY	S	DOX, MNO	S	Expert Rules on Haemophilus influenzae	Expert Rules	3.2	
@@ -136,8 +136,8 @@ read_EUCAST <- function(sheet, file, guideline_name) {
              disk_R = ifelse(has_zone_diameters, G, NA_character_)) %>% 
    filter(!is.na(drug),
           !(is.na(MIC_S) & is.na(MIC_R) & is.na(disk_S) & is.na(disk_R)),
-           !MIC_S %like% "(MIC|S ≤|note)",
-           !MIC_S %like% "^[-]",
+           MIC_S %unlike% "(MIC|S ≤|note)",
+           MIC_S %unlike% "^[-]",
           drug != MIC_S,) %>% 
    mutate(administration = case_when(drug %like% "[( ]oral" ~ "oral",
                                      drug %like% "[( ]iv"   ~ "iv",
@@ -114,8 +114,8 @@ abx_atc2 <- ab_old %>%
  filter(!atc %in% abx_atc1$atc,
         is.na(ears_net),
         !is.na(atc_group1),
-         !atc_group1 %like% ("virus|vaccin|viral|immun"),
-         !official %like% "(combinations| with )") %>%
+         atc_group1 %unlike% ("virus|vaccin|viral|immun"),
+         official %unlike% "(combinations| with )") %>%
  mutate(ab = NA_character_) %>%
  as.data.frame(stringsAsFactors = FALSE) %>%
  select(ab, atc, name = official)
@@ -382,7 +382,7 @@ MOs <- MOs %>%

 # what characters are in the fullnames?
 table(sort(unlist(strsplit(x = paste(MOs$fullname, collapse = ""), split = ""))))
-MOs %>% filter(!fullname %like% "^[a-z ]+$") %>% arrange(fullname) %>% View()
+MOs %>% filter(fullname %unlike% "^[a-z ]+$") %>% arrange(fullname) %>% View()

 table(MOs$kingdom, MOs$rank)
 table(AMR::microorganisms$kingdom, AMR::microorganisms$rank)
@@ -160,7 +160,7 @@ updated_microorganisms <- taxonomy %>%
                             TRUE ~ "subsp."),
            ref = get_author_year(authors),
            species_id = as.character(record_no),
-            source = "LSPN",
+            source = "LPSN",
            prevalence = 0,
            snomed = NA)

@@ -9,9 +9,9 @@ files <- xml2::read_html(paste0("https://github.com/nathaneastwood/poorman/tree/
 # get full URLs of all raw R files
 files <- sort(paste0("https://raw.githubusercontent.com", gsub("blob/", "", files[files %like% "/R/.*.R$"])))
 # remove files with only pkg specific code
-files <- files[!files %like% "(zzz|init)[.]R$"]
+files <- files[files %unlike% "(zzz|init)[.]R$"]
 # also, there's a lot of functions we don't use
-files <- files[!files %like% "(slice|glimpse|recode|replace_na|coalesce)[.]R$"]
+files <- files[files %unlike% "(slice|glimpse|recode|replace_na|coalesce)[.]R$"]

 # add our prepend file, containing info about the source of the data
 intro <- readLines("data-raw/poorman_prepend.R")
@@ -39,6 +39,10 @@ antibiotic	TRUE	TRUE	FALSE	Antibiotikum	antibioticum	antibiótico
 Antibiotic	TRUE	TRUE	FALSE	Antibiotikum	Antibioticum	Antibiótico			
 Drug	TRUE	TRUE	FALSE	Medikament	Middel	Fármaco			
 drug	TRUE	TRUE	FALSE	Medikament	middel	fármaco			
+Frequency	FALSE	TRUE	FALSE	Zahl	Aantal				
+Minimum Inhibitory Concentration (mg/L)	FALSE	FALSE	FALSE	Minimale Hemm-Konzentration (mg/L)	Minimale inhiberende concentratie (mg/L)				
+Disk diffusion diameter (mm)	FALSE	FALSE	FALSE	Durchmesser der Scheibenzone (mm)	Diameter diskzone (mm)				
+Antimicrobial Interpretation	FALSE	FALSE	FALSE	Antimikrobielle Auswertung	Antimicrobiële interpretatie				
 4-aminosalicylic acid	FALSE	TRUE	FALSE	4-Aminosalicylsäure	4-aminosalicylzuur	Ácido 4-aminosalicílico			
 Adefovir dipivoxil	FALSE	TRUE	FALSE	Adefovir Dipivoxil	Adefovir	Adefovir dipivoxil			
 Aldesulfone sodium	FALSE	TRUE	FALSE	Aldesulfon-Natrium	Aldesulfon	Aldesulfona sódica			
@@ -81,7 +81,7 @@
      </button>
      <span class="navbar-brand">
        <a class="navbar-link" href="https://msberends.github.io/AMR//index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9012</span>
      </span>
    </div>

@@ -89,14 +89,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -105,77 +105,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -184,21 +184,21 @@
 </li>
 <li>
  <a href="reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -207,14 +207,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -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">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9012</span>
      </span>
    </div>

@@ -89,14 +89,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -105,77 +105,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -184,21 +184,21 @@
 </li>
 <li>
  <a href="reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -207,14 +207,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -0,0 +1,4 @@
+/* Styles for section anchors */
+a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
+a.anchor-section::before {content: '#';}
+.hasAnchor:hover a.anchor-section {visibility: visible;}
@@ -0,0 +1,33 @@
+// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
+document.addEventListener('DOMContentLoaded', function() {
+  // Do nothing if AnchorJS is used
+  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
+    return;
+  }
+
+  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
+
+  // Do nothing if sections are already anchored
+  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
+    return null;
+  }
+
+  // Use section id when pandoc runs with --section-divs
+  const section_id = function(x) {
+    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
+            ? x.id : '');
+  };
+
+  // Add anchors
+  h.forEach(function(x) {
+    const id = x.id || section_id(x.parentElement);
+    if (id === '') {
+      return null;
+    }
+    let anchor = document.createElement('a');
+    anchor.href = '#' + id;
+    anchor.classList = ['anchor-section'];
+    x.classList.add('hasAnchor');
+    x.appendChild(anchor);
+  });
+});
@@ -39,7 +39,7 @@
      </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">1.5.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -47,14 +47,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -63,77 +63,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -142,21 +142,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -165,14 +165,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -187,7 +187,8 @@

      

-      </header><script src="EUCAST_files/header-attrs-2.6/header-attrs.js"></script><div class="row">
+      </header><link href="EUCAST_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
+<script src="EUCAST_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
  <div class="col-md-9 contents">
    <div class="page-header toc-ignore">
      <h1 data-toc-skip>How to apply EUCAST rules</h1>
@@ -215,8 +216,8 @@
 <a href="#examples" class="anchor"></a>Examples</h2>
 <p>These rules can be used to discard impossible bug-drug combinations in your data. For example, <em>Klebsiella</em> produces beta-lactamase that prevents ampicillin (or amoxicillin) from working against it. In other words, practically every strain of <em>Klebsiella</em> is resistant to ampicillin.</p>
 <p>Sometimes, laboratory data can still contain such strains with ampicillin being susceptible to ampicillin. This could be because an antibiogram is available before an identification is available, and the antibiogram is then not re-interpreted based on the identification (namely, <em>Klebsiella</em>). EUCAST expert rules solve this, that can be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">oops</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, 
+<div class="sourceCode" id="cb1"><pre class="downlit">
+<span class="va">oops</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, 
                          <span class="st">"Escherichia"</span><span class="op">)</span>,
                   ampicillin <span class="op">=</span> <span class="st">"S"</span><span class="op">)</span>
 <span class="va">oops</span>
@@ -227,19 +228,19 @@
 <span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">oops</span>, info <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
 <span class="co">#            mo ampicillin</span>
 <span class="co"># 1  Klebsiella          R</span>
-<span class="co"># 2 Escherichia          S</span></code></pre></div>
+<span class="co"># 2 Escherichia          S</span></pre></div>
 <p>A more convenient function is <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> that uses the same guideline, but allows to check for one or more specific microorganisms or antibiotics:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,
+<div class="sourceCode" id="cb2"><pre class="downlit">
+<span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,
                          <span class="st">"ampicillin"</span><span class="op">)</span>
 <span class="co"># [1]  TRUE FALSE</span>

 <span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>,
                          <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"kanamycin"</span><span class="op">)</span><span class="op">)</span>
-<span class="co"># [1]  TRUE FALSE</span></code></pre></div>
+<span class="co"># [1]  TRUE FALSE</span></pre></div>
 <p>EUCAST rules can not only be used for correction, they can also be used for filling in known resistance and susceptibility based on results of other antimicrobials drugs. This process is called <em>interpretive reading</em>, is basically a form of imputation, and is part of the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span>,
+<div class="sourceCode" id="cb3"><pre class="downlit">
+<span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span>,
                          <span class="st">"Enterococcus faecalis"</span>,
                          <span class="st">"Escherichia coli"</span>,
                          <span class="st">"Klebsiella pneumoniae"</span>,
@@ -251,9 +252,9 @@
                   CXM <span class="op">=</span> <span class="st">"-"</span>,       <span class="co"># Cefuroxime</span>
                   PEN <span class="op">=</span> <span class="st">"S"</span>,       <span class="co"># Benzylenicillin</span>
                   FOX <span class="op">=</span> <span class="st">"S"</span>,       <span class="co"># Cefoxitin</span>
-                   stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span></code></pre></div>
+                   stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></pre></div>
+<div class="sourceCode" id="cb4"><pre class="downlit">
+<span class="va">data</span></pre></div>
 <table class="table">
 <thead><tr class="header">
 <th align="left">mo</th>
@@ -318,8 +319,8 @@
 </tr>
 </tbody>
 </table>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb5"><pre class="downlit">
+<span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></pre></div>
 <table class="table">
 <thead><tr class="header">
 <th align="left">mo</th>
@@ -0,0 +1,4 @@
+/* Styles for section anchors */
+a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
+a.anchor-section::before {content: '#';}
+.hasAnchor:hover a.anchor-section {visibility: visible;}
@@ -0,0 +1,33 @@
+// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
+document.addEventListener('DOMContentLoaded', function() {
+  // Do nothing if AnchorJS is used
+  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
+    return;
+  }
+
+  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
+
+  // Do nothing if sections are already anchored
+  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
+    return null;
+  }
+
+  // Use section id when pandoc runs with --section-divs
+  const section_id = function(x) {
+    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
+            ? x.id : '');
+  };
+
+  // Add anchors
+  h.forEach(function(x) {
+    const id = x.id || section_id(x.parentElement);
+    if (id === '') {
+      return null;
+    }
+    let anchor = document.createElement('a');
+    anchor.href = '#' + id;
+    anchor.classList = ['anchor-section'];
+    x.classList.add('hasAnchor');
+    x.appendChild(anchor);
+  });
+});
@@ -39,7 +39,7 @@
      </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">1.5.0.9018</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -47,14 +47,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -63,77 +63,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -142,21 +142,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -165,14 +165,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -187,7 +187,8 @@

      

-      </header><script src="MDR_files/header-attrs-2.6/header-attrs.js"></script><div class="row">
+      </header><link href="MDR_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
+<script src="MDR_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
  <div class="col-md-9 contents">
    <div class="page-header toc-ignore">
      <h1 data-toc-skip>How to determine multi-drug resistance (MDR)</h1>
@@ -243,27 +244,27 @@
 <a href="#custom-guidelines" class="anchor"></a>Custom Guidelines</h4>
 <p>You can also use your own custom guideline. Custom guidelines can be set with the <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.</p>
 <p>If you are familiar with <code><a href="https://dplyr.tidyverse.org/reference/case_when.html">case_when()</a></code> of the <code>dplyr</code> package, you will recognise the input method to set your own rules. Rules must be set using what considers to be the ‘formula notation’:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">custom</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">custom_mdro_guideline</a></span><span class="op">(</span><span class="va">CIP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type A"</span>,
-                                <span class="va">ERY</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type B"</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb1"><pre class="downlit">
+<span class="va">custom</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">custom_mdro_guideline</a></span><span class="op">(</span><span class="va">CIP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type A"</span>,
+                                <span class="va">ERY</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type B"</span><span class="op">)</span></pre></div>
 <p>If a row/an isolate matches the first rule, the value after the first <code><a href="https://rdrr.io/r/base/tilde.html">~</a></code> (in this case <em>‘Elderly Type A’</em>) will be set as MDRO value. Otherwise, the second rule will be tried and so on. The number of rules is unlimited.</p>
 <p>You can print the rules set in the console for an overview. Colours will help reading it if your console supports colours.</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">custom</span>
+<div class="sourceCode" id="cb2"><pre class="downlit">
+<span class="va">custom</span>
 <span class="co"># A set of custom MDRO rules:</span>
-<span class="co">#   1. CIP is "R" and age is higher than 60 -&gt; Elderly Type A</span>
-<span class="co">#   2. ERY is "R" and age is higher than 60 -&gt; Elderly Type B</span>
-<span class="co">#   3. Otherwise -&gt; Negative</span>
+<span class="co">#   1. If CIP is "R" and age is higher than 60 then: Elderly Type A</span>
+<span class="co">#   2. If ERY is "R" and age is higher than 60 then: Elderly Type B</span>
+<span class="co">#   3. Otherwise: Negative</span>
 <span class="co"># </span>
 <span class="co"># Unmatched rows will return NA.</span>
-<span class="co"># Results will be of class &lt;factor&gt;, with ordered levels: Negative &lt; Elderly Type A &lt; Elderly Type B</span></code></pre></div>
+<span class="co"># Results will be of class &lt;factor&gt;, with ordered levels: Negative &lt; Elderly Type A &lt; Elderly Type B</span></pre></div>
 <p>The outcome of the function can be used for the <code>guideline</code> argument in the [mdro()] function:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">example_isolates</span>, guideline <span class="op">=</span> <span class="va">custom</span><span class="op">)</span>
+<div class="sourceCode" id="cb3"><pre class="downlit">
+<span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">example_isolates</span>, guideline <span class="op">=</span> <span class="va">custom</span><span class="op">)</span>
 <span class="fu"><a href="https://rdrr.io/r/base/table.html">table</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
 <span class="co"># x</span>
 <span class="co">#       Negative Elderly Type A Elderly Type B </span>
-<span class="co">#           1066             43            891</span></code></pre></div>
+<span class="co">#           1070            198            732</span></pre></div>
 <p>The rules set (the <code>custom</code> object in this case) could be exported to a shared file location using <code><a href="https://rdrr.io/r/base/readRDS.html">saveRDS()</a></code> if you collaborate with multiple users. The custom rules set could then be imported using <code><a href="https://rdrr.io/r/base/readRDS.html">readRDS()</a></code>.</p>
 </div>
 </div>
@@ -272,15 +273,15 @@
 <a href="#examples" class="anchor"></a>Examples</h3>
 <p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered <code>factor</code>. For example, the output of the default guideline by Magiorakos <em>et al.</em> returns a <code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in that order.</p>
 <p>The next example uses the <code>example_isolates</code> data set. This is a data set included with this package and contains 2,000 microbial isolates with their full antibiograms. It reflects reality and can be used to practice AMR data analysis. If we test the MDR/XDR/PDR guideline on this data set, we get:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>   <span class="co"># to support pipes: %&gt;%</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op">%&gt;%</span> 
+<div class="sourceCode" id="cb4"><pre class="downlit">
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>   <span class="co"># to support pipes: %&gt;%</span>
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></pre></div>
+<div class="sourceCode" id="cb5"><pre class="downlit">
+<span class="va">example_isolates</span> <span class="op">%&gt;%</span> 
  <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="op">)</span> <span class="op">%&gt;%</span> 
  <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="op">)</span> <span class="co"># show frequency table of the result</span>
 <span class="co"># Warning: NA introduced for isolates where the available percentage of antimicrobial</span>
-<span class="co"># classes was below 50% (set with `pct_required_classes`)</span></code></pre></div>
+<span class="co"># classes was below 50% (set with `pct_required_classes`)</span></pre></div>
 <p><strong>Frequency table</strong></p>
 <p>Class: factor &gt; ordered (numeric)<br>
 Length: 2,000<br>
@@ -316,8 +317,8 @@ Unique: 2</p>
 </tbody>
 </table>
 <p>For another example, I will create a data set to determine multi-drug resistant TB:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># random_rsi() is a helper function to generate</span>
+<div class="sourceCode" id="cb6"><pre class="downlit">
+<span class="co"># random_rsi() is a helper function to generate</span>
 <span class="co"># a random vector with values S, I and R</span>
 <span class="va">my_TB_data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>rifampicin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
                         isoniazid <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
@@ -325,44 +326,44 @@ Unique: 2</p>
                         ethambutol <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
                         pyrazinamide <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
                         moxifloxacin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
-                         kanamycin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></code></pre></div>
+                         kanamycin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></pre></div>
 <p>Because all column names are automatically verified for valid drug names or codes, this would have worked exactly the same:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">my_TB_data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>RIF <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
+<div class="sourceCode" id="cb7"><pre class="downlit">
+<span class="va">my_TB_data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>RIF <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
                         INH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
                         GAT <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
                         ETH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
                         PZA <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
                         MFX <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
-                         KAN <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></code></pre></div>
+                         KAN <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></pre></div>
 <p>The data set now looks like this:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
+<div class="sourceCode" id="cb8"><pre class="downlit">
+<span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
 <span class="co">#   rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span>
-<span class="co"># 1          S         R            S          S            S            I</span>
-<span class="co"># 2          S         I            R          R            R            R</span>
-<span class="co"># 3          R         S            S          I            S            I</span>
-<span class="co"># 4          I         S            S          S            I            S</span>
-<span class="co"># 5          I         I            I          S            I            R</span>
-<span class="co"># 6          S         I            S          R            S            S</span>
+<span class="co"># 1          S         S            S          S            R            R</span>
+<span class="co"># 2          R         S            S          S            I            R</span>
+<span class="co"># 3          R         R            I          R            I            R</span>
+<span class="co"># 4          R         R            S          S            R            I</span>
+<span class="co"># 5          R         R            R          I            I            I</span>
+<span class="co"># 6          R         I            R          R            I            I</span>
 <span class="co">#   kanamycin</span>
-<span class="co"># 1         R</span>
-<span class="co"># 2         I</span>
-<span class="co"># 3         R</span>
-<span class="co"># 4         S</span>
+<span class="co"># 1         I</span>
+<span class="co"># 2         R</span>
+<span class="co"># 3         I</span>
+<span class="co"># 4         I</span>
 <span class="co"># 5         S</span>
-<span class="co"># 6         R</span></code></pre></div>
+<span class="co"># 6         I</span></pre></div>
 <p>We can now add the interpretation of MDR-TB to our data set. You can use:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">my_TB_data</span>, guideline <span class="op">=</span> <span class="st">"TB"</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb9"><pre class="downlit">
+<span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">my_TB_data</span>, guideline <span class="op">=</span> <span class="st">"TB"</span><span class="op">)</span></pre></div>
 <p>or its shortcut <code><a href="../reference/mdro.html">mdr_tb()</a></code>:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">mdr_tb</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
-<span class="co"># NOTE: No column found as input for `col_mo`, assuming all records</span>
-<span class="co">#       containMycobacterium tuberculosis.</span></code></pre></div>
+<div class="sourceCode" id="cb10"><pre class="downlit">
+<span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">mdr_tb</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
+<span class="co"># ℹ No column found as input for `col_mo`, assuming all records</span>
+<span class="co">#   containMycobacterium tuberculosis.</span></pre></div>
 <p>Create a frequency table of the results:</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb11"><pre class="downlit">
+<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span><span class="op">)</span></pre></div>
 <p><strong>Frequency table</strong></p>
 <p>Class: factor &gt; ordered (numeric)<br>
 Length: 5,000<br>
@@ -382,40 +383,40 @@ Unique: 5</p>
 <tr class="odd">
 <td align="left">1</td>
 <td align="left">Mono-resistant</td>
-<td align="right">3246</td>
-<td align="right">64.92%</td>
-<td align="right">3246</td>
-<td align="right">64.92%</td>
+<td align="right">3165</td>
+<td align="right">63.30%</td>
+<td align="right">3165</td>
+<td align="right">63.30%</td>
 </tr>
 <tr class="even">
 <td align="left">2</td>
 <td align="left">Negative</td>
-<td align="right">976</td>
-<td align="right">19.52%</td>
-<td align="right">4222</td>
-<td align="right">84.44%</td>
+<td align="right">1000</td>
+<td align="right">20.00%</td>
+<td align="right">4165</td>
+<td align="right">83.30%</td>
 </tr>
 <tr class="odd">
 <td align="left">3</td>
 <td align="left">Multi-drug-resistant</td>
-<td align="right">467</td>
-<td align="right">9.34%</td>
-<td align="right">4689</td>
-<td align="right">93.78%</td>
+<td align="right">463</td>
+<td align="right">9.26%</td>
+<td align="right">4628</td>
+<td align="right">92.56%</td>
 </tr>
 <tr class="even">
 <td align="left">4</td>
 <td align="left">Poly-resistant</td>
-<td align="right">230</td>
-<td align="right">4.60%</td>
-<td align="right">4919</td>
-<td align="right">98.38%</td>
+<td align="right">255</td>
+<td align="right">5.10%</td>
+<td align="right">4883</td>
+<td align="right">97.66%</td>
 </tr>
 <tr class="odd">
 <td align="left">5</td>
 <td align="left">Extensively drug-resistant</td>
-<td align="right">81</td>
-<td align="right">1.62%</td>
+<td align="right">117</td>
+<td align="right">2.34%</td>
 <td align="right">5000</td>
 <td align="right">100.00%</td>
 </tr>
@@ -0,0 +1,4 @@
+/* Styles for section anchors */
+a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
+a.anchor-section::before {content: '#';}
+.hasAnchor:hover a.anchor-section {visibility: visible;}
@@ -0,0 +1,33 @@
+// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
+document.addEventListener('DOMContentLoaded', function() {
+  // Do nothing if AnchorJS is used
+  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
+    return;
+  }
+
+  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
+
+  // Do nothing if sections are already anchored
+  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
+    return null;
+  }
+
+  // Use section id when pandoc runs with --section-divs
+  const section_id = function(x) {
+    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
+            ? x.id : '');
+  };
+
+  // Add anchors
+  h.forEach(function(x) {
+    const id = x.id || section_id(x.parentElement);
+    if (id === '') {
+      return null;
+    }
+    let anchor = document.createElement('a');
+    anchor.href = '#' + id;
+    anchor.classList = ['anchor-section'];
+    x.classList.add('hasAnchor');
+    x.appendChild(anchor);
+  });
+});
@@ -39,7 +39,7 @@
      </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">1.5.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -47,14 +47,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -63,77 +63,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -142,21 +142,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -165,14 +165,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -187,7 +187,8 @@

      

-      </header><script src="PCA_files/header-attrs-2.6/header-attrs.js"></script><div class="row">
+      </header><link href="PCA_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
+<script src="PCA_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
  <div class="col-md-9 contents">
    <div class="page-header toc-ignore">
      <h1 data-toc-skip>How to conduct principal component analysis (PCA) for AMR</h1>
@@ -209,8 +210,8 @@
 <h1 class="hasAnchor">
 <a href="#transforming" class="anchor"></a>Transforming</h1>
 <p>For PCA, we need to transform our AMR data first. This is what the <code>example_isolates</code> data set in this package looks like:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
+<div class="sourceCode" id="cb1"><pre class="downlit">
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
 <span class="fu"><a href="https://tibble.tidyverse.org/reference/glimpse.html">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
 <span class="co"># Rows: 2,000</span>
@@ -263,10 +264,10 @@
 <span class="co"># $ CHL             &lt;rsi&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
 <span class="co"># $ COL             &lt;rsi&gt; NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, …</span>
 <span class="co"># $ MUP             &lt;rsi&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
-<span class="co"># $ RIF             &lt;rsi&gt; R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…</span></code></pre></div>
+<span class="co"># $ RIF             &lt;rsi&gt; R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…</span></pre></div>
 <p>Now to transform this to a data set with only resistance percentages per taxonomic order and genus:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">resistance_data</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op">%&gt;%</span> 
+<div class="sourceCode" id="cb2"><pre class="downlit">
+<span class="va">resistance_data</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op">%&gt;%</span> 
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span>order <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>,       <span class="co"># group on anything, like order</span>
           genus <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span>   <span class="co">#  and genus as we do here</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html">summarise_if</a></span><span class="op">(</span><span class="va">is.rsi</span>, <span class="va">resistance</span><span class="op">)</span> <span class="op">%&gt;%</span> <span class="co"># then get resistance of all drugs</span>
@@ -275,48 +276,52 @@

 <span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
 <span class="co"># # A tibble: 6 x 10</span>
-<span class="co"># # Groups:   order [2]</span>
-<span class="co">#   order           genus            AMC   CXM   CTX   CAZ   GEN   TOB   TMP   SXT</span>
-<span class="co">#   &lt;chr&gt;           &lt;chr&gt;          &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;</span>
-<span class="co"># 1 (unknown order) (unknown genu…    NA    NA    NA    NA    NA    NA    NA    NA</span>
-<span class="co"># 2 Actinomycetales Corynebacteri…    NA    NA    NA    NA    NA    NA    NA    NA</span>
-<span class="co"># 3 Actinomycetales Cutibacterium     NA    NA    NA    NA    NA    NA    NA    NA</span>
-<span class="co"># 4 Actinomycetales Dermabacter       NA    NA    NA    NA    NA    NA    NA    NA</span>
-<span class="co"># 5 Actinomycetales Micrococcus       NA    NA    NA    NA    NA    NA    NA    NA</span>
-<span class="co"># 6 Actinomycetales Rothia            NA    NA    NA    NA    NA    NA    NA    NA</span></code></pre></div>
+<span class="co"># # Groups:   order [5]</span>
+<span class="co">#   order            genus           AMC   CXM   CTX   CAZ   GEN   TOB   TMP   SXT</span>
+<span class="co">#   &lt;chr&gt;            &lt;chr&gt;         &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;</span>
+<span class="co"># 1 (unknown order)  (unknown gen…    NA    NA    NA    NA    NA    NA    NA    NA</span>
+<span class="co"># 2 Actinomycetales  Schaalia         NA    NA    NA    NA    NA    NA    NA    NA</span>
+<span class="co"># 3 Bacteroidales    Bacteroides      NA    NA    NA    NA    NA    NA    NA    NA</span>
+<span class="co"># 4 Campylobacteral… Campylobacter    NA    NA    NA    NA    NA    NA    NA    NA</span>
+<span class="co"># 5 Caryophanales    Gemella          NA    NA    NA    NA    NA    NA    NA    NA</span>
+<span class="co"># 6 Caryophanales    Listeria         NA    NA    NA    NA    NA    NA    NA    NA</span></pre></div>
 </div>
 <div id="perform-principal-component-analysis" class="section level1">
 <h1 class="hasAnchor">
 <a href="#perform-principal-component-analysis" class="anchor"></a>Perform principal component analysis</h1>
 <p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows that contain numeric values in all selected variables, so we now only need to do:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
-<span class="co"># NOTE: Columns selected for PCA: AMC CXM CTX CAZ GEN TOB TMP SXT. Total</span>
-<span class="co">#       observations available: 7.</span></code></pre></div>
+<div class="sourceCode" id="cb3"><pre class="downlit">
+<span class="va">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
+<span class="co"># ℹ Columns selected for PCA: "AMC", "CAZ", "CTX", "CXM", "GEN", "SXT", "TMP"</span>
+<span class="co">#   and "TOB". Total observations available: 7.</span></pre></div>
 <p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html">summary()</a></code> function:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span>
+<div class="sourceCode" id="cb4"><pre class="downlit">
+<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span>
+<span class="co"># Groups (n=4, named as 'order'):</span>
+<span class="co"># [1] "Caryophanales"    "Enterobacterales" "Lactobacillales"  "Pseudomonadales"</span>
 <span class="co"># Importance of components:</span>
-<span class="co">#                          PC1    PC2     PC3     PC4     PC5     PC6       PC7</span>
-<span class="co"># Standard deviation     2.154 1.6807 0.61365 0.33902 0.20757 0.03136 1.733e-16</span>
-<span class="co"># Proportion of Variance 0.580 0.3531 0.04707 0.01437 0.00539 0.00012 0.000e+00</span>
-<span class="co"># Cumulative Proportion  0.580 0.9331 0.98012 0.99449 0.99988 1.00000 1.000e+00</span></code></pre></div>
+<span class="co">#                           PC1    PC2    PC3     PC4     PC5     PC6       PC7</span>
+<span class="co"># Standard deviation     2.1539 1.6807 0.6138 0.33879 0.20808 0.03140 5.121e-17</span>
+<span class="co"># Proportion of Variance 0.5799 0.3531 0.0471 0.01435 0.00541 0.00012 0.000e+00</span>
+<span class="co"># Cumulative Proportion  0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00</span></pre></div>
+<pre><code># Groups (n=4, named as 'order'):
+# [1] "Caryophanales"    "Enterobacterales" "Lactobacillales"  "Pseudomonadales"</code></pre>
 <p>Good news. The first two components explain a total of 93.3% of the variance (see the PC1 and PC2 values of the <em>Proportion of Variance</em>. We can create a so-called biplot with the base R <code><a href="https://rdrr.io/r/stats/biplot.html">biplot()</a></code> function, to see which antimicrobial resistance per drug explain the difference per microorganism.</p>
 </div>
 <div id="plotting-the-results" class="section level1">
 <h1 class="hasAnchor">
 <a href="#plotting-the-results" class="anchor"></a>Plotting the results</h1>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/stats/biplot.html">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb6"><pre class="downlit">
+<span class="fu"><a href="https://rdrr.io/r/stats/biplot.html">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></pre></div>
 <p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" width="750"></p>
 <p>But we can’t see the explanation of the points. Perhaps this works better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that automatically adds the right labels and even groups:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb7"><pre class="downlit">
+<span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></pre></div>
 <p><img src="PCA_files/figure-html/unnamed-chunk-6-1.png" width="750"></p>
 <p>You can also print an ellipse per group, and edit the appearance:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span>, ellipse <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">+</span>
-  <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"An AMR/PCA biplot!"</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb8"><pre class="downlit">
+<span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span>, ellipse <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">+</span>
+  <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"An AMR/PCA biplot!"</span><span class="op">)</span></pre></div>
 <p><img src="PCA_files/figure-html/unnamed-chunk-7-1.png" width="750"></p>
 </div>
  </div>
@@ -39,7 +39,7 @@
      </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">1.5.0.9014</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -47,14 +47,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -63,77 +63,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -142,21 +142,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -165,14 +165,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -187,13 +187,14 @@

      

-      </header><script src="SPSS_files/header-attrs-2.6/header-attrs.js"></script><div class="row">
+      </header><link href="SPSS_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
+<script src="SPSS_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
  <div class="col-md-9 contents">
    <div class="page-header toc-ignore">
      <h1 data-toc-skip>How to import data from SPSS / SAS / Stata</h1>
                        <h4 class="author">Matthijs S. Berends</h4>
            
-            <h4 class="date">02 February 2021</h4>
+            <h4 class="date">27 April 2021</h4>
      
      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/SPSS.Rmd"><code>vignettes/SPSS.Rmd</code></a></small>
      <div class="hidden name"><code>SPSS.Rmd</code></div>
@@ -228,7 +229,7 @@
 </li>
 <li>
 <p><strong>R has a huge community.</strong></p>
-<p>Many R users just ask questions on websites like <a href="https://stackoverflow.com">StackOverflow.com</a>, the largest online community for programmers. At the time of writing, <a href="https://stackoverflow.com/questions/tagged/r?sort=votes">385,525 R-related questions</a> have already been asked on this platform (that covers questions and answers for any programming language). In my own experience, most questions are answered within a couple of minutes.</p>
+<p>Many R users just ask questions on websites like <a href="https://stackoverflow.com">StackOverflow.com</a>, the largest online community for programmers. At the time of writing, <a href="https://stackoverflow.com/questions/tagged/r?sort=votes">398,952 R-related questions</a> have already been asked on this platform (that covers questions and answers for any programming language). In my own experience, most questions are answered within a couple of minutes.</p>
 </li>
 <li>
 <p><strong>R understands any data type, including SPSS/SAS/Stata.</strong></p>
@@ -247,8 +248,8 @@
 </li>
 </ul>
 <p>To demonstrate the first point:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># not all values are valid MIC values:</span>
+<div class="sourceCode" id="cb1"><pre class="downlit">
+<span class="co"># not all values are valid MIC values:</span>
 <span class="fu"><a href="../reference/as.mic.html">as.mic</a></span><span class="op">(</span><span class="fl">0.125</span><span class="op">)</span>
 <span class="co"># Class &lt;mic&gt;</span>
 <span class="co"># [1] 0.125</span>
@@ -279,7 +280,7 @@
 <span class="co"># [4] "fluclox"              "flucloxacilina"       "flucloxacillin"      </span>
 <span class="co"># [7] "flucloxacilline"      "flucloxacillinum"     "fluorochloroxacillin"</span>
 <span class="fu"><a href="../reference/ab_property.html">ab_atc</a></span><span class="op">(</span><span class="st">"floxapen"</span><span class="op">)</span>
-<span class="co"># [1] "J01CF05"</span></code></pre></div>
+<span class="co"># [1] "J01CF05"</span></pre></div>
 </div>
 <div id="import-data-from-spsssasstata" class="section level2">
 <h2 class="hasAnchor">
@@ -295,8 +296,8 @@
 <p><img src="https://github.com/msberends/AMR/raw/master/docs/import2.png"></p>
 <p>If you want named variables to be imported as factors so it resembles SPSS more, use <code><a href="https://haven.tidyverse.org/reference/as_factor.html">as_factor()</a></code>.</p>
 <p>The difference is this:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">SPSS_data</span>
+<div class="sourceCode" id="cb2"><pre class="downlit">
+<span class="va">SPSS_data</span>
 <span class="co"># # A tibble: 4,203 x 4</span>
 <span class="co">#     v001 sex       status    statusage</span>
 <span class="co">#    &lt;dbl&gt; &lt;dbl+lbl&gt; &lt;dbl+lbl&gt;     &lt;dbl&gt;</span>
@@ -326,74 +327,74 @@
 <span class="co">#  8 10011 Male   alive       73.1</span>
 <span class="co">#  9 10017 Male   alive       56.7</span>
 <span class="co"># 10 10018 Female alive       66.6</span>
-<span class="co"># # … with 4,193 more rows</span></code></pre></div>
+<span class="co"># # … with 4,193 more rows</span></pre></div>
 </div>
 <div id="base-r" class="section level3">
 <h3 class="hasAnchor">
 <a href="#base-r" class="anchor"></a>Base R</h3>
 <p>To import data from SPSS, SAS or Stata, you can use the <a href="https://haven.tidyverse.org/">great <code>haven</code> package</a> yourself:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># download and install the latest version:</span>
+<div class="sourceCode" id="cb3"><pre class="downlit">
+<span class="co"># download and install the latest version:</span>
 <span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"haven"</span><span class="op">)</span>
 <span class="co"># load the package you just installed:</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="http://haven.tidyverse.org">haven</a></span><span class="op">)</span> </code></pre></div>
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="http://haven.tidyverse.org">haven</a></span><span class="op">)</span> </pre></div>
 <p>You can now import files as follows:</p>
 <div id="spss" class="section level4">
 <h4 class="hasAnchor">
 <a href="#spss" class="anchor"></a>SPSS</h4>
 <p>To read files from SPSS into R:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># read any SPSS file based on file extension (best way):</span>
+<div class="sourceCode" id="cb4"><pre class="downlit">
+<span class="co"># read any SPSS file based on file extension (best way):</span>
 <span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_spss</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>

 <span class="co"># read .sav or .zsav file:</span>
 <span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_sav</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>

 <span class="co"># read .por file:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_por</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></code></pre></div>
+<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_por</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></pre></div>
 <p>Do not forget about <code><a href="https://haven.tidyverse.org/reference/as_factor.html">as_factor()</a></code>, as mentioned above.</p>
 <p>To export your R objects to the SPSS file format:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># save as .sav file:</span>
+<div class="sourceCode" id="cb5"><pre class="downlit">
+<span class="co"># save as .sav file:</span>
 <span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">write_sav</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>

 <span class="co"># save as compressed .zsav file:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">write_sav</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, compress <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div>
+<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">write_sav</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, compress <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></pre></div>
 </div>
 <div id="sas" class="section level4">
 <h4 class="hasAnchor">
 <a href="#sas" class="anchor"></a>SAS</h4>
 <p>To read files from SAS into R:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># read .sas7bdat + .sas7bcat files:</span>
+<div class="sourceCode" id="cb6"><pre class="downlit">
+<span class="co"># read .sas7bdat + .sas7bcat files:</span>
 <span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html">read_sas</a></span><span class="op">(</span>data_file <span class="op">=</span> <span class="st">"path/to/file"</span>, catalog_file <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span>

 <span class="co"># read SAS transport files (version 5 and version 8):</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">read_xpt</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></code></pre></div>
+<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">read_xpt</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></pre></div>
 <p>To export your R objects to the SAS file format:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># save as regular SAS file:</span>
+<div class="sourceCode" id="cb7"><pre class="downlit">
+<span class="co"># save as regular SAS file:</span>
 <span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html">write_sas</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>

 <span class="co"># the SAS transport format is an open format </span>
 <span class="co"># (required for submission of the data to the FDA)</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">write_xpt</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, version <span class="op">=</span> <span class="fl">8</span><span class="op">)</span></code></pre></div>
+<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">write_xpt</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, version <span class="op">=</span> <span class="fl">8</span><span class="op">)</span></pre></div>
 </div>
 <div id="stata" class="section level4">
 <h4 class="hasAnchor">
 <a href="#stata" class="anchor"></a>Stata</h4>
 <p>To read files from Stata into R:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># read .dta file:</span>
+<div class="sourceCode" id="cb8"><pre class="downlit">
+<span class="co"># read .dta file:</span>
 <span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">read_stata</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span>

 <span class="co"># works exactly the same:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">read_dta</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span></code></pre></div>
+<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">read_dta</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span></pre></div>
 <p>To export your R objects to the Stata file format:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># save as .dta file, Stata version 14:</span>
+<div class="sourceCode" id="cb9"><pre class="downlit">
+<span class="co"># save as .dta file, Stata version 14:</span>
 <span class="co"># (supports Stata v8 until v15 at the time of writing)</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">write_dta</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"/path/to/file"</span>, version <span class="op">=</span> <span class="fl">14</span><span class="op">)</span></code></pre></div>
+<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">write_dta</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"/path/to/file"</span>, version <span class="op">=</span> <span class="fl">14</span><span class="op">)</span></pre></div>
 </div>
 </div>
 </div>
@@ -39,7 +39,7 @@
      </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">1.5.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -47,14 +47,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -63,77 +63,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -142,21 +142,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -165,14 +165,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -187,7 +187,8 @@

      

-      </header><script src="WHONET_files/header-attrs-2.6/header-attrs.js"></script><div class="row">
+      </header><link href="WHONET_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
+<script src="WHONET_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
  <div class="col-md-9 contents">
    <div class="page-header toc-ignore">
      <h1 data-toc-skip>How to work with WHONET data</h1>
@@ -205,38 +206,38 @@
 <a href="#import-of-data" class="anchor"></a>Import of data</h3>
 <p>This tutorial assumes you already imported the WHONET data with e.g. the <a href="https://readxl.tidyverse.org/"><code>readxl</code> package</a>. In RStudio, this can be done using the menu button ‘Import Dataset’ in the tab ‘Environment’. Choose the option ‘From Excel’ and select your exported file. Make sure date fields are imported correctly.</p>
 <p>An example syntax could look like this:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://readxl.tidyverse.org">readxl</a></span><span class="op">)</span>
-<span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html">read_excel</a></span><span class="op">(</span>path <span class="op">=</span> <span class="st">"path/to/your/file.xlsx"</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb1"><pre class="downlit">
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://readxl.tidyverse.org">readxl</a></span><span class="op">)</span>
+<span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html">read_excel</a></span><span class="op">(</span>path <span class="op">=</span> <span class="st">"path/to/your/file.xlsx"</span><span class="op">)</span></pre></div>
 <p>This package comes with an <a href="https://msberends.github.io/AMR/reference/WHONET.html">example data set <code>WHONET</code></a>. We will use it for this analysis.</p>
 </div>
 <div id="preparation" class="section level3">
 <h3 class="hasAnchor">
 <a href="#preparation" class="anchor"></a>Preparation</h3>
 <p>First, load the relevant packages if you did not yet did this. I use the tidyverse for all of my analyses. All of them. If you don’t know it yet, I suggest you read about it on their website: <a href="https://www.tidyverse.org/" class="uri">https://www.tidyverse.org/</a>.</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>   <span class="co"># part of tidyverse</span>
+<div class="sourceCode" id="cb2"><pre class="downlit">
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>   <span class="co"># part of tidyverse</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="http://ggplot2.tidyverse.org">ggplot2</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>     <span class="co"># this package</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></pre></div>
 <p>We will have to transform some variables to simplify and automate the analysis:</p>
 <ul>
 <li>Microorganisms should be transformed to our own microorganism IDs (called an <code>mo</code>) using <a href="https://msberends.github.io/AMR/reference/catalogue_of_life">our Catalogue of Life reference data set</a>, which contains all ~70,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>. This function also recognises almost all WHONET abbreviations of microorganisms.</li>
 <li>Antimicrobial results or interpretations have to be clean and valid. In other words, they should only contain values <code>"S"</code>, <code>"I"</code> or <code>"R"</code>. That is exactly where the <code><a href="../reference/as.rsi.html">as.rsi()</a></code> function is for.</li>
 </ul>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># transform variables</span>
+<div class="sourceCode" id="cb3"><pre class="downlit">
+<span class="co"># transform variables</span>
 <span class="va">data</span> <span class="op">&lt;-</span> <span class="va">WHONET</span> <span class="op">%&gt;%</span>
  <span class="co"># get microbial ID based on given organism</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">Organism</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span> 
  <span class="co"># transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class</span>
-  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span><span class="op">(</span><span class="va">AMP_ND10</span><span class="op">:</span><span class="va">CIP_EE</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span></code></pre></div>
+  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span><span class="op">(</span><span class="va">AMP_ND10</span><span class="op">:</span><span class="va">CIP_EE</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span></pre></div>
 <p>No errors or warnings, so all values are transformed succesfully.</p>
 <p>We also created a package dedicated to data cleaning and checking, called the <code>cleaner</code> package. Its <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> function can be used to create frequency tables.</p>
 <p>So let’s check our data, with a couple of frequency tables:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># our newly created `mo` variable, put in the mo_name() function</span>
-<span class="va">data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, nmax <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb4"><pre class="downlit">
+<span class="co"># our newly created `mo` variable, put in the mo_name() function</span>
+<span class="va">data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, nmax <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></pre></div>
 <p><strong>Frequency table</strong></p>
 <p>Class: character<br>
 Length: 500<br>
@@ -337,10 +338,10 @@ Longest: 40</p>
 </tbody>
 </table>
 <p>(omitted 27 entries, n = 56 [11.20%])</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># our transformed antibiotic columns</span>
+<div class="sourceCode" id="cb5"><pre class="downlit">
+<span class="co"># our transformed antibiotic columns</span>
 <span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span>
-<span class="va">data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">AMC_ND2</span><span class="op">)</span></code></pre></div>
+<span class="va">data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">AMC_ND2</span><span class="op">)</span></pre></div>
 <p><strong>Frequency table</strong></p>
 <p>Class: factor &gt; ordered &gt; rsi (numeric)<br>
 Length: 500<br>
@@ -391,11 +392,11 @@ Drug group: Beta-lactams/penicillins<br>
 <h3 class="hasAnchor">
 <a href="#a-first-glimpse-at-results" class="anchor"></a>A first glimpse at results</h3>
 <p>An easy <code>ggplot</code> will already give a lot of information, using the included <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> function:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op">%&gt;%</span>
+<div class="sourceCode" id="cb6"><pre class="downlit">
+<span class="va">data</span> <span class="op">%&gt;%</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span><span class="va">Country</span><span class="op">)</span> <span class="op">%&gt;%</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">Country</span>, <span class="va">AMP_ND2</span>, <span class="va">AMC_ED20</span>, <span class="va">CAZ_ED10</span>, <span class="va">CIP_ED5</span><span class="op">)</span> <span class="op">%&gt;%</span>
-  <span class="fu"><a href="../reference/ggplot_rsi.html">ggplot_rsi</a></span><span class="op">(</span>translate_ab <span class="op">=</span> <span class="st">'ab'</span>, facet <span class="op">=</span> <span class="st">"Country"</span>, datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
+  <span class="fu"><a href="../reference/ggplot_rsi.html">ggplot_rsi</a></span><span class="op">(</span>translate_ab <span class="op">=</span> <span class="st">'ab'</span>, facet <span class="op">=</span> <span class="st">"Country"</span>, datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></pre></div>
 <p><img src="WHONET_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
 </div>
  </div>
@@ -39,7 +39,7 @@
      </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">1.5.0.9027</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -47,14 +47,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -63,77 +63,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -142,21 +142,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -165,14 +165,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -187,7 +187,8 @@

      

-      </header><script src="benchmarks_files/header-attrs-2.6/header-attrs.js"></script><div class="row">
+      </header><link href="benchmarks_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
+<script src="benchmarks_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
  <div class="col-md-9 contents">
    <div class="page-header toc-ignore">
      <h1 data-toc-skip>Benchmarks</h1>
@@ -202,15 +203,15 @@
    
 <p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://www.catalogueoflife.org">Catalogue of Life</a> (CoL) and the <a href="https://lpsn.dsmz.de">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN). We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the microbial taxonomy.</p>
 <p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/">microbenchmark</a></span><span class="op">)</span>
+<div class="sourceCode" id="cb1"><pre class="downlit">
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/">microbenchmark</a></span><span class="op">)</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span></code></pre></div>
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span></pre></div>
 <p>In the next test, we try to ‘coerce’ different input values into the microbial code of <em>Staphylococcus aureus</em>. Coercion is a computational process of forcing output based on an input. For microorganism names, coercing user input to taxonomically valid microorganism names is crucial to ensure correct interpretation and to enable grouping based on taxonomic properties.</p>
 <p>The actual result is the same every time: it returns its microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for <em>Bacteria</em>, its taxonomic kingdom).</p>
 <p>But the calculation time differs a lot:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">S.aureus</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>
+<div class="sourceCode" id="cb2"><pre class="downlit">
+<span class="va">S.aureus</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>
  <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"sau"</span><span class="op">)</span>, <span class="co"># WHONET code</span>
  <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"stau"</span><span class="op">)</span>,
  <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"STAU"</span><span class="op">)</span>,
@@ -224,21 +225,21 @@
  <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"MRSA"</span><span class="op">)</span>, <span class="co"># Methicillin Resistant S. aureus</span>
  <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"VISA"</span><span class="op">)</span>, <span class="co"># Vancomycin Intermediate S. aureus</span>
  times <span class="op">=</span> <span class="fl">25</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>
+<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>
 <span class="co"># Unit: milliseconds</span>
-<span class="co">#                                   expr   min    lq  mean median    uq max neval</span>
-<span class="co">#                           as.mo("sau")   9.9  11.0  13.0   11.0  12.0  43    25</span>
-<span class="co">#                          as.mo("stau")  52.0  55.0  68.0   58.0  86.0  95    25</span>
-<span class="co">#                          as.mo("STAU")  53.0  56.0  73.0   62.0  93.0 100    25</span>
-<span class="co">#                        as.mo("staaur")  10.0  11.0  17.0   11.0  12.0  48    25</span>
-<span class="co">#                        as.mo("STAAUR")  10.0  11.0  14.0   11.0  13.0  48    25</span>
-<span class="co">#                     as.mo("S. aureus")  27.0  28.0  41.0   33.0  60.0  73    25</span>
-<span class="co">#                      as.mo("S aureus")  27.0  28.0  49.0   34.0  64.0 160    25</span>
-<span class="co">#         as.mo("Staphylococcus aureus")   2.9   3.2   4.8    3.4   3.7  36    25</span>
-<span class="co">#  as.mo("Staphylococcus aureus (MRSA)") 250.0 260.0 270.0  270.0 280.0 320    25</span>
-<span class="co">#       as.mo("Sthafilokkockus aaureuz") 170.0 200.0 210.0  210.0 210.0 310    25</span>
-<span class="co">#                          as.mo("MRSA")  10.0  11.0  16.0   12.0  12.0  50    25</span>
-<span class="co">#                          as.mo("VISA")  19.0  20.0  27.0   21.0  23.0  60    25</span></code></pre></div>
+<span class="co">#                                   expr   min    lq mean median    uq max neval</span>
+<span class="co">#                           as.mo("sau")  25.0  25.0   30   26.0  26.0  83    25</span>
+<span class="co">#                          as.mo("stau") 120.0 130.0  150  130.0 180.0 390    25</span>
+<span class="co">#                          as.mo("STAU") 120.0 130.0  150  130.0 180.0 190    25</span>
+<span class="co">#                        as.mo("staaur")  25.0  26.0   33   26.0  26.0  83    25</span>
+<span class="co">#                        as.mo("STAAUR")  25.0  26.0   33   26.0  26.0  83    25</span>
+<span class="co">#                     as.mo("S. aureus")  66.0  66.0   89   67.0 120.0 150    25</span>
+<span class="co">#                      as.mo("S aureus")  66.0  66.0   74   66.0  67.0 120    25</span>
+<span class="co">#         as.mo("Staphylococcus aureus")   6.8   6.9   14    6.9   7.5  63    25</span>
+<span class="co">#  as.mo("Staphylococcus aureus (MRSA)") 550.0 550.0  560  550.0 560.0 620    25</span>
+<span class="co">#       as.mo("Sthafilokkockus aaureuz") 410.0 420.0  430  420.0 420.0 620    25</span>
+<span class="co">#                          as.mo("MRSA")  25.0  26.0   31   26.0  26.0  83    25</span>
+<span class="co">#                          as.mo("VISA")  46.0  47.0   65   47.0  98.0 110    25</span></pre></div>
 <p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="750"></p>
 <p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 200 milliseconds, this is only 5 input values per second. It is clear that accepted taxonomic names are extremely fast, but some variations are up to 200 times slower to determine.</p>
 <p>To improve performance, we implemented two important algorithms to save unnecessary calculations: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
@@ -247,8 +248,8 @@
 <a href="#repetitive-results" class="anchor"></a>Repetitive results</h3>
 <p>Repetitive results are values that are present more than once in a vector. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. So running <code><a href="../reference/as.mo.html">as.mo(c("E. coli", "E. coli"))</a></code> will check the value <code>"E. coli"</code> only once.</p>
 <p>To prove this, we will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for testing - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># start with the example_isolates data set</span>
+<div class="sourceCode" id="cb3"><pre class="downlit">
+<span class="co"># start with the example_isolates data set</span>
 <span class="va">x</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op">%&gt;%</span> 
  <span class="co"># take all MO codes from the 'mo' column</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span> <span class="op">%&gt;%</span>
@@ -260,8 +261,8 @@
 <span class="co"># what do these values look like? They are of class &lt;mo&gt;:</span>
 <span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
 <span class="co"># Class &lt;mo&gt;</span>
-<span class="co"># [1] B_STRPT_PYGN  B_STPHY_HMNS  B_STPHY_CONS  B_STRPT_SLVR  B_ENTRBC_CLOC</span>
-<span class="co"># [6] B_STPHY_CONS</span>
+<span class="co"># [1] B_STPHY_EPDR B_STPHY_EPDR B_STPHY_CONS B_STPHY_CONS B_STPHY_EPDR</span>
+<span class="co"># [6] B_ESCHR_COLI</span>
  
 <span class="co"># as the example_isolates data set has 2,000 rows, we should have 2 million items</span>
 <span class="fu"><a href="https://rdrr.io/r/base/length.html">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
@@ -274,30 +275,30 @@
 <span class="co"># now let's see:</span>
 <span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>,
                         times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
+<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
 <span class="co"># Unit: milliseconds</span>
 <span class="co">#        expr min  lq mean median  uq max neval</span>
-<span class="co">#  mo_name(x) 161 194  224    204 229 368    10</span></code></pre></div>
-<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.204 seconds. That is 102 nanoseconds on average. You only lose time on your unique input values.</p>
+<span class="co">#  mo_name(x) 321 378  443    410 438 713    10</span></pre></div>
+<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.41 seconds. That is 205 nanoseconds on average. You only lose time on your unique input values.</p>
 </div>
 <div id="precalculated-results" class="section level3">
 <h3 class="hasAnchor">
 <a href="#precalculated-results" class="anchor"></a>Precalculated results</h3>
 <p>What about precalculated results? If the input is an already precalculated result of a helper function such as <code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesn’t take any time at all. In other words, if you run <code><a href="../reference/mo_property.html">mo_name()</a></code> on a valid taxonomic name, it will return the results immediately (see ‘C’ below):</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
+<div class="sourceCode" id="cb4"><pre class="downlit">
+<span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
                         B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>,
                         C <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span>,
                         times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
+<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
 <span class="co"># Unit: milliseconds</span>
-<span class="co">#  expr   min    lq  mean median    uq   max neval</span>
-<span class="co">#     A  7.45  7.84 12.70   8.62  9.16 51.10    10</span>
-<span class="co">#     B 23.80 24.50 30.60  26.30 28.80 70.20    10</span>
-<span class="co">#     C  1.66  1.74  1.85   1.79  1.92  2.24    10</span></code></pre></div>
-<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0018 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>,
+<span class="co">#  expr   min   lq  mean median    uq    max neval</span>
+<span class="co">#     A 17.00 17.1 17.10  17.10 17.20  17.20    10</span>
+<span class="co">#     B 57.20 57.3 68.90  57.60 58.40 117.00    10</span>
+<span class="co">#     C  3.66  3.7  3.74   3.74  3.77   3.89    10</span></pre></div>
+<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0037 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
+<div class="sourceCode" id="cb5"><pre class="downlit">
+<span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>,
                         B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"Staphylococcus"</span><span class="op">)</span>,
                         C <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span>,
                         D <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="st">"Staphylococcaceae"</span><span class="op">)</span>,
@@ -306,25 +307,25 @@
                         G <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_phylum</a></span><span class="op">(</span><span class="st">"Firmicutes"</span><span class="op">)</span>,
                         H <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_kingdom</a></span><span class="op">(</span><span class="st">"Bacteria"</span><span class="op">)</span>,
                         times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
+<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
 <span class="co"># Unit: milliseconds</span>
 <span class="co">#  expr  min   lq mean median   uq  max neval</span>
-<span class="co">#     A 1.59 1.60 1.91   1.97 2.15 2.28    10</span>
-<span class="co">#     B 1.58 1.61 1.87   1.86 1.96 2.39    10</span>
-<span class="co">#     C 1.55 1.57 1.64   1.63 1.69 1.79    10</span>
-<span class="co">#     D 1.57 1.60 1.83   1.72 1.92 2.73    10</span>
-<span class="co">#     E 1.50 1.74 1.86   1.86 2.03 2.24    10</span>
-<span class="co">#     F 1.49 1.55 1.75   1.67 1.90 2.24    10</span>
-<span class="co">#     G 1.54 1.59 1.69   1.65 1.77 1.95    10</span>
-<span class="co">#     H 1.57 1.58 1.75   1.72 1.78 2.21    10</span></code></pre></div>
+<span class="co">#     A 3.70 3.71 3.81   3.74 3.82 4.14    10</span>
+<span class="co">#     B 3.66 3.67 3.76   3.69 3.76 4.10    10</span>
+<span class="co">#     C 3.66 3.70 3.72   3.72 3.73 3.76    10</span>
+<span class="co">#     D 3.63 3.67 3.77   3.71 3.88 4.09    10</span>
+<span class="co">#     E 3.62 3.67 3.75   3.70 3.78 4.07    10</span>
+<span class="co">#     F 3.62 3.64 3.66   3.65 3.65 3.74    10</span>
+<span class="co">#     G 3.63 3.64 3.67   3.67 3.68 3.75    10</span>
+<span class="co">#     H 3.63 3.64 3.74   3.67 3.84 4.07    10</span></pre></div>
 <p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> anyway, there is no point in calculating the result. And because this package contains all phyla of all known bacteria, it can just return the initial value immediately.</p>
 </div>
 <div id="results-in-other-languages" class="section level3">
 <h3 class="hasAnchor">
 <a href="#results-in-other-languages" class="anchor"></a>Results in other languages</h3>
 <p>When the system language is non-English and supported by this <code>AMR</code> package, some functions will have a translated result. This almost does’t take extra time:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span> <span class="co"># or just mo_name("CoNS") on an English system</span>
+<div class="sourceCode" id="cb6"><pre class="downlit">
+<span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span> <span class="co"># or just mo_name("CoNS") on an English system</span>
 <span class="co"># [1] "Coagulase-negative Staphylococcus (CoNS)"</span>

 <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span> <span class="co"># or just mo_name("CoNS") on a Spanish system</span>
@@ -341,16 +342,16 @@
                         fr <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"fr"</span><span class="op">)</span>,
                         pt <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"pt"</span><span class="op">)</span>,
                         times <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span>
+<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span>
 <span class="co"># Unit: milliseconds</span>
 <span class="co">#  expr   min    lq  mean median    uq   max neval</span>
-<span class="co">#    en 17.33 18.21 21.97  19.06 20.40 68.32   100</span>
-<span class="co">#    de 20.44 21.37 30.49  22.33 24.97 78.42   100</span>
-<span class="co">#    nl 25.13 26.10 31.91  27.11 28.50 86.00   100</span>
-<span class="co">#    es 20.28 21.16 26.37  22.03 23.67 74.74   100</span>
-<span class="co">#    it 20.06 21.00 26.05  21.95 23.42 94.16   100</span>
-<span class="co">#    fr 19.90 20.63 24.40  21.85 22.82 69.07   100</span>
-<span class="co">#    pt 20.22 21.03 25.63  21.89 23.24 76.63   100</span></code></pre></div>
+<span class="co">#    en 43.15 43.49 48.88  43.66 43.81 122.3   100</span>
+<span class="co">#    de 79.59 80.39 88.27  80.89 81.11 135.8   100</span>
+<span class="co">#    nl 79.69 80.45 87.16  80.81 81.07 136.6   100</span>
+<span class="co">#    es 79.28 80.12 89.84  80.51 81.02 159.5   100</span>
+<span class="co">#    it 51.74 52.20 55.59  52.39 52.61 109.1   100</span>
+<span class="co">#    fr 51.43 51.88 54.83  52.05 52.29 105.5   100</span>
+<span class="co">#    pt 51.58 51.93 59.25  52.28 52.55 111.8   100</span></pre></div>
 <p>Currently supported non-English languages are German, Dutch, Spanish, Italian, French and Portuguese.</p>
 </div>
  </div>
@@ -39,7 +39,7 @@
      </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">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -47,14 +47,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -63,77 +63,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -142,21 +142,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -165,14 +165,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -187,12 +187,13 @@

      

-      </header><script src="datasets_files/header-attrs-2.7/header-attrs.js"></script><div class="row">
+      </header><link href="datasets_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
+<script src="datasets_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
  <div class="col-md-9 contents">
    <div class="page-header toc-ignore">
      <h1 data-toc-skip>Data sets for download / own use</h1>
            
-            <h4 class="date">11 March 2021</h4>
+            <h4 class="date">27 April 2021</h4>
      
      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/datasets.Rmd"><code>vignettes/datasets.Rmd</code></a></small>
      <div class="hidden name"><code>datasets.Rmd</code></div>
@@ -211,7 +212,7 @@ If you are reading this page from within R, please <a href="https://msberends.gi
 <a href="#microorganisms-currently-accepted-names" class="anchor"></a>Microorganisms (currently accepted names)</h2>
 <p>A data set with 70,026 rows and 16 columns, containing the following column names:<br><em>mo</em>, <em>fullname</em>, <em>kingdom</em>, <em>phylum</em>, <em>class</em>, <em>order</em>, <em>family</em>, <em>genus</em>, <em>species</em>, <em>subspecies</em>, <em>rank</em>, <em>ref</em>, <em>species_id</em>, <em>source</em>, <em>prevalence</em> and <em>snomed</em>.</p>
 <p>This data set is in R available as <code>microorganisms</code>, after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 11 March 2021 20:59:32 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.html">here</a>.</p>
+<p>It was last updated on 27 April 2021 08:12:46 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.rds">R file</a> (2.2 MB)<br>
@@ -432,7 +433,7 @@ If you are reading this page from within R, please <a href="https://msberends.gi
 <p>A data set with 14,100 rows and 4 columns, containing the following column names:<br><em>fullname</em>, <em>fullname_new</em>, <em>ref</em> and <em>prevalence</em>.</p>
 <p><strong>Note:</strong> remember that the ‘ref’ columns contains the scientific reference to the old taxonomic entries, i.e. of column <em>‘fullname’</em>. For the scientific reference of the new names, i.e. of column <em>‘fullname_new’</em>, see the <code>microorganisms</code> data set.</p>
 <p>This data set is in R available as <code>microorganisms.old</code>, after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 5 March 2021 09:46:55 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.old.html">here</a>.</p>
+<p>It was last updated on 27 April 2021 08:12:46 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.old.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.rds">R file</a> (0.2 MB)<br>
@@ -497,7 +498,7 @@ If you are reading this page from within R, please <a href="https://msberends.gi
 <a href="#antibiotic-agents" class="anchor"></a>Antibiotic agents</h2>
 <p>A data set with 456 rows and 14 columns, containing the following column names:<br><em>ab</em>, <em>atc</em>, <em>cid</em>, <em>name</em>, <em>group</em>, <em>atc_group1</em>, <em>atc_group2</em>, <em>abbreviations</em>, <em>synonyms</em>, <em>oral_ddd</em>, <em>oral_units</em>, <em>iv_ddd</em>, <em>iv_units</em> and <em>loinc</em>.</p>
 <p>This data set is in R available as <code>antibiotics</code>, after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 11 March 2021 20:59:32 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/antibiotics.html">here</a>.</p>
+<p>It was last updated on 27 April 2021 08:12:46 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/antibiotics.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.rds">R file</a> (32 kB)<br>
@@ -665,7 +666,7 @@ If you are reading this page from within R, please <a href="https://msberends.gi
 <a href="#antiviral-agents" class="anchor"></a>Antiviral agents</h2>
 <p>A data set with 102 rows and 9 columns, containing the following column names:<br><em>atc</em>, <em>cid</em>, <em>name</em>, <em>atc_group</em>, <em>synonyms</em>, <em>oral_ddd</em>, <em>oral_units</em>, <em>iv_ddd</em> and <em>iv_units</em>.</p>
 <p>This data set is in R available as <code>antivirals</code>, after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 29 August 2020 19:53:07 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/antibiotics.html">here</a>.</p>
+<p>It was last updated on 27 April 2021 08:12:46 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/antibiotics.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.rds">R file</a> (5 kB)<br>
@@ -792,7 +793,7 @@ If you are reading this page from within R, please <a href="https://msberends.gi
 <a href="#intrinsic-bacterial-resistance" class="anchor"></a>Intrinsic bacterial resistance</h2>
 <p>A data set with 93,892 rows and 2 columns, containing the following column names:<br><em>microorganism</em> and <em>antibiotic</em>.</p>
 <p>This data set is in R available as <code>intrinsic_resistant</code>, after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 5 March 2021 09:46:55 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/intrinsic_resistant.html">here</a>.</p>
+<p>It was last updated on 27 April 2021 08:12:46 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/intrinsic_resistant.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.rds">R file</a> (69 kB)<br>
@@ -1007,7 +1008,7 @@ If you are reading this page from within R, please <a href="https://msberends.gi
 <a href="#interpretation-from-mic-values-disk-diameters-to-rsi" class="anchor"></a>Interpretation from MIC values / disk diameters to R/SI</h2>
 <p>A data set with 20,486 rows and 10 columns, containing the following column names:<br><em>guideline</em>, <em>method</em>, <em>site</em>, <em>mo</em>, <em>ab</em>, <em>ref_tbl</em>, <em>disk_dose</em>, <em>breakpoint_S</em>, <em>breakpoint_R</em> and <em>uti</em>.</p>
 <p>This data set is in R available as <code>rsi_translation</code>, after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 5 March 2021 09:46:55 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/rsi_translation.html">here</a>.</p>
+<p>It was last updated on 27 April 2021 08:12:46 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/rsi_translation.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.rds">R file</a> (34 kB)<br>
@@ -1137,7 +1138,7 @@ If you are reading this page from within R, please <a href="https://msberends.gi
 <a href="#dosage-guidelines-from-eucast" class="anchor"></a>Dosage guidelines from EUCAST</h2>
 <p>A data set with 169 rows and 9 columns, containing the following column names:<br><em>ab</em>, <em>name</em>, <em>type</em>, <em>dose</em>, <em>dose_times</em>, <em>administration</em>, <em>notes</em>, <em>original_txt</em> and <em>eucast_version</em>.</p>
 <p>This data set is in R available as <code>dosage</code>, after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 25 January 2021 20:58:20 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/dosage.html">here</a>.</p>
+<p>It was last updated on 27 April 2021 08:12:46 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/dosage.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.rds">R file</a> (3 kB)<br>
@@ -0,0 +1,4 @@
+/* Styles for section anchors */
+a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
+a.anchor-section::before {content: '#';}
+.hasAnchor:hover a.anchor-section {visibility: visible;}
@@ -0,0 +1,33 @@
+// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
+document.addEventListener('DOMContentLoaded', function() {
+  // Do nothing if AnchorJS is used
+  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
+    return;
+  }
+
+  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
+
+  // Do nothing if sections are already anchored
+  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
+    return null;
+  }
+
+  // Use section id when pandoc runs with --section-divs
+  const section_id = function(x) {
+    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
+            ? x.id : '');
+  };
+
+  // Add anchors
+  h.forEach(function(x) {
+    const id = x.id || section_id(x.parentElement);
+    if (id === '') {
+      return null;
+    }
+    let anchor = document.createElement('a');
+    anchor.href = '#' + id;
+    anchor.classList = ['anchor-section'];
+    x.classList.add('hasAnchor');
+    x.appendChild(anchor);
+  });
+});
@@ -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">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9012</span>
      </span>
    </div>

@@ -89,14 +89,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -105,77 +105,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -184,21 +184,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -207,14 +207,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -39,7 +39,7 @@
      </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">1.5.0.9018</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -47,14 +47,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -63,77 +63,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -142,21 +142,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -165,14 +165,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -187,7 +187,8 @@

      

-      </header><script src="resistance_predict_files/header-attrs-2.6/header-attrs.js"></script><div class="row">
+      </header><link href="resistance_predict_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
+<script src="resistance_predict_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
  <div class="col-md-9 contents">
    <div class="page-header toc-ignore">
      <h1 data-toc-skip>How to predict antimicrobial resistance</h1>
@@ -205,37 +206,37 @@
 <a href="#needed-r-packages" class="anchor"></a>Needed R packages</h2>
 <p>As with many uses in R, we need some additional packages for AMR data analysis. Our package works closely together with the <a href="https://www.tidyverse.org">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org"><code>ggplot2</code></a> by Dr Hadley Wickham. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.</p>
 <p>Our <code>AMR</code> package depends on these packages and even extends their use and functions.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
+<div class="sourceCode" id="cb1"><pre class="downlit">
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="http://ggplot2.tidyverse.org">ggplot2</a></span><span class="op">)</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>

 <span class="co"># (if not yet installed, install with:)</span>
-<span class="co"># install.packages(c("tidyverse", "AMR"))</span></code></pre></div>
+<span class="co"># install.packages(c("tidyverse", "AMR"))</span></pre></div>
 </div>
 <div id="prediction-analysis" class="section level2">
 <h2 class="hasAnchor">
 <a href="#prediction-analysis" class="anchor"></a>Prediction analysis</h2>
 <p>Our package contains a function <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>, which takes the same input as functions for <a href="./AMR.html">other AMR data analysis</a>. Based on a date column, it calculates cases per year and uses a regression model to predict antimicrobial resistance.</p>
 <p>It is basically as easy as:</p>
-<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># resistance prediction of piperacillin/tazobactam (TZP):</span></span>
-<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="fu">resistance_predict</span>(<span class="at">tbl =</span> example_isolates, <span class="at">col_date =</span> <span class="st">"date"</span>, <span class="at">col_ab =</span> <span class="st">"TZP"</span>, <span class="at">model =</span> <span class="st">"binomial"</span>)</span>
-<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a><span class="co"># or:</span></span>
-<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a>example_isolates <span class="sc">%&gt;%</span> </span>
-<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">resistance_predict</span>(<span class="at">col_ab =</span> <span class="st">"TZP"</span>,</span>
-<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a>                     model  <span class="st">"binomial"</span>)</span>
-<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a><span class="co"># to bind it to object 'predict_TZP' for example:</span></span>
-<span id="cb2-10"><a href="#cb2-10" aria-hidden="true" tabindex="-1"></a>predict_TZP <span class="ot">&lt;-</span> example_isolates <span class="sc">%&gt;%</span> </span>
-<span id="cb2-11"><a href="#cb2-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">resistance_predict</span>(<span class="at">col_ab =</span> <span class="st">"TZP"</span>,</span>
-<span id="cb2-12"><a href="#cb2-12" aria-hidden="true" tabindex="-1"></a>                     <span class="at">model =</span> <span class="st">"binomial"</span>)</span></code></pre></div>
+<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" title="1"><span class="co"># resistance prediction of piperacillin/tazobactam (TZP):</span></a>
+<a class="sourceLine" id="cb2-2" title="2"><span class="kw">resistance_predict</span>(<span class="dt">tbl =</span> example_isolates, <span class="dt">col_date =</span> <span class="st">"date"</span>, <span class="dt">col_ab =</span> <span class="st">"TZP"</span>, <span class="dt">model =</span> <span class="st">"binomial"</span>)</a>
+<a class="sourceLine" id="cb2-3" title="3"></a>
+<a class="sourceLine" id="cb2-4" title="4"><span class="co"># or:</span></a>
+<a class="sourceLine" id="cb2-5" title="5">example_isolates <span class="op">%&gt;%</span><span class="st"> </span></a>
+<a class="sourceLine" id="cb2-6" title="6"><span class="st">  </span><span class="kw">resistance_predict</span>(<span class="dt">col_ab =</span> <span class="st">"TZP"</span>,</a>
+<a class="sourceLine" id="cb2-7" title="7">                     model  <span class="st">"binomial"</span>)</a>
+<a class="sourceLine" id="cb2-8" title="8"></a>
+<a class="sourceLine" id="cb2-9" title="9"><span class="co"># to bind it to object 'predict_TZP' for example:</span></a>
+<a class="sourceLine" id="cb2-10" title="10">predict_TZP &lt;-<span class="st"> </span>example_isolates <span class="op">%&gt;%</span><span class="st"> </span></a>
+<a class="sourceLine" id="cb2-11" title="11"><span class="st">  </span><span class="kw">resistance_predict</span>(<span class="dt">col_ab =</span> <span class="st">"TZP"</span>,</a>
+<a class="sourceLine" id="cb2-12" title="12">                     <span class="dt">model =</span> <span class="st">"binomial"</span>)</a></code></pre></div>
 <p>The function will look for a date column itself if <code>col_date</code> is not set.</p>
 <p>When running any of these commands, a summary of the regression model will be printed unless using <code><a href="../reference/resistance_predict.html">resistance_predict(..., info = FALSE)</a></code>.</p>
-<pre><code># NOTE: Using column 'date' as input for `col_date`.</code></pre>
+<pre><code># ℹ Using column 'date' as input for `col_date`.</code></pre>
 <p>This text is only a printed summary - the actual result (output) of the function is a <code>data.frame</code> containing for each year: the number of observations, the actual observed resistance, the estimated resistance and the standard error below and above the estimation:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">predict_TZP</span>
+<div class="sourceCode" id="cb4"><pre class="downlit">
+<span class="va">predict_TZP</span>
 <span class="co">#    year      value    se_min    se_max observations   observed  estimated</span>
 <span class="co"># 1  2002 0.20000000        NA        NA           15 0.20000000 0.05616378</span>
 <span class="co"># 2  2003 0.06250000        NA        NA           32 0.06250000 0.06163839</span>
@@ -266,30 +267,30 @@
 <span class="co"># 27 2028 0.43730688 0.3418075 0.5328063           NA         NA 0.43730688</span>
 <span class="co"># 28 2029 0.46175755 0.3597639 0.5637512           NA         NA 0.46175755</span>
 <span class="co"># 29 2030 0.48639359 0.3782932 0.5944939           NA         NA 0.48639359</span>
-<span class="co"># 30 2031 0.51109592 0.3973697 0.6248221           NA         NA 0.51109592</span></code></pre></div>
+<span class="co"># 30 2031 0.51109592 0.3973697 0.6248221           NA         NA 0.51109592</span></pre></div>
 <p>The function <code>plot</code> is available in base R, and can be extended by other packages to depend the output based on the type of input. We extended its function to cope with resistance predictions:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb5"><pre class="downlit">
+<span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></pre></div>
 <p><img src="resistance_predict_files/figure-html/unnamed-chunk-4-1.png" width="720"></p>
 <p>This is the fastest way to plot the result. It automatically adds the right axes, error bars, titles, number of available observations and type of model.</p>
 <p>We also support the <code>ggplot2</code> package with our custom function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> to create more appealing plots:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb6"><pre class="downlit">
+<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></pre></div>
 <p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-1.png" width="720"></p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R">
+<div class="sourceCode" id="cb7"><pre class="downlit">
+
 <span class="co"># choose for error bars instead of a ribbon</span>
-<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span>, ribbon <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
+<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span>, ribbon <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></pre></div>
 <p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-2.png" width="720"></p>
 <div id="choosing-the-right-model" class="section level3">
 <h3 class="hasAnchor">
 <a href="#choosing-the-right-model" class="anchor"></a>Choosing the right model</h3>
 <p>Resistance is not easily predicted; if we look at vancomycin resistance in Gram-positive bacteria, the spread (i.e. standard error) is enormous:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op">%&gt;%</span>
+<div class="sourceCode" id="cb8"><pre class="downlit">
+<span class="va">example_isolates</span> <span class="op">%&gt;%</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op">%&gt;%</span>
  <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span> <span class="op">%&gt;%</span> 
-  <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
+  <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span></pre></div>
 <p><img src="resistance_predict_files/figure-html/unnamed-chunk-6-1.png" width="720"></p>
 <p>Vancomycin resistance could be 100% in ten years, but might also stay around 0%.</p>
 <p>You can define the model with the <code>model</code> parameter. The model chosen above is a generalised linear regression model using a binomial distribution, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance.</p>
@@ -330,16 +331,16 @@
 </tbody>
 </table>
 <p>For the vancomycin resistance in Gram-positive bacteria, a linear model might be more appropriate since no binomial distribution is to be expected based on the observed years:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op">%&gt;%</span>
+<div class="sourceCode" id="cb9"><pre class="downlit">
+<span class="va">example_isolates</span> <span class="op">%&gt;%</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op">%&gt;%</span>
  <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"linear"</span><span class="op">)</span> <span class="op">%&gt;%</span> 
-  <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
+  <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span></pre></div>
 <p><img src="resistance_predict_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
 <p>This seems more likely, doesn’t it?</p>
 <p>The model itself is also available from the object, as an <code>attribute</code>:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">model</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span>
+<div class="sourceCode" id="cb10"><pre class="downlit">
+<span class="va">model</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span>

 <span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">family</span>
 <span class="co"># </span>
@@ -349,7 +350,7 @@
 <span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">coefficients</span>
 <span class="co">#                  Estimate  Std. Error   z value     Pr(&gt;|z|)</span>
 <span class="co"># (Intercept) -200.67944891 46.17315349 -4.346237 1.384932e-05</span>
-<span class="co"># year           0.09883005  0.02295317  4.305725 1.664395e-05</span></code></pre></div>
+<span class="co"># year           0.09883005  0.02295317  4.305725 1.664395e-05</span></pre></div>
 </div>
 </div>
  </div>
@@ -39,7 +39,7 @@
      </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">1.5.0.9018</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -47,14 +47,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -63,77 +63,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -142,21 +142,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -165,14 +165,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -187,7 +187,8 @@

      

-      </header><script src="welcome_to_AMR_files/header-attrs-2.6/header-attrs.js"></script><div class="row">
+      </header><link href="welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
+<script src="welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
  <div class="col-md-9 contents">
    <div class="page-header toc-ignore">
      <h1 data-toc-skip>Welcome to the AMR package</h1>
@@ -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">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9012</span>
      </span>
    </div>

@@ -89,14 +89,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -105,77 +105,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -184,21 +184,21 @@
 </li>
 <li>
  <a href="reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -207,14 +207,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -236,13 +236,13 @@
      <small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/inst/CITATION'><code>inst/CITATION</code></a></small>
    </div>

-    <p>Berends MS, Luz CF et al. (2019). AMR - An R Package for Working with Antimicrobial Resistance Data. bioRxiv, https://doi.org/10.1101/810622</p>
+    <p>Berends MS, Luz CF et al. (2021). AMR - An R Package for Working with Antimicrobial Resistance Data. bioRxiv, https://doi.org/10.1101/810622</p>
    <pre>@Article{,
  title = {AMR - An R Package for Working with Antimicrobial Resistance Data},
  author = {M S Berends and C F Luz and A W Friedrich and B N M Sinha and C J Albers and C Glasner},
  journal = {bioRxiv},
  publisher = {Cold Spring Harbor Laboratory},
-  year = {2019},
+  year = {2021},
  url = {https://doi.org/10.1101/810622},
 }</pre>

@@ -19,11 +19,10 @@
 <!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="pkgdown.css" rel="stylesheet">
 <script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet">
 <script src="extra.js"></script><meta property="og:title" content="Antimicrobial Resistance Data Analysis">
-<meta property="og:description" content="Functions to simplify the analysis and prediction of Antimicrobial 
-    Resistance (AMR) and to work with microbial and antimicrobial properties by
-    using evidence-based methods, like those defined by Leclercq et al. (2013) 
-    &lt;doi:10.1111/j.1469-0691.2011.03703.x&gt; and containing reference data such as 
-    LPSN &lt;doi:10.1099/ijsem.0.004332&gt;.">
+<meta property="og:description" content="Functions to simplify and standardise antimicrobial resistance (AMR)
+    data analysis and to work with microbial and antimicrobial properties by
+    using evidence-based methods and reliable reference data such as LPSN
+    &lt;doi:10.1099/ijsem.0.004332&gt;.">
 <meta property="og:image" content="https://msberends.github.io/AMR/logo.png">
 <!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
@@ -43,7 +42,7 @@
      </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">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9012</span>
      </span>
    </div>

@@ -51,14 +50,14 @@
      <ul class="nav navbar-nav">
 <li>
  <a href="index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -67,77 +66,77 @@
  <ul class="dropdown-menu" role="menu">
 <li>
      <a href="articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -146,21 +145,21 @@
 </li>
 <li>
  <a href="reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -169,14 +168,14 @@
 <ul class="nav navbar-nav navbar-right">
 <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -197,16 +196,12 @@
 <div class="page-header"><h1 class="hasAnchor">
 <a href="#amr-for-r-" class="anchor"></a><code>AMR</code> (for R) <img src="./logo.png" align="right" height="120px">
 </h1></div>
-<p><em>Note: the rules of ‘EUCAST Clinical Breakpoints v11.0 (2021)’ are now implemented</em></p>
-<blockquote>
-<p><span class="fa fa-clipboard-list" style="color: #128f76; font-size: 20pt; margin-right: 5px;"></span> <strong>PLEASE TAKE PART IN OUR SURVEY!</strong><br>
-Since you are one of our users, we would like to know how you use the package and what it brought you or your organisation. <strong>If you have a minute, please <a href="./survey.html">anonymously fill in this short questionnaire</a></strong>. Your valuable input will help to improve the package and its functionalities. You can answer the open questions in either English, Spanish, French, Dutch, or German. Thank you very much in advance! <br><a class="btn btn-info btn-amr" href="./survey.html">Take me to the 5-min survey!</a></p>
-</blockquote>
+<p><em>Note: the rules of ‘EUCAST Clinical Breakpoints v11.0 (2021)’ are now implemented.</em></p>
 <div id="what-is-amr-for-r" class="section level3">
 <h3 class="hasAnchor">
 <a href="#what-is-amr-for-r" class="anchor"></a>What is <code>AMR</code> (for R)?</h3>
 <p><em>(To find out how to conduct AMR data analysis, please <a href="./articles/AMR.html">continue reading here to get started</a>.)</em></p>
-<p><code>AMR</code> is a free, open-source and independent <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
+<p><code>AMR</code> is a free, open-source and independent <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
 <p>After installing this package, R knows <a href="./reference/microorganisms.html"><strong>~70,000 distinct microbial species</strong></a> and all <a href="./reference/antibiotics.html"><strong>~550 antibiotic, antimycotic and antiviral drugs</strong></a> by name and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
 <p>This package is <a href="https://en.wikipedia.org/wiki/Dependency_hell">fully independent of any other R package</a> and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl">University Medical Center Groningen</a>. This R package is <a href="./news">actively maintained</a> and is free software (see <a href="#copyright">Copyright</a>).</p>
 <div class="main-content" style="display: inline-block;">
@@ -217,8 +212,8 @@ Since you are one of our users, we would like to know how you use the package an
 <div id="with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side" class="section level5">
 <h5 class="hasAnchor">
 <a href="#with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side" class="anchor"></a>With <code>AMR</code> (for R), there’s always a knowledgeable microbiologist by your side!</h5>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># AMR works great with dplyr, but it's not required or neccesary</span>
+<div class="sourceCode" id="cb1"><pre class="downlit">
+<span class="co"># AMR works great with dplyr, but it's not required or neccesary</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
 <span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>

@@ -232,7 +227,7 @@ Since you are one of our users, we would like to know how you use the package an
 <span class="co">#&gt;       'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 (2020).</span>
 <span class="co">#&gt; Selecting aminoglycosides: columns 'AMK' (amikacin), 'GEN' (gentamicin), </span>
 <span class="co">#&gt;       'KAN' (kanamycin) and 'TOB' (tobramycin)</span>
-<span class="co">#&gt; Selecting carbapenems: columns 'IPM' (imipenem) and 'MEM' (meropenem)</span></code></pre></div>
+<span class="co">#&gt; Selecting carbapenems: columns 'IPM' (imipenem) and 'MEM' (meropenem)</span></pre></div>
 <p>With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (<code><a href="reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><a href="reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>) and a column selection on two antibiotic groups (<code><a href="reference/antibiotic_class_selectors.html">aminoglycosides()</a></code> and <code><a href="reference/antibiotic_class_selectors.html">carbapenems()</a></code>), the reference data about <a href="./reference/microorganisms.html">all microorganisms</a> and <a href="./reference/antibiotics.html">all antibiotics</a> in the <code>AMR</code> package make sure you get what you meant:</p>
 <table class="table">
 <thead><tr class="header">
@@ -338,18 +333,18 @@ Since you are one of our users, we would like to know how you use the package an
 </tbody>
 </table>
 <p>A base R equivalent would be, giving the exact same results:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">example_isolates</span><span class="op">$</span><span class="va">bacteria</span> <span class="op">&lt;-</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">mo</span><span class="op">)</span>
+<div class="sourceCode" id="cb2"><pre class="downlit">
+<span class="va">example_isolates</span><span class="op">$</span><span class="va">bacteria</span> <span class="op">&lt;-</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">mo</span><span class="op">)</span>
 <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html">which</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&amp;</span>
                         <span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span>,
-                 <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"bacteria"</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">]</span></code></pre></div>
+                 <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"bacteria"</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">]</span></pre></div>
 </div>
 <div id="partners" class="section level4">
 <h4 class="hasAnchor">
 <a href="#partners" class="anchor"></a>Partners</h4>
 <p>The development of this package is part of, related to, or made possible by:</p>
 <div align="center">
-<p><a href="https://www.rug.nl" title="University of Groningen"><img src="./logo_rug.png" class="partner_logo"></a> <a href="https://www.umcg.nl" title="University Medical Center Groningen"><img src="./logo_umcg.png" class="partner_logo"></a> <a href="https://www.certe.nl" title="Certe Medical Diagnostics and Advice Foundation"><img src="./logo_certe.png" class="partner_logo"></a> <a href="http://www.eurhealth-1health.eu" title="EurHealth-1-Health"><img src="./logo_eh1h.png" class="partner_logo"></a> <a href="https://www.deutschland-nederland.eu" title="INTERREG"><img src="./logo_interreg.png" class="partner_logo"></a></p>
+<a href="https://www.rug.nl" title="University of Groningen"><img src="./logo_rug.png" class="partner_logo"></a> <a href="https://www.umcg.nl" title="University Medical Center Groningen"><img src="./logo_umcg.png" class="partner_logo"></a> <a href="https://www.certe.nl" title="Certe Medical Diagnostics and Advice Foundation"><img src="./logo_certe.png" class="partner_logo"></a> <a href="http://www.eurhealth-1health.eu" title="EurHealth-1-Health"><img src="./logo_eh1h.png" class="partner_logo"></a> <a href="https://www.deutschland-nederland.eu" title="INTERREG"><img src="./logo_interreg.png" class="partner_logo"></a>
 </div>
 </div>
 </div>
@@ -384,8 +379,8 @@ Since you are one of our users, we would like to know how you use the package an
 <a href="#latest-released-version" class="anchor"></a>Latest released version</h4>
 <p><a href="https://cran.r-project.org/package=AMR"><img src="https://www.r-pkg.org/badges/version-ago/AMR" alt="CRAN"></a> <a href="https://cran.r-project.org/package=AMR"><img src="https://cranlogs.r-pkg.org/badges/grand-total/AMR" alt="CRANlogs"></a></p>
 <p>This package is available <a href="https://cran.r-project.org/package=AMR">here on the official R network (CRAN)</a>, which has a peer-reviewed submission process. Install this package in R from CRAN by using the command:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"AMR"</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb3"><pre class="downlit">
+<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"AMR"</span><span class="op">)</span></pre></div>
 <p>It will be downloaded and installed automatically. For RStudio, click on the menu <em>Tools</em> &gt; <em>Install Packages…</em> and then type in “AMR” and press <kbd>Install</kbd>.</p>
 <p><strong>Note:</strong> Not all functions on this website may be available in this latest release. To use all functions and data sets mentioned on this website, install the latest development version.</p>
 </div>
@@ -394,9 +389,9 @@ Since you are one of our users, we would like to know how you use the package an
 <a href="#latest-development-version" class="anchor"></a>Latest development version</h4>
 <p><img src="https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master" alt="R-code-check"><a href="https://www.codefactor.io/repository/github/msberends/amr"><img src="https://www.codefactor.io/repository/github/msberends/amr/badge" alt="CodeFactor"></a> <a href="https://codecov.io/gh/msberends/AMR?branch=master"><img src="https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg" alt="Codecov"></a></p>
 <p>The latest and unpublished development version can be installed from GitHub using:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"remotes"</span><span class="op">)</span> <span class="co"># if you haven't already</span>
-<span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html">install_github</a></span><span class="op">(</span><span class="st">"msberends/AMR"</span><span class="op">)</span></code></pre></div>
+<div class="sourceCode" id="cb4"><pre class="downlit">
+<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"remotes"</span><span class="op">)</span> <span class="co"># if you haven't already</span>
+<span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html">install_github</a></span><span class="op">(</span><span class="st">"msberends/AMR"</span><span class="op">)</span></pre></div>
 <p>You can also download the latest build from our repository: <a href="https://github.com/msberends/AMR/raw/master/data-raw/AMR_latest.tar.gz" class="uri">https://github.com/msberends/AMR/raw/master/data-raw/AMR_latest.tar.gz</a></p>
 </div>
 </div>
@@ -1,4 +1,4 @@
-pandoc: 2.11.2
+pandoc: '2.6'
 pkgdown: 1.6.1
 pkgdown_sha: ~
 articles:
@@ -12,7 +12,7 @@ articles:
  datasets: datasets.html
  resistance_predict: resistance_predict.html
  welcome_to_AMR: welcome_to_AMR.html
-last_built: 2021-03-14T08:55Z
+last_built: 2021-04-27T09:08Z
 urls:
  reference: https://msberends.github.io/AMR//reference
  article: https://msberends.github.io/AMR//articles
@@ -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">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9010</span>
      </span>
    </div>

@@ -242,7 +242,43 @@
    <p>These functions are so-called '<a href='https://rdrr.io/r/base/Deprecated.html'>Deprecated</a>'. They will be removed in a future release. Using the functions will give a warning with the name of the function it has been replaced by (if there is one).</p>
    </div>

-    <pre class="usage"><span class='fu'>p_symbol</span><span class='op'>(</span><span class='va'>p</span>, emptychar <span class='op'>=</span> <span class='st'>" "</span><span class='op'>)</span></pre>
+    <pre class="usage"><span class='fu'>p_symbol</span><span class='op'>(</span><span class='va'>p</span>, emptychar <span class='op'>=</span> <span class='st'>" "</span><span class='op'>)</span>
+
+<span class='fu'>key_antibiotics</span><span class='op'>(</span>
+  x <span class='op'>=</span> <span class='cn'>NULL</span>,
+  col_mo <span class='op'>=</span> <span class='cn'>NULL</span>,
+  universal_1 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"amoxicillin"</span><span class='op'>)</span>,
+  universal_2 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"amoxicillin/clavulanic acid"</span><span class='op'>)</span>,
+  universal_3 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"cefuroxime"</span><span class='op'>)</span>,
+  universal_4 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"piperacillin/tazobactam"</span><span class='op'>)</span>,
+  universal_5 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"ciprofloxacin"</span><span class='op'>)</span>,
+  universal_6 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"trimethoprim/sulfamethoxazole"</span><span class='op'>)</span>,
+  GramPos_1 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"vancomycin"</span><span class='op'>)</span>,
+  GramPos_2 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"teicoplanin"</span><span class='op'>)</span>,
+  GramPos_3 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"tetracycline"</span><span class='op'>)</span>,
+  GramPos_4 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"erythromycin"</span><span class='op'>)</span>,
+  GramPos_5 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"oxacillin"</span><span class='op'>)</span>,
+  GramPos_6 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"rifampin"</span><span class='op'>)</span>,
+  GramNeg_1 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"gentamicin"</span><span class='op'>)</span>,
+  GramNeg_2 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"tobramycin"</span><span class='op'>)</span>,
+  GramNeg_3 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"colistin"</span><span class='op'>)</span>,
+  GramNeg_4 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"cefotaxime"</span><span class='op'>)</span>,
+  GramNeg_5 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"ceftazidime"</span><span class='op'>)</span>,
+  GramNeg_6 <span class='op'>=</span> <span class='fu'><a href='guess_ab_col.html'>guess_ab_col</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='st'>"meropenem"</span><span class='op'>)</span>,
+  warnings <span class='op'>=</span> <span class='cn'>TRUE</span>,
+  <span class='va'>...</span>
+<span class='op'>)</span>
+
+<span class='fu'>key_antibiotics_equal</span><span class='op'>(</span>
+  <span class='va'>y</span>,
+  <span class='va'>z</span>,
+  type <span class='op'>=</span> <span class='st'>"keyantimicrobials"</span>,
+  ignore_I <span class='op'>=</span> <span class='cn'>TRUE</span>,
+  points_threshold <span class='op'>=</span> <span class='fl'>2</span>,
+  info <span class='op'>=</span> <span class='cn'>FALSE</span>,
+  na.rm <span class='op'>=</span> <span class='cn'>TRUE</span>,
+  <span class='va'>...</span>
+<span class='op'>)</span></pre>


    <h2 class="hasAnchor" id="retired-lifecycle"><a class="anchor" href="#retired-lifecycle"></a>Retired Lifecycle</h2>
@@ -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">1.5.0.9032</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -90,14 +90,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -106,77 +106,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -185,21 +185,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -208,14 +208,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -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">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -90,14 +90,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -106,77 +106,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -185,21 +185,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -208,14 +208,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -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">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -90,14 +90,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -106,77 +106,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -185,21 +185,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -208,14 +208,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -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">1.5.0.9040</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9010</span>
      </span>
    </div>

@@ -248,6 +248,7 @@
  collapse <span class='op'>=</span> <span class='cn'>NULL</span>,
  translate_ab <span class='op'>=</span> <span class='cn'>FALSE</span>,
  thorough_search <span class='op'>=</span> <span class='cn'>NULL</span>,
+  info <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span><span class='op'>(</span><span class='op'>)</span>,
  <span class='va'>...</span>
 <span class='op'>)</span></pre>

@@ -274,6 +275,10 @@
      <th>thorough_search</th>
      <td><p>logical to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to <code>TRUE</code> will take considerably more time than when using <code>FALSE</code>. At default, it will turn <code>TRUE</code> when all input elements contain a maximum of three words.</p></td>
    </tr>
+    <tr>
+      <th>info</th>
+      <td><p>logical to indicate whether a progress bar should be printed, defaults to <code>TRUE</code> only in interactive mode</p></td>
+    </tr>
    <tr>
      <th>...</th>
      <td><p>arguments passed on to <code><a href='as.ab.html'>as.ab()</a></code></p></td>
@@ -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">1.5.0.9019</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -90,14 +90,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -106,77 +106,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -185,21 +185,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -208,14 +208,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -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">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -90,14 +90,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -106,77 +106,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -185,21 +185,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -208,14 +208,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -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">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -90,14 +90,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -106,77 +106,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -185,21 +185,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -208,14 +208,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -83,7 +83,7 @@
      </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">1.6.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -91,14 +91,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -107,77 +107,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -186,21 +186,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -209,14 +209,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -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">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -90,14 +90,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -106,77 +106,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -185,21 +185,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -208,14 +208,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
@@ -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">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9010</span>
      </span>
    </div>

@@ -242,7 +242,7 @@
    <p>Use this function to determine the antibiotic code of one or more antibiotics. The data set <a href='antibiotics.html'>antibiotics</a> will be searched for abbreviations, official names and synonyms (brand names).</p>
    </div>

-    <pre class="usage"><span class='fu'>as.ab</span><span class='op'>(</span><span class='va'>x</span>, flag_multiple_results <span class='op'>=</span> <span class='cn'>TRUE</span>, info <span class='op'>=</span> <span class='cn'>TRUE</span>, <span class='va'>...</span><span class='op'>)</span>
+    <pre class="usage"><span class='fu'>as.ab</span><span class='op'>(</span><span class='va'>x</span>, flag_multiple_results <span class='op'>=</span> <span class='cn'>TRUE</span>, info <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>

 <span class='fu'>is.ab</span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span></pre>

@@ -259,7 +259,7 @@
    </tr>
    <tr>
      <th>info</th>
-      <td><p>logical to indicate whether a progress bar should be printed</p></td>
+      <td><p>a <a href='https://rdrr.io/r/base/logical.html'>logical</a> to indicate whether a progress bar should be printed, defaults to <code>TRUE</code> only in interactive mode</p></td>
    </tr>
    <tr>
      <th>...</th>
@@ -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">1.5.0.9016</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
      </span>
    </div>

@@ -90,14 +90,14 @@
      <ul class="nav navbar-nav">
        <li>
  <a href="../index.html">
-    <span class="fas fa-home"></span>
+    <span class="fa fa-home"></span>
     
    Home
  </a>
 </li>
 <li class="dropdown">
  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    <span class="fas fa-question-circle"></span>
+    <span class="fa fa-question-circle"></span>
     
    How to
     
@@ -106,77 +106,77 @@
  <ul class="dropdown-menu" role="menu">
    <li>
      <a href="../articles/AMR.html">
-        <span class="fas fa-directions"></span>
+        <span class="fa fa-directions"></span>
         
        Conduct AMR analysis
      </a>
    </li>
    <li>
      <a href="../articles/resistance_predict.html">
-        <span class="fas fa-dice"></span>
+        <span class="fa fa-dice"></span>
         
        Predict antimicrobial resistance
      </a>
    </li>
    <li>
      <a href="../articles/datasets.html">
-        <span class="fas fa-database"></span>
+        <span class="fa fa-database"></span>
         
        Data sets for download / own use
      </a>
    </li>
    <li>
      <a href="../articles/PCA.html">
-        <span class="fas fa-compress"></span>
+        <span class="fa fa-compress"></span>
         
        Conduct principal component analysis for AMR
      </a>
    </li>
    <li>
      <a href="../articles/MDR.html">
-        <span class="fas fa-skull-crossbones"></span>
+        <span class="fa fa-skull-crossbones"></span>
         
        Determine multi-drug resistance (MDR)
      </a>
    </li>
    <li>
      <a href="../articles/WHONET.html">
-        <span class="fas fa-globe-americas"></span>
+        <span class="fa fa-globe-americas"></span>
         
        Work with WHONET data
      </a>
    </li>
    <li>
      <a href="../articles/SPSS.html">
-        <span class="fas fa-file-upload"></span>
+        <span class="fa fa-file-upload"></span>
         
        Import data from SPSS/SAS/Stata
      </a>
    </li>
    <li>
      <a href="../articles/EUCAST.html">
-        <span class="fas fa-exchange-alt"></span>
+        <span class="fa fa-exchange-alt"></span>
         
        Apply EUCAST rules
      </a>
    </li>
    <li>
      <a href="../reference/mo_property.html">
-        <span class="fas fa-bug"></span>
+        <span class="fa fa-bug"></span>
         
        Get properties of a microorganism
      </a>
    </li>
    <li>
      <a href="../reference/ab_property.html">
-        <span class="fas fa-capsules"></span>
+        <span class="fa fa-capsules"></span>
         
        Get properties of an antibiotic
      </a>
    </li>
    <li>
      <a href="../articles/benchmarks.html">
-        <span class="fas fa-shipping-fast"></span>
+        <span class="fa fa-shipping-fast"></span>
         
        Other: benchmarks
      </a>
@@ -185,21 +185,21 @@
 </li>
 <li>
  <a href="../reference/index.html">
-    <span class="fas fa-book-open"></span>
+    <span class="fa fa-book-open"></span>
     
    Manual
  </a>
 </li>
 <li>
  <a href="../authors.html">
-    <span class="fas fa-users"></span>
+    <span class="fa fa-users"></span>
     
    Authors
  </a>
 </li>
 <li>
  <a href="../news/index.html">
-    <span class="far fa-newspaper"></span>
+    <span class="far fa far fa-newspaper"></span>
     
    Changelog
  </a>
@@ -208,14 +208,14 @@
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="https://github.com/msberends/AMR">
-    <span class="fab fa-github"></span>
+    <span class="fab fa fab fa-github"></span>
     
    Source Code
  </a>
 </li>
 <li>
  <a href="../survey.html">
-    <span class="fas fa-clipboard-list"></span>
+    <span class="fa fa-clipboard-list"></span>
     
    Survey
  </a>
Author	SHA1	Message	Date
dr. M.S. (Matthijs) Berends	5e06b20d43	(v1.6.0.9012) unit tests	2021-04-27 11:28:17 +02:00
dr. M.S. (Matthijs) Berends	c5fff1c95c	(v1.6.0.9011) unit tests	2021-04-27 10:27:13 +02:00
dr. M.S. (Matthijs) Berends	93683a4ae2	(v1.6.0.9010) big first_isolate() update	2021-04-26 23:57:37 +02:00
dr. M.S. (Matthijs) Berends	5f9e7bd3ee	(v1.6.0.9009) key_antibiotics update	2021-04-23 16:13:26 +02:00
dr. M.S. (Matthijs) Berends	70b803dbb6	(v1.6.0.9008) unlike, bugfix for col_mo naming	2021-04-23 09:59:36 +02:00
dr. M.S. (Matthijs) Berends	c6289c3fc3	(v1.6.0.9007) documentation custom eucast rules, progress bar as.mo	2021-04-20 10:46:17 +02:00
dr. M.S. (Matthijs) Berends	de66eccf43	(v1.6.0.9006) eucast rules fix for Ochrobactrum anthropi	2021-04-16 14:59:57 +02:00
dr. M.S. (Matthijs) Berends	24ac18a99d	(v1.6.0.9005) unit test fix	2021-04-16 13:24:59 +02:00
dr. M.S. (Matthijs) Berends	9842ef9660	(v1.6.0.9004) unit test fix	2021-04-16 12:02:57 +02:00
dr. M.S. (Matthijs) Berends	00d3e437a8	(v1.6.0.9003) like() fix	2021-04-16 11:41:05 +02:00
dr. M.S. (Matthijs) Berends	d277d58475	(v1.6.0.9002) R-3.0 installation fix	2021-04-12 14:24:40 +02:00
dr. M.S. (Matthijs) Berends	6ff5448192	(v1.6.0.9001) support Inf for episodes	2021-04-12 12:35:13 +02:00
dr. M.S. (Matthijs) Berends	7a3139f7cc	(v1.6.0.9000) custom EUCAST rules	2021-04-07 08:37:42 +02:00