From 760d69a3e063e3567447e01f33a9bb0210ef60f9 Mon Sep 17 00:00:00 2001
From: "Matthijs S. Berends" <berendsms@gmail.com>
Date: Mon, 26 Oct 2020 12:23:03 +0100
Subject: [PATCH] (v1.4.0.9008) like variations

---
 DESCRIPTION                                   |   4 +-
 NAMESPACE                                     |   2 +
 NEWS.md                                       |   8 +-
 R/aa_helper_functions.R                       | 171 ++++++---
 R/like.R                                      |  13 +-
 R/mo.R                                        | 349 +++++++++---------
 R/mo_property.R                               | 118 +++---
 docs/404.html                                 |   2 +-
 docs/LICENSE-text.html                        |   2 +-
 docs/articles/PCA.html                        |  54 ++-
 .../anchor-sections-1.0/anchor-sections.css   |   4 +
 .../anchor-sections-1.0/anchor-sections.js    |  33 ++
 .../figure-html/unnamed-chunk-5-1.png         | Bin 88331 -> 47914 bytes
 .../figure-html/unnamed-chunk-6-1.png         | Bin 146668 -> 91805 bytes
 .../figure-html/unnamed-chunk-7-1.png         | Bin 151865 -> 92338 bytes
 docs/articles/SPSS.html                       |  80 ++--
 .../anchor-sections-1.0/anchor-sections.css   |   4 +
 .../anchor-sections-1.0/anchor-sections.js    |  33 ++
 docs/articles/WHONET.html                     |  47 ++-
 .../anchor-sections-1.0/anchor-sections.css   |   4 +
 .../anchor-sections-1.0/anchor-sections.js    |  33 ++
 .../figure-html/unnamed-chunk-7-1.png         | Bin 95752 -> 61471 bytes
 docs/articles/benchmarks.html                 |  95 +++--
 .../anchor-sections-1.0/anchor-sections.css   |   4 +
 .../anchor-sections-1.0/anchor-sections.js    |  33 ++
 .../figure-html/unnamed-chunk-4-1.png         | Bin 70223 -> 71518 bytes
 docs/articles/index.html                      |   2 +-
 docs/articles/resistance_predict.html         |  61 ++-
 .../anchor-sections-1.0/anchor-sections.css   |   4 +
 .../anchor-sections-1.0/anchor-sections.js    |  33 ++
 .../figure-html/unnamed-chunk-4-1.png         | Bin 98817 -> 49261 bytes
 .../figure-html/unnamed-chunk-5-1.png         | Bin 95884 -> 71626 bytes
 .../figure-html/unnamed-chunk-5-2.png         | Bin 94467 -> 70493 bytes
 .../figure-html/unnamed-chunk-6-1.png         | Bin 96773 -> 73734 bytes
 .../figure-html/unnamed-chunk-7-1.png         | Bin 89941 -> 66876 bytes
 docs/articles/welcome_to_AMR.html             |   7 +-
 .../anchor-sections-1.0/anchor-sections.css   |   4 +
 .../anchor-sections-1.0/anchor-sections.js    |  33 ++
 docs/authors.html                             |   2 +-
 docs/index.html                               |   2 +-
 docs/news/index.html                          |  56 +--
 docs/pkgdown.yml                              |   4 +-
 docs/reference/AMR-deprecated.html            |   2 +-
 docs/reference/age.html                       |   2 +-
 docs/reference/age_groups.html                |   2 +-
 .../reference/antibiotic_class_selectors.html |   2 +-
 docs/reference/as.mo.html                     |   2 +-
 docs/reference/as.rsi.html                    |   2 +-
 docs/reference/bug_drug_combinations.html     |   2 +-
 docs/reference/filter_ab_class.html           |  68 ++--
 docs/reference/ggplot_pca.html                |   2 +-
 docs/reference/ggplot_rsi.html                |   2 +-
 docs/reference/guess_ab_col.html              |   2 +-
 docs/reference/index.html                     |   6 +-
 docs/reference/key_antibiotics.html           |   2 +-
 docs/reference/lifecycle.html                 |   4 +-
 docs/reference/like.html                      |  17 +-
 docs/reference/mo_property.html               |   8 +-
 docs/reference/pca.html                       |  46 +--
 docs/survey.html                              |   2 +-
 inst/rstudio/addins.dcf                       |   2 +-
 man/like.Rd                                   |  12 +-
 man/mo_property.Rd                            |   6 +-
 tests/testthat/test-like.R                    |   7 +-
 64 files changed, 919 insertions(+), 582 deletions(-)
 create mode 100644 docs/articles/PCA_files/anchor-sections-1.0/anchor-sections.css
 create mode 100644 docs/articles/PCA_files/anchor-sections-1.0/anchor-sections.js
 create mode 100644 docs/articles/SPSS_files/anchor-sections-1.0/anchor-sections.css
 create mode 100644 docs/articles/SPSS_files/anchor-sections-1.0/anchor-sections.js
 create mode 100644 docs/articles/WHONET_files/anchor-sections-1.0/anchor-sections.css
 create mode 100644 docs/articles/WHONET_files/anchor-sections-1.0/anchor-sections.js
 create mode 100644 docs/articles/benchmarks_files/anchor-sections-1.0/anchor-sections.css
 create mode 100644 docs/articles/benchmarks_files/anchor-sections-1.0/anchor-sections.js
 create mode 100644 docs/articles/resistance_predict_files/anchor-sections-1.0/anchor-sections.css
 create mode 100644 docs/articles/resistance_predict_files/anchor-sections-1.0/anchor-sections.js
 create mode 100644 docs/articles/welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.css
 create mode 100644 docs/articles/welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.js

diff --git a/DESCRIPTION b/DESCRIPTION
index e54f581e..31916785 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: AMR
-Version: 1.4.0.9007
-Date: 2020-10-21
+Version: 1.4.0.9008
+Date: 2020-10-26
 Title: Antimicrobial Resistance Analysis
 Authors@R: c(
     person(role = c("aut", "cre"), 
diff --git a/NAMESPACE b/NAMESPACE
index 0eadd0cb..4660150e 100755
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -65,6 +65,8 @@ S3method(unique,mo)
 S3method(unique,rsi)
 export("%like%")
 export("%like_case%")
+export("%not_like%")
+export("%not_like_case%")
 export(ab_atc)
 export(ab_atc_group1)
 export(ab_atc_group2)
diff --git a/NEWS.md b/NEWS.md
index f9123a95..6470ba87 100755
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,17 +1,19 @@
-# AMR 1.4.0.9007
-## <small>Last updated: 21 October 2020</small>
+# AMR 1.4.0.9008
+## <small>Last updated: 26 October 2020</small>
 
 ### New
 * Functions `is_gram_negative()` and `is_gram_positive()` as wrappers around `mo_gramstain()`. They always return `TRUE` or `FALSE`, thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
-* Functions `%not_like%` and `%like_perl%` as wrappers around `%like%`.
+* Functions `%not_like%` and `%not_like_case%` as wrappers around `%like%` and `%like_case%`. The RStudio addin to insert the text " %like% " as provided in this package now iterates over all like variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert ` %like% ` and by pressing it again it will be replaced with ` %not_like% `, etc.
 
 ### Changed
 * For all function parameters in the code, it is now defined what the exact type of user input should be (inspired by the [`typed`](https://github.com/moodymudskipper/typed) package). If the user input for a certain function does not meet the requirements for a specific parameter (such as the class or length), an informative error will be thrown. This makes the package more robust and the use of it more reproducible and reliable. In total, more than 400 arguments were defined.
 * Deprecated function `p_symbol()` that not really fits the scope of this package. It will be removed in a future version. See [here](https://github.com/msberends/AMR/blob/v1.4.0/R/p_symbol.R) for the source code to preserve it.
 * Better determination of disk zones and MIC values when running `as.rsi()` on a data.frame
 * Updated coagulase-negative staphylococci with Becker *et al.* 2020 (PMID 32056452), meaning that the species *S. argensis*, *S. caeli*, *S. debuckii*, *S. edaphicus* and *S. pseudoxylosus* are now all considered CoNS
+* Fix for using parameter `reference_df` in `as.mo()` and `mo_*()` functions that contain old microbial codes (from previous package versions)
 
 ### Other
+* All messages thrown by this package now have correct line breaks
 * More extensive unit tests
 
 # AMR 1.4.0
diff --git a/R/aa_helper_functions.R b/R/aa_helper_functions.R
index 448da7a2..20044608 100755
--- a/R/aa_helper_functions.R
+++ b/R/aa_helper_functions.R
@@ -9,7 +9,7 @@
 # (c) 2018-2020 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.       # 
+# 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  #
@@ -37,18 +37,18 @@ pm_left_join <- function(x, y, by = NULL, suffix = c(".x", ".y")) {
   if (length(by) == 1) {
     by <- rep(by, 2)
   }
-  
+
   int_x <- colnames(x) %in% colnames(y) & colnames(x) != by[1]
   int_y <- colnames(y) %in% colnames(x) & colnames(y) != by[2]
   colnames(x)[int_x] <- paste0(colnames(x)[int_x], suffix[1L])
   colnames(y)[int_y] <- paste0(colnames(y)[int_y], suffix[2L])
-  
+
   merged <- cbind(x,
                   y[match(x[, by[1], drop = TRUE],
                           y[, by[2], drop = TRUE]),
                     colnames(y)[!colnames(y) %in% colnames(x) & !colnames(y) == by[2]],
                     drop = FALSE])
-  
+
   rownames(merged) <- NULL
   merged
 }
@@ -71,7 +71,42 @@ addin_insert_in <- function() {
 
 # No export, no Rd
 addin_insert_like <- function() {
-  import_fn("insertText", "rstudioapi")(" %like% ")
+  stop_ifnot_installed("rstudioapi")
+  # we want Ctrl/Cmd + L to iterate over %like%, %not_like% and %like_case%, so determine context first
+  
+  getSourceEditorContext <- import_fn("getSourceEditorContext", "rstudioapi")
+  insertText <- import_fn("insertText", "rstudioapi")
+  modifyRange <- import_fn("insertText", "rstudioapi")
+  document_range <- import_fn("document_range", "rstudioapi")
+  document_position <- import_fn("document_position", "rstudioapi")
+  # setSelectionRanges <- import_fn("setSelectionRanges", "rstudioapi")
+  
+  context <- getSourceEditorContext()
+  current_row <- context$selection[[1]]$range$end[1]
+  current_col <- context$selection[[1]]$range$end[2]
+  current_row_txt <- context$contents[current_row]
+  
+  pos_preceded_by <- function(txt) {
+    substr(current_row_txt, current_col - nchar(txt), current_col) == txt
+  }
+  replace_pos <- function(old, with) {
+    modifyRange(document_range(document_position(current_row, current_col - nchar(old)),
+                               document_position(current_row, current_col)),
+                text = with,
+                id = context$id)
+  }
+  
+  if (pos_preceded_by(" %like% ")) {
+    replace_pos(" %like% ", with = " %not_like% ")
+  } else if (pos_preceded_by(" %not_like% ")) {
+    replace_pos(" %not_like% ", with = " %like_case% ")
+  } else if (pos_preceded_by(" %like_case% ")) {
+    replace_pos(" %like_case% ", with = " %not_like_case% ")
+  } else if (pos_preceded_by(" %not_like_case% ")) {
+    replace_pos(" %not_like_case% ", with = " %like% ")
+  } else {
+    insertText(" %like% ")
+  }
 }
 
 check_dataset_integrity <- function() {
@@ -88,13 +123,13 @@ check_dataset_integrity <- function() {
   # check if other packages did not overwrite our data sets
   tryCatch({
     check_microorganisms <- all(c("mo", "fullname", "kingdom", "phylum",
-                                  "class", "order", "family", "genus", 
+                                  "class", "order", "family", "genus",
                                   "species", "subspecies", "rank",
                                   "species_id", "source", "ref", "prevalence") %in% colnames(microorganisms),
                                 na.rm = TRUE)
-    check_antibiotics <- all(c("ab", "atc", "cid", "name", "group", 
+    check_antibiotics <- all(c("ab", "atc", "cid", "name", "group",
                                "atc_group1", "atc_group2", "abbreviations",
-                               "synonyms", "oral_ddd", "oral_units", 
+                               "synonyms", "oral_ddd", "oral_units",
                                "iv_ddd", "iv_units", "loinc") %in% colnames(antibiotics),
                              na.rm = TRUE)
   }, error = function(e) {
@@ -107,10 +142,10 @@ check_dataset_integrity <- function() {
 search_type_in_df <- function(x, type, info = TRUE) {
   # try to find columns based on type
   found <- NULL
-  
+
   x <- as.data.frame(x, stringsAsFactors = FALSE)
   colnames(x) <- trimws(colnames(x))
-  
+
   # -- mo
   if (type == "mo") {
     if (any(sapply(x, is.mo))) {
@@ -128,7 +163,7 @@ search_type_in_df <- function(x, type, info = TRUE) {
     } else if (any(colnames(x) %like% "species")) {
       found <- sort(colnames(x)[colnames(x) %like% "species"])[1]
     }
-    
+
   }
   # -- key antibiotics
   if (type == "keyantibiotics") {
@@ -180,7 +215,7 @@ search_type_in_df <- function(x, type, info = TRUE) {
       }
     }
   }
-  
+
   if (!is.null(found) & info == TRUE) {
     msg <- paste0("NOTE: Using column `", font_bold(found), "` as input for `col_", type, "`.")
     if (type %in% c("keyantibiotics", "specimen")) {
@@ -222,8 +257,8 @@ import_fn <- function(name, pkg, error_on_fail = TRUE) {
     get(name, envir = asNamespace(pkg)),
     error = function(e) {
       if (isTRUE(error_on_fail)) {
-        stop_("function ", name, "() not found in package '", pkg, 
-              "'. Please create an issue at https://github.com/msberends/AMR/issues. Many thanks!", 
+        stop_("function ", name, "() not found in package '", pkg,
+              "'. Please create an issue at https://github.com/msberends/AMR/issues. Many thanks!",
               call = FALSE)
       } else {
         return(NULL)
@@ -231,6 +266,52 @@ import_fn <- function(name, pkg, error_on_fail = TRUE) {
     })
 }
 
+# this alternative to the message() function:
+# - wraps text to never break lines within words
+# - ignores formatted text while wrapping
+# - adds indentation dependent on the type of message (like NOTE)
+# - add additional formatting functions like blue or bold text
+message_ <- function(..., appendLF = TRUE, add_fn = list(font_blue)) {
+  msg <- paste0(c(...), collapse = "")
+
+  # we need to correct for already applied style, that adds text like "\033[31m\"
+  msg_stripped <- font_stripstyle(msg)
+  # where are the spaces now?
+  msg_stripped_wrapped <- paste0(strwrap(msg_stripped,
+                                         simplify = TRUE,
+                                         width = 0.95 * getOption("width")),
+                                 collapse = "\n")
+  msg_stripped_spaces <- which(unlist(strsplit(msg_stripped, "")) == " ")
+  msg_stripped_wrapped_spaces <- which(unlist(strsplit(msg_stripped_wrapped, "")) == " ")
+  # so these are the indices of spaces that need to be replaced
+  replace_spaces <- which(!msg_stripped_spaces %in% msg_stripped_wrapped_spaces)
+  # put it together
+  msg <- unlist(strsplit(msg, " "))
+  msg[replace_spaces] <- paste0(msg[replace_spaces], "\n")
+  msg <- paste0(msg, collapse = " ")
+  msg <- gsub("\n ", "\n", msg, fixed = TRUE)
+
+  if (msg_stripped %like% "^NOTE: ") {
+    indentation <- 6
+  } else {
+    indentation <- 0
+  }
+  msg <- gsub("\n", paste0("\n", strrep(" ", indentation)), msg, fixed = TRUE)
+
+  if (length(add_fn) > 0) {
+    if (!is.list(add_fn)) {
+      add_fn <- list(add_fn)
+    }
+    for (i in seq_len(length(add_fn))) {
+      msg <- add_fn[[i]](msg)
+    }
+  }
+  message(msg, appendLF = appendLF)
+}
+
+# this alternative to the stop() function:
+# - adds the function name where the error was thrown
+# - wraps text to never break lines within words
 stop_ <- function(..., call = TRUE) {
   msg <- paste0(c(...), collapse = "")
   if (!isFALSE(call)) {
@@ -340,10 +421,10 @@ meet_criteria <- function(object,
                           allow_NA = FALSE,
                           ignore.case = FALSE,
                           .call_depth = 0) { # depth in calling
-  
+
   obj_name <- deparse(substitute(object))
   call_depth <- -2 - abs(.call_depth)
-  
+
   if (is.null(object)) {
     stop_if(allow_NULL == FALSE, "argument `", obj_name, "` must not be NULL", call = call_depth)
     return(invisible())
@@ -352,7 +433,7 @@ meet_criteria <- function(object,
     stop_if(allow_NA == FALSE, "argument `", obj_name, "` must not be NA", call = call_depth)
     return(invisible())
   }
-  
+
   vector_or <- function(v, quotes) {
     if (length(v) == 1) {
       return(paste0(ifelse(quotes, '"', ""), v, ifelse(quotes, '"', "")))
@@ -361,32 +442,32 @@ meet_criteria <- function(object,
     paste0(paste0(ifelse(quotes, '"', ""), v[seq_len(length(v) - 1)], ifelse(quotes, '"', ""), collapse = ", "),
            " or ", paste0(ifelse(quotes, '"', ""), v[length(v)], ifelse(quotes, '"', "")))
   }
-  
+
   if (!is.null(allow_class)) {
-    stop_ifnot(inherits(object, allow_class), "argument `", obj_name, 
-               "` must ", # ifelse(allow_NULL, "be NULL or must ", ""), 
-               "be of class ", vector_or(allow_class, quotes = TRUE), 
+    stop_ifnot(inherits(object, allow_class), "argument `", obj_name,
+               "` must ", # ifelse(allow_NULL, "be NULL or must ", ""),
+               "be of class ", vector_or(allow_class, quotes = TRUE),
                ", not \"", paste(class(object), collapse = "/"), "\"",
                call = call_depth)
     # check data.frames for data
     if (inherits(object, "data.frame")) {
-      stop_if(any(dim(object) == 0), 
+      stop_if(any(dim(object) == 0),
               "the data provided in argument `", obj_name,
-              "` must contain rows and columns (current dimensions: ", 
+              "` must contain rows and columns (current dimensions: ",
               paste(dim(object), collapse = " x "), ")",
               call = call_depth)
     }
   }
   if (!is.null(has_length)) {
-    stop_ifnot(length(object) %in% has_length, "argument `", obj_name, 
-               "` must ", # ifelse(allow_NULL, "be NULL or must ", ""), 
+    stop_ifnot(length(object) %in% has_length, "argument `", obj_name,
+               "` must ", # ifelse(allow_NULL, "be NULL or must ", ""),
                "be of length ", vector_or(has_length, quotes = FALSE),
                ", not ", length(object),
                call = call_depth)
   }
   if (!is.null(looks_like)) {
-    stop_ifnot(object %like% looks_like, "argument `", obj_name, 
-               "` must ", # ifelse(allow_NULL, "be NULL or must ", ""), 
+    stop_ifnot(object %like% looks_like, "argument `", obj_name,
+               "` must ", # ifelse(allow_NULL, "be NULL or must ", ""),
                "resemble the regular expression \"", looks_like, "\"",
                call = call_depth)
   }
@@ -395,16 +476,16 @@ meet_criteria <- function(object,
       object <- tolower(object)
       is_in <- tolower(is_in)
     }
-    stop_ifnot(all(object %in% is_in, na.rm = TRUE), "argument `", obj_name, 
+    stop_ifnot(all(object %in% is_in, na.rm = TRUE), "argument `", obj_name,
                "` must be ",
                ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1, "one of: ", ""),
-               vector_or(is_in, quotes = TRUE), 
+               vector_or(is_in, quotes = TRUE),
                ", not ", paste0("\"", object, "\"", collapse = "/"), "",
                call = call_depth)
   }
   if (!is.null(contains_column_class)) {
     stop_ifnot(any(sapply(object, function(col, columns_class = contains_column_class) inherits(col, columns_class)), na.rm = TRUE),
-               "the data provided in argument `", obj_name, 
+               "the data provided in argument `", obj_name,
                "` must contain at least one column of class <", contains_column_class, ">. ",
                "See ?as.", contains_column_class, ".",
                call = call_depth)
@@ -463,7 +544,7 @@ has_colour <- function() {
   if (Sys.getenv("TERM") == "dumb") {
     return(FALSE)
   }
-  grepl(pattern = "^screen|^xterm|^vt100|color|ansi|cygwin|linux", 
+  grepl(pattern = "^screen|^xterm|^vt100|color|ansi|cygwin|linux",
         x = Sys.getenv("TERM"),
         ignore.case = TRUE,
         perl = TRUE)
@@ -560,7 +641,7 @@ progress_ticker <- function(n = 1, n_min = 0, ...) {
 create_pillar_column <- function(x, ...) {
   new_pillar_shaft_simple <- import_fn("new_pillar_shaft_simple", "pillar", error_on_fail = FALSE)
   if (!is.null(new_pillar_shaft_simple)) {
-    new_pillar_shaft_simple(x, ...)  
+    new_pillar_shaft_simple(x, ...)
   } else {
     # does not exist in package 'pillar' anymore
     structure(list(x),
@@ -622,12 +703,12 @@ round2 <- function(x, digits = 0, force_zero = TRUE) {
   if (digits > 0 & force_zero == TRUE) {
     values_trans <- val[val != as.integer(val) & !is.na(val)]
     val[val != as.integer(val) & !is.na(val)] <- paste0(values_trans,
-                                                        strrep("0", 
-                                                               max(0, 
+                                                        strrep("0",
+                                                               max(0,
                                                                    digits - nchar(
                                                                      format(
                                                                        as.double(
-                                                                         gsub(".*[.](.*)$", 
+                                                                         gsub(".*[.](.*)$",
                                                                               "\\1",
                                                                               values_trans)),
                                                                        scientific = FALSE)))))
@@ -638,7 +719,7 @@ round2 <- function(x, digits = 0, force_zero = TRUE) {
 
 # percentage from our other package: 'cleaner'
 percentage <- function(x, digits = NULL, ...) {
-  
+
   # getdecimalplaces() function
   getdecimalplaces <- function(x, minimum = 0, maximum = 3) {
     if (maximum < minimum) {
@@ -647,20 +728,20 @@ percentage <- function(x, digits = NULL, ...) {
     if (minimum > maximum) {
       minimum <- maximum
     }
-    max_places <- max(unlist(lapply(strsplit(sub("0+$", "", 
+    max_places <- max(unlist(lapply(strsplit(sub("0+$", "",
                                                  as.character(x * 100)), ".", fixed = TRUE),
                                     function(y) ifelse(length(y) == 2, nchar(y[2]), 0))), na.rm = TRUE)
     max(min(max_places,
             maximum, na.rm = TRUE),
         minimum, na.rm = TRUE)
   }
-  
+
   # format_percentage() function
   format_percentage <- function(x, digits = NULL, ...) {
     if (is.null(digits)) {
       digits <- getdecimalplaces(x)
     }
-    
+
     # round right: percentage(0.4455) and format(as.percentage(0.4455), 1) should return "44.6%", not "44.5%"
     x_formatted <- format(round2(as.double(x), digits = digits + 2) * 100,
                           scientific = FALSE,
@@ -671,7 +752,7 @@ percentage <- function(x, digits = NULL, ...) {
     x_formatted[!grepl(pattern = "^[0-9.,e-]+$", x = x)] <- NA_character_
     x_formatted
   }
-  
+
   # the actual working part
   x <- as.double(x)
   if (is.null(digits)) {
@@ -688,12 +769,12 @@ percentage <- function(x, digits = NULL, ...) {
 # see here for the full list: https://github.com/r-lib/backports
 strrep <- function(x, times) {
   x <- as.character(x)
-  if (length(x) == 0L) 
+  if (length(x) == 0L)
     return(x)
   unlist(.mapply(function(x, times) {
-    if (is.na(x) || is.na(times)) 
+    if (is.na(x) || is.na(times))
       return(NA_character_)
-    if (times <= 0L) 
+    if (times <= 0L)
       return("")
     paste0(replicate(times, x), collapse = "")
   }, list(x = x, times = times), MoreArgs = list()), use.names = FALSE)
@@ -701,9 +782,9 @@ strrep <- function(x, times) {
 trimws <- function(x, which = c("both", "left", "right")) {
   which <- match.arg(which)
   mysub <- function(re, x) sub(re, "", x, perl = TRUE)
-  if (which == "left") 
+  if (which == "left")
     return(mysub("^[ \t\r\n]+", x))
-  if (which == "right") 
+  if (which == "right")
     return(mysub("[ \t\r\n]+$", x))
   mysub("[ \t\r\n]+$", mysub("^[ \t\r\n]+", x))
 }
diff --git a/R/like.R b/R/like.R
index d132341e..3d1c8b8b 100755
--- a/R/like.R
+++ b/R/like.R
@@ -23,7 +23,7 @@
 # how to conduct AMR analysis: https://msberends.github.io/AMR/        #
 # ==================================================================== #
 
-#' Pattern Matching
+#' Pattern matching with keyboard shortcut
 #'
 #' Convenient wrapper around [grep()] 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
@@ -41,9 +41,9 @@
 #' * Checks if `pattern` is a regular expression and sets `fixed = TRUE` if not, to greatly improve speed
 #' * Tries again with `perl = TRUE` if regex fails
 #' 
-#' Using RStudio? This function can also be inserted from the Addins menu and can have its own Keyboard Shortcut like `Ctrl+Shift+L` or `Cmd+Shift+L` (see `Tools` > `Modify Keyboard Shortcuts...`).
+#' Using RStudio? This function can also be 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...`). This addin iterates over all 'like' variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert ` %like% ` and by pressing it again it will be replaced with ` %not_like% `, then ` %like_case% `, then ` %not_like_case% ` and then back to ` %like% `.
 #' 
-#' The `"%not_like%"` and `"%like_perl%"` functions are wrappers around `"%like%"`.
+#' The `"%not_like%"` and `"%not_like_case%"` functions are wrappers around `"%like%"` and `"%like_case%"`.
 #' @source Idea from the [`like` function from the `data.table` package](https://github.com/Rdatatable/data.table/blob/master/R/like.R)
 #' @seealso [grep()]
 #' @inheritSection AMR Read more on our website!
@@ -168,8 +168,15 @@ like <- function(x, pattern, ignore.case = TRUE) {
   like(x, pattern, ignore.case = FALSE)
 }
 
+
 #' @rdname like
 #' @export
+"%not_like_case%" <- function(x, pattern) {
+  meet_criteria(x, allow_NA = TRUE)
+  meet_criteria(pattern, allow_NA = FALSE)
+  !like(x, pattern, ignore.case = FALSE)
+}
+
 "%like_perl%" <- function(x, pattern) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(pattern, allow_NA = FALSE)
diff --git a/R/mo.R b/R/mo.R
index af8d1b29..daeb411e 100755
--- a/R/mo.R
+++ b/R/mo.R
@@ -9,7 +9,7 @@
 # (c) 2018-2020 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.       # 
+# 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  #
@@ -44,7 +44,7 @@
 #' @keywords mo Becker becker Lancefield lancefield guess
 #' @details
 #' ## General info
-#' 
+#'
 #' A microorganism ID from this package (class: [`mo`]) is human readable and typically looks like these examples:
 #' ```
 #'   Code               Full name
@@ -68,35 +68,35 @@
 #' The algorithm uses data from the Catalogue of Life (see below) and from one other source (see [microorganisms]).
 #'
 #' The [as.mo()] function uses several coercion rules for fast and logical results. It assesses the input matching criteria in the following order:
-#' 
+#'
 #' 1. Human pathogenic prevalence: the function  starts with more prevalent microorganisms, followed by less prevalent ones;
 #' 2. Taxonomic kingdom: the function starts with determining Bacteria, then Fungi, then Protozoa, then others;
 #' 3. Breakdown of input values to identify possible matches.
 #'
 #' This will lead to the effect that e.g. `"E. coli"` (a microorganism highly prevalent in humans) will return the microbial ID of *Escherichia coli* and not *Entamoeba coli* (a microorganism less prevalent in humans), although the latter would alphabetically come first.
-#' 
+#'
 #' ## Coping with uncertain results
-#' 
-#' In addition, the [as.mo()] function can differentiate four levels of uncertainty to guess valid results: 
+#'
+#' In addition, the [as.mo()] function can differentiate four levels of uncertainty to guess valid results:
 #' - Uncertainty level 0: no additional rules are applied;
 #' - Uncertainty level 1: allow previously accepted (but now invalid) taxonomic names and minor spelling errors;
 #' - Uncertainty level 2: allow all of level 1, strip values between brackets, inverse the words of the input, strip off text elements from the end keeping at least two elements;
 #' - Uncertainty level 3: allow all of level 1 and 2, strip off text elements from the end, allow any part of a taxonomic name.
-#' 
+#'
 #' The level of uncertainty can be set using the argument `allow_uncertain`. The default is `allow_uncertain = TRUE`, which is equal to uncertainty level 2. Using `allow_uncertain = FALSE` is equal to uncertainty level 0 and will skip all rules. You can also use e.g. `as.mo(..., allow_uncertain = 1)` to only allow up to level 1 uncertainty.
-#' 
+#'
 #' With the default setting (`allow_uncertain = TRUE`, level 2), below examples will lead to valid results:
 #' - `"Streptococcus group B (known as S. agalactiae)"`. The text between brackets will be removed and a warning will be thrown that the result *Streptococcus group B* (``r as.mo("Streptococcus group B")``) needs review.
 #' - `"S. aureus - please mind: MRSA"`. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result *Staphylococcus aureus* (``r as.mo("Staphylococcus aureus")``) needs review.
 #' - `"Fluoroquinolone-resistant Neisseria gonorrhoeae"`. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result *Neisseria gonorrhoeae* (``r as.mo("Neisseria gonorrhoeae")``) needs review.
-#' 
+#'
 #' There are three helper functions that can be run after using the [as.mo()] function:
 #' - Use [mo_uncertainties()] to get a [data.frame] that prints in a pretty format with all taxonomic names that were guessed. The output contains the matching score for all matches (see *Background on matching score*).
 #' - Use [mo_failures()] to get a [character] [vector] with all values that could not be coerced to a valid value.
 #' - Use [mo_renamed()] to get a [data.frame] with all values that could be coerced based on old, previously accepted taxonomic names.
 #'
 #' ## Microbial prevalence of pathogens in humans
-#' 
+#'
 #' The intelligent rules consider the prevalence of microorganisms in humans grouped into three groups, which is available as the `prevalence` columns in the [microorganisms] and [microorganisms.old] data sets. The grouping into human pathogenic prevalence is explained in the section *Matching score for microorganisms* below.
 #' @inheritSection mo_matching_score Matching score for microorganisms
 #' @inheritSection catalogue_of_life Catalogue of Life
@@ -110,7 +110,7 @@
 #' @export
 #' @return A [character] [vector] with additional class [`mo`]
 #' @seealso [microorganisms] for the [data.frame] that is being used to determine ID's.
-#' 
+#'
 #' The [mo_property()] functions (like [mo_genus()], [mo_gramstain()]) to get properties based on the returned code.
 #' @inheritSection AMR Reference data publicly available
 #' @inheritSection AMR Read more on our website!
@@ -130,7 +130,7 @@
 #' as.mo("VISA")    # Vancomycin Intermediate S. aureus
 #' as.mo("VRSA")    # Vancomycin Resistant S. aureus
 #' as.mo(115329001) # SNOMED CT code
-#' 
+#'
 #' # Dyslexia is no problem - these all work:
 #' as.mo("Ureaplasma urealyticum")
 #' as.mo("Ureaplasma urealyticus")
@@ -151,10 +151,10 @@
 #' mo_genus("E. coli")           # returns "Escherichia"
 #' mo_gramstain("E. coli")       # returns "Gram negative"
 #' }
-as.mo <- function(x, 
-                  Becker = FALSE, 
-                  Lancefield = FALSE, 
-                  allow_uncertain = TRUE, 
+as.mo <- function(x,
+                  Becker = FALSE,
+                  Lancefield = FALSE,
+                  allow_uncertain = TRUE,
                   reference_df = get_mo_source(),
                   ignore_pattern = getOption("AMR_ignore_pattern"),
                   language = get_locale(),
@@ -166,9 +166,9 @@ 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)
-  
+
   check_dataset_integrity()
-  
+
   if (tryCatch(all(x[!is.na(x)] %in% MO_lookup$mo)
                & isFALSE(Becker)
                & isFALSE(Lancefield), error = function(e) FALSE)) {
@@ -176,34 +176,34 @@ as.mo <- function(x,
     # is.mo() won't work - codes might change between package versions
     return(to_class_mo(x))
   }
-  
+
   if (tryCatch(all(x == "" | gsub(".*(unknown ).*", "unknown name", tolower(x), perl = TRUE) %in% MO_lookup$fullname_lower, na.rm = TRUE)
                & isFALSE(Becker)
                & isFALSE(Lancefield), error = function(e) FALSE)) {
     # to improve speed, special case for taxonomically correct full names (case-insensitive)
     return(MO_lookup[match(gsub(".*(unknown ).*", "unknown name", tolower(x), perl = TRUE), MO_lookup$fullname_lower), "mo", drop = TRUE])
   }
-  
+
   # start off with replaced language-specific non-ASCII characters with ASCII characters
   x <- parse_and_convert(x)
   # replace mo codes used in older package versions
   x <- replace_old_mo_codes(x, property = "mo")
   # ignore cases that match the ignore pattern
   x <- replace_ignore_pattern(x, ignore_pattern)
-  
+
   # WHONET: xxx = no growth
   x[tolower(as.character(paste0(x, ""))) %in% c("", "xxx", "na", "nan")] <- NA_character_
   # Laboratory systems: remove (translated) entries like "no growth", etc.
   x[trimws2(x) %like% translate_AMR("no .*growth", language = language)] <- NA_character_
   x[trimws2(x) %like% paste0("^(", translate_AMR("no|not", language = language), ") [a-z]+")] <- "UNKNOWN"
   uncertainty_level <- translate_allow_uncertain(allow_uncertain)
-  
+
   if (mo_source_isvalid(reference_df)
       & isFALSE(Becker)
       & isFALSE(Lancefield)
       & !is.null(reference_df)
       & all(x %in% reference_df[, 1][[1]])) {
-    
+
     # has valid own reference_df
     # (data.table not faster here)
     reference_df <- reference_df %pm>% pm_filter(!is.na(mo))
@@ -221,25 +221,27 @@ as.mo <- function(x,
     suppressWarnings(
       y <- data.frame(x = x, stringsAsFactors = FALSE) %pm>%
         pm_left_join(reference_df, by = "x") %pm>%
-        pm_pull("mo")
+        pm_pull("mo") %pm>%
+        # run as.mo() for when using old microbial codes
+        as.mo()
     )
-    
+
   } else if (all(x[!is.na(x)] %in% MO_lookup$mo)
              & isFALSE(Becker)
              & isFALSE(Lancefield)) {
     y <- x
-    
+
   } else {
     # will be checked for mo class in validation and uses exec_as.mo internally if necessary
     y <- mo_validate(x = x, property = "mo",
                      Becker = Becker, Lancefield = Lancefield,
-                     allow_uncertain = uncertainty_level, 
+                     allow_uncertain = uncertainty_level,
                      reference_df = reference_df,
                      ignore_pattern = ignore_pattern,
                      language = language,
                      ...)
   }
-  
+
   to_class_mo(y)
 }
 
@@ -290,24 +292,24 @@ exec_as.mo <- function(x,
   meet_criteria(actual_uncertainty, allow_class = "numeric", has_length = 1)
   meet_criteria(actual_input, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   check_dataset_integrity()
-  
-  lookup <- function(needle, 
+
+  lookup <- function(needle,
                      column = property,
                      haystack = reference_data_to_use,
                      n = 1,
-                     debug_mode = debug, 
+                     debug_mode = debug,
                      initial = initial_search,
                      uncertainty = actual_uncertainty,
                      input_actual = actual_input) {
-    
+
     if (!is.null(input_actual)) {
       input <- input_actual
     } else {
       input <- tryCatch(x_backup[i], error = function(e) "")
     }
-    
+
     # `column` can be NULL for all columns, or a selection
     # returns a character (vector) - if `column` > length 1 then with columns as names
     if (isTRUE(debug_mode)) {
@@ -317,7 +319,7 @@ exec_as.mo <- function(x,
       res_df <- haystack[which(eval(substitute(needle), envir = haystack, enclos = parent.frame())), , drop = FALSE]
       if (NROW(res_df) > 1 & uncertainty != -1) {
         # sort the findings on matching score
-        scores <- mo_matching_score(x = input, 
+        scores <- mo_matching_score(x = input,
                                     n = res_df[, "fullname", drop = TRUE])
         res_df <- res_df[order(scores, decreasing = TRUE), , drop = FALSE]
       }
@@ -326,7 +328,7 @@ exec_as.mo <- function(x,
         if (isTRUE(debug_mode)) {
           cat(font_red(" (no match)\n"))
         }
-        NA_character_ 
+        NA_character_
       } else {
         if (isTRUE(debug_mode)) {
           cat(font_green(paste0(" **MATCH** (", NROW(res_df), " results)\n")))
@@ -358,27 +360,27 @@ exec_as.mo <- function(x,
       res
     }
   }
-  
+
   # start off with replaced language-specific non-ASCII characters with ASCII characters
   x <- parse_and_convert(x)
   # replace mo codes used in older package versions
   x <- replace_old_mo_codes(x, property)
   # ignore cases that match the ignore pattern
   x <- replace_ignore_pattern(x, ignore_pattern)
-  
+
   # WHONET: xxx = no growth
   x[tolower(as.character(paste0(x, ""))) %in% c("", "xxx", "na", "nan")] <- NA_character_
   # Laboratory systems: remove (translated) entries like "no growth", etc.
   x[trimws2(x) %like% translate_AMR("no .*growth", language = language)] <- NA_character_
   x[trimws2(x) %like% paste0("^(", translate_AMR("no|not", language = language), ") [a-z]+")] <- "UNKNOWN"
-  
+
   if (initial_search == TRUE) {
     options(mo_failures = NULL)
     options(mo_uncertainties = NULL)
     options(mo_renamed = NULL)
   }
   options(mo_renamed_last_run = NULL)
-  
+
   failures <- character(0)
   uncertainty_level <- translate_allow_uncertain(allow_uncertain)
   uncertainties <- data.frame(uncertainty = integer(0),
@@ -388,8 +390,7 @@ exec_as.mo <- function(x,
                               mo = character(0),
                               candidates = character(0),
                               stringsAsFactors = FALSE)
-  old_mo_warning <- FALSE
-  
+
   x_input <- x
   # already strip leading and trailing spaces
   x <- trimws(x)
@@ -401,25 +402,28 @@ exec_as.mo <- function(x,
          & !is.null(x)
          & !identical(x, "")
          & !identical(x, "xxx")]
-  
+
   # defined df to check for
   if (!is.null(reference_df)) {
     mo_source_isvalid(reference_df)
-    
+
     reference_df <- reference_df %pm>% pm_filter(!is.na(mo))
-    # keep only first two columns, second must be mo
+    # keep only first two columns, second must be named "mo"
     if (colnames(reference_df)[1] == "mo") {
       reference_df <- reference_df[, c(2, 1)]
     } else {
       reference_df <- reference_df[, c(1, 2)]
     }
+    # some microbial codes might be old
+    reference_df$mo <- as.mo(reference_df$mo)
+    
     colnames(reference_df)[1] <- "x"
     # remove factors, just keep characters
     suppressWarnings(
       reference_df[] <- lapply(reference_df, as.character)
     )
   }
-  
+
   # all empty
   if (all(identical(trimws(x_input), "") | is.na(x_input) | length(x) == 0)) {
     if (property == "mo") {
@@ -427,39 +431,39 @@ exec_as.mo <- function(x,
     } else {
       return(rep(NA_character_, length(x_input)))
     }
-    
+
   } else if (all(x %in% reference_df[, 1][[1]])) {
     # all in reference df
     colnames(reference_df)[1] <- "x"
     suppressWarnings(
       x <- MO_lookup[match(reference_df[match(x, reference_df$x), "mo", drop = TRUE], MO_lookup$mo), property, drop = TRUE]
     )
-    
+
   } else if (all(x %in% reference_data_to_use$mo)) {
     x <- MO_lookup[match(x, MO_lookup$mo), property, drop = TRUE]
-    
+
   } else if (all(tolower(x) %in% reference_data_to_use$fullname_lower)) {
     # we need special treatment for very prevalent full names, they are likely!
     # e.g. as.mo("Staphylococcus aureus")
     x <- MO_lookup[match(tolower(x), MO_lookup$fullname_lower), property, drop = TRUE]
-    
+
   } else if (all(x %in% reference_data_to_use$fullname)) {
     # we need special treatment for very prevalent full names, they are likely!
     # e.g. as.mo("Staphylococcus aureus")
     x <- MO_lookup[match(x, MO_lookup$fullname), property, drop = TRUE]
-    
+
   } else if (all(toupper(x) %in% microorganisms.codes$code)) {
     # commonly used MO codes
-    x <- MO_lookup[match(microorganisms.codes[match(toupper(x), 
-                                                    microorganisms.codes$code), 
+    x <- MO_lookup[match(microorganisms.codes[match(toupper(x),
+                                                    microorganisms.codes$code),
                                               "mo",
-                                              drop = TRUE], 
-                         MO_lookup$mo), 
+                                              drop = TRUE],
+                         MO_lookup$mo),
                    property,
                    drop = TRUE]
-    
+
   } else if (!all(x %in% microorganisms[, property])) {
-    
+
     strip_whitespace <- function(x, dyslexia_mode) {
       # all whitespaces (tab, new lines, etc.) should be one space
       # and spaces before and after should be omitted
@@ -472,22 +476,22 @@ exec_as.mo <- function(x,
       }
       trimmed
     }
-    
+
     x_backup_untouched <- x
     x <- strip_whitespace(x, dyslexia_mode)
     x_backup <- x
-    
+
     # from here on case-insensitive
     x <- tolower(x)
-    
+
     x_backup[grepl("^(fungus|fungi)$", x)] <- "F_FUNGUS" # will otherwise become the kingdom
-    
+
     # remove spp and species
     x <- gsub(" +(spp.?|ssp.?|sp.? |ss ?.?|subsp.?|subspecies|biovar |serovar |species)", " ", x, perl = TRUE)
     x <- gsub("(spp.?|subsp.?|subspecies|biovar|serovar|species)", "", x, perl = TRUE)
     x <- gsub("^([a-z]{2,4})(spe.?)$", "\\1", x, perl = TRUE) # when ending in SPE instead of SPP and preceded by 2-4 characters
     x <- strip_whitespace(x, dyslexia_mode)
-    
+
     x_backup_without_spp <- x
     x_species <- paste(x, "species")
     # translate to English for supported languages of mo_property
@@ -554,7 +558,7 @@ exec_as.mo <- function(x,
     # make sure to remove regex overkill (will lead to errors)
     x <- gsub("++", "+", x, fixed = TRUE)
     x <- gsub("?+", "?", x, fixed = TRUE)
-    
+
     x_trimmed <- x
     x_trimmed_species <- paste(x_trimmed, "species")
     x_trimmed_without_group <- gsub(" gro.u.p$", "", x_trimmed, perl = TRUE)
@@ -565,11 +569,11 @@ exec_as.mo <- function(x,
     x <- gsub("[ .]+", ".*", x, perl = TRUE)
     # add start en stop regex
     x <- paste0("^", x, "$")
-    
+
     x_withspaces_start_only <- paste0("^", x_withspaces)
     x_withspaces_end_only <- paste0(x_withspaces, "$")
     x_withspaces_start_end <- paste0("^", x_withspaces, "$")
-    
+
     if (isTRUE(debug)) {
       cat(paste0(font_blue("x"), '                       "', x, '"\n'))
       cat(paste0(font_blue("x_species"), '               "', x_species, '"\n'))
@@ -582,25 +586,25 @@ exec_as.mo <- function(x,
       cat(paste0(font_blue("x_trimmed_species"), '       "', x_trimmed_species, '"\n'))
       cat(paste0(font_blue("x_trimmed_without_group"), ' "', x_trimmed_without_group, '"\n'))
     }
-    
+
     if (initial_search == TRUE) {
       progress <- progress_ticker(n = length(x), n_min = 25) # start if n >= 25
       on.exit(close(progress))
     }
-    
+
     for (i in seq_len(length(x))) {
-      
+
       if (initial_search == TRUE) {
         progress$tick()
       }
-      
+
       # valid MO code ----
       found <- lookup(mo == toupper(x_backup[i]))
       if (!is.na(found)) {
         x[i] <- found[1L]
         next
       }
-      
+
       # valid fullname ----
       found <- lookup(fullname_lower %in% gsub("[^a-zA-Z0-9_. -]", "", tolower(c(x_backup[i], x_backup_without_spp[i])), perl = TRUE))
       # added the gsub() for "(unknown fungus)", since fullname_lower does not contain brackets
@@ -608,7 +612,7 @@ exec_as.mo <- function(x,
         x[i] <- found[1L]
         next
       }
-      
+
       # old fullname ----
       found <- lookup(fullname_lower %in% tolower(c(x_backup[i], x_backup_without_spp[i])),
                       column = NULL, # all columns
@@ -630,13 +634,13 @@ exec_as.mo <- function(x,
                     mo = lookup(fullname == found["fullname_new"], "mo", haystack = MO_lookup))
         next
       }
-      
+
       if (x_backup[i] %like_case% "\\(unknown [a-z]+\\)" | tolower(x_backup_without_spp[i]) %in% c("other", "none", "unknown")) {
         # empty and nonsense values, ignore without warning
         x[i] <- lookup(mo == "UNKNOWN")
         next
       }
-      
+
       # exact SNOMED code ----
       if (x_backup[i] %like% "^[0-9]+$") {
         snomed_found <- unlist(lapply(reference_data_to_use$snomed,
@@ -653,24 +657,24 @@ exec_as.mo <- function(x,
           }
         }
       }
-      
+
       # very probable: is G. species ----
-      found <- lookup(g_species %in% gsub("[^a-z0-9/ \\-]+", "", 
+      found <- lookup(g_species %in% gsub("[^a-z0-9/ \\-]+", "",
                                           tolower(c(x_backup[i], x_backup_without_spp[i])), perl = TRUE))
       if (!is.na(found)) {
         x[i] <- found[1L]
         next
       }
-      
+
       # WHONET and other common LIS codes ----
       found <- lookup(code %in% toupper(c(x_backup_untouched[i], x_backup[i], x_backup_without_spp[i])),
-                      column = "mo", 
+                      column = "mo",
                       haystack = microorganisms.codes)
       if (!is.na(found)) {
         x[i] <- lookup(mo == found)
         next
       }
-      
+
       # user-defined reference ----
       if (!is.null(reference_df)) {
         if (x_backup[i] %in% reference_df[, 1]) {
@@ -680,13 +684,13 @@ exec_as.mo <- function(x,
           next
         }
       }
-      
+
       # WHONET: xxx = no growth
       if (tolower(as.character(paste0(x_backup_without_spp[i], ""))) %in% c("", "xxx", "na", "nan")) {
         x[i] <- NA_character_
         next
       }
-      
+
       # 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)") {
@@ -697,13 +701,13 @@ exec_as.mo <- function(x,
         }
         next
       }
-      
+
       if (x_backup_without_spp[i] %like_case% "(virus|viridae)") {
         # there is no fullname like virus or viridae, so don't try to coerce it
         x[i] <- NA_character_
         next
       }
-      
+
       # translate known trivial abbreviations to genus + species ----
       if (toupper(x_backup_without_spp[i]) %in% c("MRSA", "MSSA", "VISA", "VRSA", "BORSA")
           | x_backup_without_spp[i] %like_case% " (mrsa|mssa|visa|vrsa) ") {
@@ -765,14 +769,14 @@ exec_as.mo <- function(x,
       }
       if (x_backup_without_spp[i] %like_case% "(streptococ|streptokok).* [abcdfghk]$") {
         # Streptococci in different languages, like "estreptococos grupo B"
-        x[i] <- lookup(mo == toupper(gsub(".*(streptococ|streptokok|estreptococ).* ([abcdfghk])$", 
+        x[i] <- lookup(mo == toupper(gsub(".*(streptococ|streptokok|estreptococ).* ([abcdfghk])$",
                                           "B_STRPT_GRP\\2",
                                           x_backup_without_spp[i])), uncertainty = -1)
         next
       }
       if (x_backup_without_spp[i] %like_case% "group [abcdfghk] (streptococ|streptokok|estreptococ)") {
         # Streptococci in different languages, like "Group A Streptococci"
-        x[i] <- lookup(mo == toupper(gsub(".*group ([abcdfghk]) (streptococ|streptokok|estreptococ).*", 
+        x[i] <- lookup(mo == toupper(gsub(".*group ([abcdfghk]) (streptococ|streptokok|estreptococ).*",
                                           "B_STRPT_GRP\\1",
                                           x_backup_without_spp[i])), uncertainty = -1)
         next
@@ -831,7 +835,7 @@ exec_as.mo <- function(x,
         x[i] <- lookup(genus == "Mycobacterium", uncertainty = -1)
         next
       }
-      
+
       if (x_backup_without_spp[i] %like_case% "salmonella [a-z]+ ?.*") {
         if (x_backup_without_spp[i] %like_case% "salmonella group") {
           # Salmonella Group A to Z, just return S. species for now
@@ -849,7 +853,7 @@ exec_as.mo <- function(x,
           next
         }
       }
-      
+
       # trivial names known to the field:
       if ("meningococcus" %like_case% x_trimmed[i]) {
         # coerce Neisseria meningitidis
@@ -867,7 +871,7 @@ exec_as.mo <- function(x,
         next
       }
       # }
-      
+
       # NOW RUN THROUGH DIFFERENT PREVALENCE LEVELS
       check_per_prevalence <- function(data_to_check,
                                        data.old_to_check,
@@ -880,10 +884,10 @@ exec_as.mo <- function(x,
                                        g.x_backup_without_spp,
                                        h.x_species,
                                        i.x_trimmed_species) {
-        
+
         # FIRST TRY FULLNAMES AND CODES ----
         # if only genus is available, return only genus
-        
+
         if (all(!c(x[i], b.x_trimmed) %like_case% " ")) {
           found <- lookup(fullname_lower %in% c(h.x_species, i.x_trimmed_species),
                           haystack = data_to_check)
@@ -901,7 +905,7 @@ exec_as.mo <- function(x,
           }
           # rest of genus only is in allow_uncertain part.
         }
-        
+
         # allow no codes less than 4 characters long, was already checked for WHONET earlier
         if (nchar(g.x_backup_without_spp) < 4) {
           x[i] <- lookup(mo == "UNKNOWN")
@@ -910,21 +914,21 @@ exec_as.mo <- function(x,
           }
           return(x[i])
         }
-        
+
         # try probable: trimmed version of fullname ----
         found <- lookup(fullname_lower %in% tolower(g.x_backup_without_spp),
                         haystack = data_to_check)
         if (!is.na(found)) {
           return(found[1L])
         }
-        
+
         # try any match keeping spaces ----
         found <- lookup(fullname_lower %like_case% d.x_withspaces_start_end,
                         haystack = data_to_check)
         if (!is.na(found) & nchar(g.x_backup_without_spp) >= 6) {
           return(found[1L])
         }
-        
+
         # try any match keeping spaces, not ending with $ ----
         found <- lookup(fullname_lower %like_case% paste0(trimws(e.x_withspaces_start_only), " "),
                         haystack = data_to_check)
@@ -936,14 +940,14 @@ exec_as.mo <- function(x,
         if (!is.na(found) & nchar(g.x_backup_without_spp) >= 6) {
           return(found[1L])
         }
-        
+
         # try any match keeping spaces, not start with ^ ----
         found <- lookup(fullname_lower %like_case% paste0(" ", trimws(f.x_withspaces_end_only)),
                         haystack = data_to_check)
         if (!is.na(found)) {
           return(found[1L])
         }
-        
+
         # try a trimmed version
         found <- lookup(fullname_lower %like_case% b.x_trimmed |
                           fullname_lower %like_case% c.x_trimmed_without_group,
@@ -951,8 +955,8 @@ exec_as.mo <- function(x,
         if (!is.na(found) & nchar(g.x_backup_without_spp) >= 6) {
           return(found[1L])
         }
-        
-        
+
+
         # try splitting of characters in the middle and then find ID ----
         # only when text length is 6 or lower
         # like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus, staaur = S. aureus
@@ -968,7 +972,7 @@ exec_as.mo <- function(x,
             return(found[1L])
           }
         }
-        
+
         # try fullname without start and without nchar limit of >= 6 ----
         # like "K. pneu rhino" >> "Klebsiella pneumoniae (rhinoscleromatis)" = KLEPNERH
         found <- lookup(fullname_lower %like_case% e.x_withspaces_start_only,
@@ -976,9 +980,9 @@ exec_as.mo <- function(x,
         if (!is.na(found)) {
           return(found[1L])
         }
-        
+
         # MISCELLANEOUS ----
-        
+
         # look for old taxonomic names ----
         found <- lookup(fullname_lower %like_case% e.x_withspaces_start_only,
                         column = NULL, # all columns
@@ -1000,7 +1004,7 @@ exec_as.mo <- function(x,
                       mo = lookup(fullname == found["fullname_new"], "mo", haystack = MO_lookup))
           return(x[i])
         }
-        
+
         # check for uncertain results ----
         uncertain_fn <- function(a.x_backup,
                                  b.x_trimmed,
@@ -1009,16 +1013,16 @@ exec_as.mo <- function(x,
                                  f.x_withspaces_end_only,
                                  g.x_backup_without_spp,
                                  uncertain.reference_data_to_use) {
-          
+
           if (uncertainty_level == 0) {
             # do not allow uncertainties
             return(NA_character_)
           }
-          
+
           # UNCERTAINTY LEVEL 1 ----
           if (uncertainty_level >= 1) {
             now_checks_for_uncertainty_level <- 1
-            
+
             # (1) look again for old taxonomic names, now for G. species ----
             if (isTRUE(debug)) {
               cat(font_bold("\n[ UNCERTAINTY LEVEL", now_checks_for_uncertainty_level, "] (1) look again for old taxonomic names, now for G. species\n"))
@@ -1051,7 +1055,7 @@ exec_as.mo <- function(x,
                                                                result_mo = lookup(fullname == found["fullname_new"], "mo", haystack = MO_lookup)))
               return(x)
             }
-            
+
             # (2) Try with misspelled input ----
             # just rerun with dyslexia_mode = TRUE will used the extensive regex part above
             if (isTRUE(debug)) {
@@ -1074,11 +1078,11 @@ exec_as.mo <- function(x,
               return(found)
             }
           }
-          
+
           # UNCERTAINTY LEVEL 2 ----
           if (uncertainty_level >= 2) {
             now_checks_for_uncertainty_level <- 2
-            
+
             # (3) look for genus only, part of name ----
             if (isTRUE(debug)) {
               cat(font_bold("\n[ UNCERTAINTY LEVEL", now_checks_for_uncertainty_level, "] (3) look for genus only, part of name\n"))
@@ -1102,7 +1106,7 @@ exec_as.mo <- function(x,
                 }
               }
             }
-            
+
             # (4) strip values between brackets ----
             if (isTRUE(debug)) {
               cat(font_bold("\n[ UNCERTAINTY LEVEL", now_checks_for_uncertainty_level, "] (4) strip values between brackets\n"))
@@ -1125,7 +1129,7 @@ exec_as.mo <- function(x,
               found <- lookup(mo == found)
               return(found)
             }
-            
+
             # (5) inverse input ----
             if (isTRUE(debug)) {
               cat(font_bold("\n[ UNCERTAINTY LEVEL", now_checks_for_uncertainty_level, "] (5) inverse input\n"))
@@ -1134,7 +1138,7 @@ exec_as.mo <- function(x,
             if (isTRUE(debug)) {
               message("Running '", a.x_backup_inversed, "'")
             }
-            
+
             # first try without dyslexia mode
             found <- suppressMessages(suppressWarnings(exec_as.mo(a.x_backup_inversed, initial_search = FALSE, dyslexia_mode = FALSE, allow_uncertain = FALSE, debug = debug, reference_data_to_use = uncertain.reference_data_to_use, actual_uncertainty = 2, actual_input = a.x_backup)))
             if (empty_result(found)) {
@@ -1148,7 +1152,7 @@ exec_as.mo <- function(x,
               found <- lookup(mo == found)
               return(found)
             }
-            
+
             # (6) try to strip off half an element from end and check the remains ----
             if (isTRUE(debug)) {
               cat(font_bold("\n[ UNCERTAINTY LEVEL", now_checks_for_uncertainty_level, "] (6) try to strip off half an element from end and check the remains\n"))
@@ -1197,7 +1201,7 @@ exec_as.mo <- function(x,
                     # then with dyslexia mode
                     found <- suppressMessages(suppressWarnings(exec_as.mo(x_strip_collapsed, initial_search = FALSE, dyslexia_mode = TRUE, allow_uncertain = FALSE, debug = debug, reference_data_to_use = uncertain.reference_data_to_use, actual_uncertainty = 2, actual_input = a.x_backup)))
                   }
-                  
+
                   if (!empty_result(found)) {
                     found_result <- found
                     uncertainties <<- rbind(uncertainties,
@@ -1262,11 +1266,11 @@ exec_as.mo <- function(x,
               }
             }
           }
-          
+
           # UNCERTAINTY LEVEL 3 ----
           if (uncertainty_level >= 3) {
             now_checks_for_uncertainty_level <- 3
-            
+
             # (10) try to strip off one element from start and check the remains (any text size) ----
             if (isTRUE(debug)) {
               cat(font_bold("\n[ UNCERTAINTY LEVEL", now_checks_for_uncertainty_level, "] (10) try to strip off one element from start and check the remains (any text size)\n"))
@@ -1319,7 +1323,7 @@ exec_as.mo <- function(x,
                 }
               }
             }
-            
+
             # (12) part of a name (very unlikely match) ----
             if (isTRUE(debug)) {
               cat(font_bold("\n[ UNCERTAINTY LEVEL", now_checks_for_uncertainty_level, "] (12) part of a name (very unlikely match)\n"))
@@ -1336,38 +1340,38 @@ exec_as.mo <- function(x,
               return(found)
             }
           }
-          
-          
+
+
           # didn't found in uncertain results too
           return(NA_character_)
         }
-        
+
         # uncertain results
-        x[i] <- uncertain_fn(a.x_backup = a.x_backup, 
+        x[i] <- uncertain_fn(a.x_backup = a.x_backup,
                              b.x_trimmed = b.x_trimmed,
                              d.x_withspaces_start_end = d.x_withspaces_start_end,
-                             e.x_withspaces_start_only = e.x_withspaces_start_only, 
+                             e.x_withspaces_start_only = e.x_withspaces_start_only,
                              f.x_withspaces_end_only = f.x_withspaces_end_only,
                              g.x_backup_without_spp = g.x_backup_without_spp,
                              uncertain.reference_data_to_use = MO_lookup) # MO_lookup[which(MO_lookup$prevalence %in% c(1, 2)), ])
         if (!empty_result(x[i])) {
           return(x[i])
         }
-        # x[i] <- uncertain_fn(a.x_backup = a.x_backup, 
+        # x[i] <- uncertain_fn(a.x_backup = a.x_backup,
         #                      b.x_trimmed = b.x_trimmed,
         #                      d.x_withspaces_start_end = d.x_withspaces_start_end,
-        #                      e.x_withspaces_start_only = e.x_withspaces_start_only, 
+        #                      e.x_withspaces_start_only = e.x_withspaces_start_only,
         #                      f.x_withspaces_end_only = f.x_withspaces_end_only,
         #                      g.x_backup_without_spp = g.x_backup_without_spp,
         #                      uncertain.reference_data_to_use = MO_lookup[which(MO_lookup$prevalence == 3), ])
         # if (!empty_result(x[i])) {
         #   return(x[i])
         # }
-        
+
         # didn't found any
         return(NA_character_)
       }
-      
+
       # CHECK ALL IN ONE GO ----
       x[i] <- check_per_prevalence(data_to_check = MO_lookup,
                                    data.old_to_check = MO.old_lookup,
@@ -1383,20 +1387,20 @@ exec_as.mo <- function(x,
       if (!empty_result(x[i])) {
         next
       }
-      
-      
+
+
       # no results found: make them UNKNOWN ----
       x[i] <- lookup(mo == "UNKNOWN", uncertainty = -1)
       if (initial_search == TRUE) {
         failures <- c(failures, x_backup[i])
       }
     }
-    
+
     if (initial_search == TRUE) {
       close(progress)
     }
   }
-  
+
   # handling failures ----
   failures <- failures[!failures %in% c(NA, NULL, NaN)]
   if (length(failures) > 0 & initial_search == TRUE) {
@@ -1427,7 +1431,7 @@ exec_as.mo <- function(x,
   if (NROW(uncertainties) > 0 & initial_search == TRUE) {
     uncertainties <- as.list(pm_distinct(uncertainties, input, .keep_all = TRUE))
     options(mo_uncertainties = uncertainties)
-    
+
     plural <- c("", "it", "was")
     if (length(uncertainties$input) > 1) {
       plural <- c("s", "them", "were")
@@ -1436,7 +1440,7 @@ exec_as.mo <- function(x,
                   " ", plural[3], " guessed with uncertainty. Use mo_uncertainties() to review ", plural[2], ".")
     message(font_red(msg))
   }
-  
+
   # Becker ----
   if (Becker == TRUE | Becker == "all") {
     # warn when species found that are not in:
@@ -1445,7 +1449,7 @@ exec_as.mo <- function(x,
     # - Becker et al. 2020, PMID 32056452
     post_Becker <- c("") # 2020-10-20 currently all are mentioned in above papers
     if (any(x %in% MO_lookup[which(MO_lookup$species %in% post_Becker), property])) {
-      
+
       warning("Becker ", font_italic("et al."), " (2014, 2019) does not contain these species named after their publication: ",
               font_italic(paste("S.",
                                 sort(mo_species(unique(x[x %in% MO_lookup[which(MO_lookup$species %in% post_Becker), property]]))),
@@ -1454,19 +1458,19 @@ exec_as.mo <- function(x,
               call. = FALSE,
               immediate. = TRUE)
     }
-    
+
     # 'MO_CONS' and 'MO_COPS' are <mo> vectors created in R/zzz.R
     CoNS <- MO_lookup[which(MO_lookup$mo %in% MO_CONS), property, drop = TRUE]
     x[x %in% CoNS] <- lookup(mo == "B_STPHY_CONS", uncertainty = -1)
-    
+
     CoPS <- MO_lookup[which(MO_lookup$mo %in% MO_COPS), property, drop = TRUE]
     x[x %in% CoPS] <- lookup(mo == "B_STPHY_COPS", uncertainty = -1)
-    
+
     if (Becker == "all") {
       x[x %in% lookup(fullname %like_case% "^Staphylococcus aureus", n = Inf)] <- lookup(mo == "B_STPHY_COPS", uncertainty = -1)
     }
   }
-  
+
   # Lancefield ----
   if (Lancefield == TRUE | Lancefield == "all") {
     # group A - S. pyogenes
@@ -1488,52 +1492,47 @@ exec_as.mo <- function(x,
     # group K - S. salivarius
     x[x %in% lookup(genus == "Streptococcus" & species == "salivarius", n = Inf)] <- lookup(fullname == "Streptococcus group K", uncertainty = -1)
   }
-  
+
   # Wrap up ----------------------------------------------------------------
-  
+
   # comply to x, which is also unique and without empty values
   x_input_unique_nonempty <- unique(x_input[!is.na(x_input)
                                             & !is.null(x_input)
                                             & !identical(x_input, "")
                                             & !identical(x_input, "xxx")])
-  
+
   # left join the found results to the original input values (x_input)
   df_found <- data.frame(input = as.character(x_input_unique_nonempty),
                          found = as.character(x),
                          stringsAsFactors = FALSE)
   df_input <- data.frame(input = as.character(x_input),
                          stringsAsFactors = FALSE)
-  
+
   # super fast using match() which is a lot faster than merge()
   x <- df_found$found[match(df_input$input, df_found$input)]
-  
+
   if (property == "mo") {
     x <- to_class_mo(x)
   }
-  
+
   if (length(mo_renamed()) > 0) {
     print(mo_renamed())
   }
-  
+
   if (initial_search == FALSE) {
     # we got here from uncertain_fn().
     if (NROW(uncertainties) == 0) {
       # the stripped/transformed version of x_backup is apparently a full hit, like with: as.mo("Escherichia (hello there) coli")
-      uncertainties <- rbind(uncertainties, 
-                             format_uncertainty_as_df(uncertainty_level = actual_uncertainty, 
-                                                      input = actual_input, 
+      uncertainties <- rbind(uncertainties,
+                             format_uncertainty_as_df(uncertainty_level = actual_uncertainty,
+                                                      input = actual_input,
                                                       result_mo = x,
                                                       candidates = ""))
     }
     # this will save the uncertain items as attribute, so they can be bound to `uncertainties` in the uncertain_fn() function
     x <- structure(x, uncertainties = uncertainties)
   }
-  
-  
-  if (old_mo_warning == TRUE & property != "mo") {
-    warning("The input contained old microorganism IDs from previous versions of this package.\nPlease use `as.mo()` on these old IDs to transform them to the new format.\nSUPPORT FOR THIS WILL BE DROPPED IN A FUTURE VERSION.", call. = FALSE)
-  }
-  
+
   x
 }
 
@@ -1542,11 +1541,11 @@ empty_result <- function(x) {
 }
 
 was_renamed <- function(name_old, name_new, ref_old = "", ref_new = "", mo = "") {
-  newly_set <- data.frame(old_name = name_old, 
+  newly_set <- data.frame(old_name = name_old,
                           old_ref = ref_old,
                           new_name = name_new,
                           new_ref = ref_new,
-                          mo = mo, 
+                          mo = mo,
                           stringsAsFactors = FALSE)
   already_set <- getOption("mo_renamed")
   if (!is.null(already_set)) {
@@ -1585,14 +1584,14 @@ 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")
-  
+
   # make it always fit exactly
   create_pillar_column(out,
-                       align = "left", 
+                       align = "left",
                        width = max(nchar(x)) + ifelse(any(x %in% c(NA, "UNKNOWN")), 2, 0))
 }
 
@@ -1706,7 +1705,7 @@ as.data.frame.mo <- function(x, ...) {
   y <- NextMethod()
   attributes(y) <- attributes(i)
   # must only contain valid MOs
-  class_integrity_check(y, "microorganism code", c(as.character(microorganisms$mo), 
+  class_integrity_check(y, "microorganism code", c(as.character(microorganisms$mo),
                                                    as.character(microorganisms.translation$mo_old)))
 }
 #' @method [[<- mo
@@ -1716,7 +1715,7 @@ as.data.frame.mo <- function(x, ...) {
   y <- NextMethod()
   attributes(y) <- attributes(i)
   # must only contain valid MOs
-  class_integrity_check(y, "microorganism code", c(as.character(microorganisms$mo), 
+  class_integrity_check(y, "microorganism code", c(as.character(microorganisms$mo),
                                                    as.character(microorganisms.translation$mo_old)))
 }
 #' @method c mo
@@ -1726,7 +1725,7 @@ c.mo <- function(x, ...) {
   y <- NextMethod()
   attributes(y) <- attributes(x)
   # must only contain valid MOs
-  class_integrity_check(y, "microorganism code", c(as.character(microorganisms$mo), 
+  class_integrity_check(y, "microorganism code", c(as.character(microorganisms$mo),
                                                    as.character(microorganisms.translation$mo_old)))
 }
 
@@ -1762,11 +1761,11 @@ print.mo_uncertainties <- function(x, ...) {
   if (NROW(x) == 0) {
     return(NULL)
   }
-  cat(font_blue(strwrap("Matching scores are based on human pathogenic prevalence and the resemblance between the input and the full taxonomic name. Please see ?mo_matching_score.", 
-                        width = 0.98 * getOption("width")), 
+  cat(font_blue(strwrap("Matching scores are based on human pathogenic prevalence and the resemblance between the input and the full taxonomic name. Please see ?mo_matching_score.",
+                        width = 0.98 * getOption("width")),
                 collapse = "\n"))
   cat("\n")
-  
+
   msg <- ""
   for (i in seq_len(nrow(x))) {
     if (x[i, ]$candidates != "") {
@@ -1778,17 +1777,17 @@ print.mo_uncertainties <- function(x, ...) {
       n_candidates <- length(candidates)
       candidates <- paste0(candidates, " (", scores_formatted[order(1 - scores)], ")", collapse = ", ")
       # align with input after arrow
-      candidates <- paste0("\n", 
+      candidates <- paste0("\n",
                            strwrap(paste0("Also matched",
-                                          ifelse(n_candidates >= 25, " (max 25)", ""), ": ", 
+                                          ifelse(n_candidates >= 25, " (max 25)", ""), ": ",
                                           candidates), # this is already max 25 due to format_uncertainty_as_df()
                                    indent = nchar(x[i, ]$input) + 6,
-                                   exdent = nchar(x[i, ]$input) + 6, 
+                                   exdent = nchar(x[i, ]$input) + 6,
                                    width = 0.98 * getOption("width")),
                            collapse = "")
       # after strwrap, make taxonomic names italic
       candidates <- gsub("([A-Za-z]+)", font_italic("\\1"), candidates)
-      candidates <- gsub(paste(font_italic(c("Also", "matched"), collapse = NULL), collapse = " "), 
+      candidates <- gsub(paste(font_italic(c("Also", "matched"), collapse = NULL), collapse = " "),
                          "Also matched",
                          candidates, fixed = TRUE)
       candidates <- gsub(font_italic("max"), "max", candidates, fixed = TRUE)
@@ -1809,7 +1808,7 @@ print.mo_uncertainties <- function(x, ...) {
                                    ", matching score = ", score,
                                    ") ")),
                      width = 0.98 * getOption("width"),
-                     exdent = nchar(x[i, ]$input) + 6), 
+                     exdent = nchar(x[i, ]$input) + 6),
                    collapse = "\n"),
                  candidates,
                  sep = "\n")
@@ -1839,14 +1838,14 @@ print.mo_renamed <- function(x, ...) {
     return(invisible())
   }
   for (i in seq_len(nrow(x))) {
-    message(font_blue(paste0("NOTE: ", 
-                             font_italic(x$old_name[i]), ifelse(x$old_ref[i] %in% c("", NA), "", 
+    message(font_blue(paste0("NOTE: ",
+                             font_italic(x$old_name[i]), ifelse(x$old_ref[i] %in% c("", NA), "",
                                                                 paste0(" (",  gsub("et al.", font_italic("et al."), x$old_ref[i]), ")")),
-                             " was renamed ", 
+                             " was renamed ",
                              ifelse(as.integer(gsub("[^0-9]", "", x$new_ref[i])) < as.integer(gsub("[^0-9]", "", x$old_ref[i])),
                                     font_bold("back to "),
                                     ""),
-                             font_italic(x$new_name[i]), ifelse(x$new_ref[i] %in% c("", NA), "", 
+                             font_italic(x$new_name[i]), ifelse(x$new_ref[i] %in% c("", NA), "",
                                                                 paste0(" (",  gsub("et al.", font_italic("et al."), x$new_ref[i]), ")")),
                              " [", x$mo[i], "]")))
   }
@@ -1934,7 +1933,9 @@ replace_old_mo_codes <- function(x, property) {
     # assign on places where a match was found
     x[which(!is.na(matched))] <- mo_new[which(!is.na(matched))]
     if (property != "mo") {
-      message(font_blue("NOTE: Old microbial codes (from previous package versions) were replaced with current codes used by this package.\n      Please update your MO codes with as.mo()." ))
+      message_(font_blue("NOTE: The input contained old microbial codes (from previous package versions). Please update your MO codes with as.mo()."))
+    } else {
+      message_(font_blue("NOTE:", length(matched), "old microbial codes (from previous package versions) were updated to current used codes."))
     }
   }
   x
@@ -1944,8 +1945,8 @@ replace_ignore_pattern <- function(x, ignore_pattern) {
   if (!is.null(ignore_pattern) && !identical(trimws2(ignore_pattern), "")) {
     ignore_cases <- x %like% ignore_pattern
     if (sum(ignore_cases) > 0) {
-      message(font_blue(paste0("NOTE: the following input was ignored by `ignore_pattern = \"", ignore_pattern, "\"`: ", 
-                               paste0("'", sort(unique(x[x %like% ignore_pattern])), "'", collapse = ", "), 
+      message(font_blue(paste0("NOTE: the following input was ignored by `ignore_pattern = \"", ignore_pattern, "\"`: ",
+                               paste0("'", sort(unique(x[x %like% ignore_pattern])), "'", collapse = ", "),
                                collapse = ", ")))
       x[x %like% ignore_pattern] <- NA_character_
     }
diff --git a/R/mo_property.R b/R/mo_property.R
index e2794d70..c5132733 100755
--- a/R/mo_property.R
+++ b/R/mo_property.R
@@ -9,7 +9,7 @@
 # (c) 2018-2020 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.       # 
+# 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  #
@@ -29,7 +29,7 @@
 #' @inheritSection lifecycle Stable lifecycle
 #' @param x any character (vector) that can be coerced to a valid microorganism code with [as.mo()]
 #' @param property one of the column names of the [microorganisms] data set or `"shortname"`
-#' @param language language of the returned text, defaults to system language (see [get_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Use `language = NULL` or `language = ""` to prevent translation.
+#' @param language language of the returned text, defaults to system language (see [get_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Also used to translate text like "no growth". Use `language = NULL` or `language = ""` to prevent translation.
 #' @param ... other parameters passed on to [as.mo()], such as 'allow_uncertain' and 'ignore_pattern'
 #' @param open browse the URL using [utils::browseURL()]
 #' @details All functions will return the most recently known taxonomic property according to the Catalogue of Life, except for [mo_ref()], [mo_authors()] and [mo_year()]. Please refer to this example, knowing that *Escherichia blattae* was renamed to *Shimwellia blattae* in 2010:
@@ -38,7 +38,7 @@
 #' - `mo_ref("Shimwellia blattae")` will return `"Priest et al., 2010"` (without a message)
 #'
 #' The short name - [mo_shortname()] - almost always returns the first character of the genus and the full species, like `"E. coli"`. Exceptions are abbreviations of staphylococci (like *"CoNS"*, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (like *"GBS"*, Group B Streptococci). Please bear in mind that e.g. *E. coli* could mean *Escherichia coli* (kingdom of Bacteria) as well as *Entamoeba coli* (kingdom of Protozoa). Returning to the full name will be done using [as.mo()] internally, giving priority to bacteria and human pathogens, i.e. `"E. coli"` will be considered *Escherichia coli*. In other words, `mo_fullname(mo_shortname("Entamoeba coli"))` returns `"Escherichia coli"`.
-#' 
+#'
 #' Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions [mo_kingdom()] and [mo_domain()] return the exact same results.
 #'
 #' The Gram stain - [mo_gramstain()] - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318)), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [is_gram_negative()] and [is_gram_positive()] always return `TRUE` or `FALSE`, even for species outside the kingdom of Bacteria.
@@ -148,7 +148,7 @@
 mo_name <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "fullname", language = language, ...), language = language, only_unknown = FALSE)
 }
 
@@ -161,20 +161,20 @@ mo_fullname <- mo_name
 mo_shortname <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x.mo <- as.mo(x, language = language, ...)
-  
+
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   replace_empty <- function(x) {
     x[x == ""] <- "spp."
     x
   }
-  
+
   # get first char of genus and complete species in English
   genera <- mo_genus(x.mo, language = NULL)
   shortnames <- paste0(substr(genera, 1, 1), ". ", replace_empty(mo_species(x.mo, language = NULL)))
-  
+
   # exceptions for where no species is known
   shortnames[shortnames %like% ".[.] spp[.]"] <- genera[shortnames %like% ".[.] spp[.]"]
   # exceptions for Staphylococci
@@ -184,7 +184,7 @@ mo_shortname <- function(x, language = get_locale(), ...) {
   shortnames[shortnames %like% "S. group [ABCDFGHK]"] <- paste0("G", gsub("S. group ([ABCDFGHK])", "\\1", shortnames[shortnames %like% "S. group [ABCDFGHK]"]), "S")
   # unknown species etc.
   shortnames[shortnames %like% "unknown"] <- paste0("(", trimws(gsub("[^a-zA-Z -]", "", shortnames[shortnames %like% "unknown"])), ")")
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
   translate_AMR(shortnames, language = language, only_unknown = FALSE)
 }
@@ -194,7 +194,7 @@ mo_shortname <- function(x, language = get_locale(), ...) {
 mo_subspecies <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "subspecies", language = language, ...), language = language, only_unknown = TRUE)
 }
 
@@ -203,7 +203,7 @@ mo_subspecies <- function(x, language = get_locale(), ...) {
 mo_species <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "species", language = language, ...), language = language, only_unknown = TRUE)
 }
 
@@ -212,7 +212,7 @@ mo_species <- function(x, language = get_locale(), ...) {
 mo_genus <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "genus", language = language, ...), language = language, only_unknown = TRUE)
 }
 
@@ -221,7 +221,7 @@ mo_genus <- function(x, language = get_locale(), ...) {
 mo_family <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "family", language = language, ...), language = language, only_unknown = TRUE)
 }
 
@@ -230,7 +230,7 @@ mo_family <- function(x, language = get_locale(), ...) {
 mo_order <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "order", language = language, ...), language = language, only_unknown = TRUE)
 }
 
@@ -239,7 +239,7 @@ mo_order <- function(x, language = get_locale(), ...) {
 mo_class <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "class", language = language, ...), language = language, only_unknown = TRUE)
 }
 
@@ -248,7 +248,7 @@ mo_class <- function(x, language = get_locale(), ...) {
 mo_phylum <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "phylum", language = language, ...), language = language, only_unknown = TRUE)
 }
 
@@ -257,7 +257,7 @@ mo_phylum <- function(x, language = get_locale(), ...) {
 mo_kingdom <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "kingdom", language = language, ...), language = language, only_unknown = TRUE)
 }
 
@@ -270,7 +270,7 @@ mo_domain <- mo_kingdom
 mo_type <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = "kingdom", language = language, ...), language = language, only_unknown = FALSE)
 }
 
@@ -279,10 +279,10 @@ mo_type <- function(x, language = get_locale(), ...) {
 mo_gramstain <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x.mo <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   x.phylum <- mo_phylum(x.mo)
   # DETERMINE GRAM STAIN FOR BACTERIA
   # Source: https://itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=956097
@@ -303,25 +303,35 @@ mo_gramstain <- function(x, language = get_locale(), ...) {
                     "Firmicutes",
                     "Tenericutes")
     | x.mo == "B_GRAMP"] <- "Gram-positive"
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
   translate_AMR(x, language = language, only_unknown = FALSE)
 }
 
 #' @rdname mo_property
 #' @export
-is_gram_negative <- function(x, ...) {
+is_gram_negative <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
-  grams <- mo_gramstain(x, language = NULL, ...)
-  "Gram-negative" == grams & !is.na(grams)
+  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
+
+  x.mo <- as.mo(x, language = language, ...)
+  metadata <- get_mo_failures_uncertainties_renamed()
+  grams <- mo_gramstain(x.mo, language = NULL)
+  load_mo_failures_uncertainties_renamed(metadata)
+  grams == "Gram-negative" & !is.na(grams)
 }
 
 #' @rdname mo_property
 #' @export
-is_gram_positive <- function(x, ...) {
+is_gram_positive <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
-  grams <- mo_gramstain(x, language = NULL, ...)
-  "Gram-positive" == grams & !is.na(grams)
+  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
+
+  x.mo <- as.mo(x, language = language, ...)
+  metadata <- get_mo_failures_uncertainties_renamed()
+  grams <- mo_gramstain(x.mo, language = NULL)
+  load_mo_failures_uncertainties_renamed(metadata)
+  grams == "Gram-positive" & !is.na(grams)
 }
 
 #' @rdname mo_property
@@ -329,7 +339,7 @@ is_gram_positive <- function(x, ...) {
 mo_snomed <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   mo_validate(x = x, property = "snomed", language = language, ...)
 }
 
@@ -338,7 +348,7 @@ mo_snomed <- function(x, language = get_locale(), ...) {
 mo_ref <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   mo_validate(x = x, property = "ref", language = language, ...)
 }
 
@@ -347,7 +357,7 @@ mo_ref <- function(x, language = get_locale(), ...) {
 mo_authors <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- mo_validate(x = x, property = "ref", language = language, ...)
   # remove last 4 digits and presumably the comma and space that preceed them
   x[!is.na(x)] <- gsub(",? ?[0-9]{4}", "", x[!is.na(x)])
@@ -359,7 +369,7 @@ mo_authors <- function(x, language = get_locale(), ...) {
 mo_year <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- mo_validate(x = x, property = "ref", language = language, ...)
   # get last 4 digits
   x[!is.na(x)] <- gsub(".*([0-9]{4})$", "\\1", x[!is.na(x)])
@@ -371,7 +381,7 @@ mo_year <- function(x, language = get_locale(), ...) {
 mo_rank <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   mo_validate(x = x, property = "rank", language = language, ...)
 }
 
@@ -380,10 +390,10 @@ mo_rank <- function(x, language = get_locale(), ...) {
 mo_taxonomy <- function(x, language = get_locale(),  ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   result <- list(kingdom = mo_kingdom(x, language = language),
                  phylum = mo_phylum(x, language = language),
                  class = mo_class(x, language = language),
@@ -392,7 +402,7 @@ mo_taxonomy <- function(x, language = get_locale(),  ...) {
                  genus = mo_genus(x, language = language),
                  species = mo_species(x, language = language),
                  subspecies = mo_subspecies(x, language = language))
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
   result
 }
@@ -402,10 +412,10 @@ mo_taxonomy <- function(x, language = get_locale(),  ...) {
 mo_synonyms <- function(x, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   IDs <- mo_name(x = x, language = NULL)
   syns <- lapply(IDs, function(newname) {
     res <- sort(microorganisms.old[which(microorganisms.old$fullname_new == newname), "fullname"])
@@ -421,7 +431,7 @@ mo_synonyms <- function(x, language = get_locale(), ...) {
   } else {
     result <- unlist(syns)
   }
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
   result
 }
@@ -431,10 +441,10 @@ mo_synonyms <- function(x, language = get_locale(), ...) {
 mo_info <- function(x, language = get_locale(),  ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   info <- lapply(x, function(y)
     c(mo_taxonomy(y, language = language),
       list(synonyms = mo_synonyms(y),
@@ -447,7 +457,7 @@ mo_info <- function(x, language = get_locale(),  ...) {
   } else {
     result <- info[[1L]]
   }
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
   result
 }
@@ -458,11 +468,11 @@ mo_url <- function(x, open = FALSE, language = get_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(open, allow_class = "logical", has_length = 1)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   mo <- as.mo(x = x, language = language, ... = ...)
   mo_names <- mo_name(mo)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   df <- data.frame(mo, stringsAsFactors = FALSE) %pm>%
     pm_left_join(pm_select(microorganisms, mo, source, species_id), by = "mo")
   df$url <- ifelse(df$source == "CoL",
@@ -472,14 +482,14 @@ mo_url <- function(x, open = FALSE, language = get_locale(), ...) {
                           NA_character_))
   u <- df$url
   names(u) <- mo_names
-  
+
   if (open == TRUE) {
     if (length(u) > 1) {
       warning("only the first URL will be opened, as `browseURL()` only suports one string.")
     }
     utils::browseURL(u[1L])
   }
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
   u
 }
@@ -491,18 +501,18 @@ mo_property <- function(x, property = "fullname", language = get_locale(), ...)
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(property, allow_class = "character", has_length = 1, is_in = colnames(microorganisms))
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   translate_AMR(mo_validate(x = x, property = property, language = language, ...), language = language, only_unknown = TRUE)
 }
 
 mo_validate <- function(x, property, language, ...) {
   check_dataset_integrity()
-  
+
   if (tryCatch(all(x[!is.na(x)] %in% MO_lookup$mo) & length(list(...)) == 0, error = function(e) FALSE)) {
     # special case for mo_* functions where class is already <mo>
     return(MO_lookup[match(x, MO_lookup$mo), property, drop = TRUE])
   }
-  
+
   dots <- list(...)
   Becker <- dots$Becker
   if (is.null(Becker)) {
@@ -512,14 +522,14 @@ mo_validate <- function(x, property, language, ...) {
   if (is.null(Lancefield)) {
     Lancefield <- FALSE
   }
-  
+
   # try to catch an error when inputting an invalid parameter
   # so the 'call.' can be set to FALSE
   tryCatch(x[1L] %in% MO_lookup[1, property, drop = TRUE],
            error = function(e) stop(e$message, call. = FALSE))
-  
-  if (is.mo(x) 
-      & !Becker %in% c(TRUE, "all") 
+
+  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
@@ -529,7 +539,7 @@ mo_validate <- function(x, property, language, ...) {
              | Lancefield %in% c(TRUE, "all")) {
     x <- exec_as.mo(x, property = property, language = language, ...)
   }
-  
+
   if (property == "mo") {
     return(to_class_mo(x))
   } else if (property == "snomed") {
diff --git a/docs/404.html b/docs/404.html
index fc139ae1..2b059ce4 100644
--- a/docs/404.html
+++ b/docs/404.html
@@ -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">1.4.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html
index a8efcc17..a59446e2 100644
--- a/docs/LICENSE-text.html
+++ b/docs/LICENSE-text.html
@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/articles/PCA.html b/docs/articles/PCA.html
index 8e55edd8..bff885c4 100644
--- a/docs/articles/PCA.html
+++ b/docs/articles/PCA.html
@@ -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">1.4.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -187,7 +187,8 @@
 
       
 
-      </header><script src="PCA_files/header-attrs-2.3/header-attrs.js"></script><script src="PCA_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
+      </header><script src="PCA_files/accessible-code-block-0.0.1/empty-anchor.js"></script><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>
@@ -210,9 +211,9 @@
 <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">
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://msberends.github.io/AMR">AMR</a></span>)
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org">dplyr</a></span>)
-<span class="fu"><a href="https://tibble.tidyverse.org/reference/glimpse.html">glimpse</a></span>(<span class="kw">example_isolates</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>
+<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>
 <span class="co"># Columns: 49</span>
 <span class="co"># $ date            &lt;date&gt; 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002…</span>
@@ -263,18 +264,17 @@
 <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>
-</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">
-<span class="kw">resistance_data</span> <span class="op">&lt;-</span> <span class="kw">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>(order = <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span>(<span class="kw">mo</span>),       <span class="co"># group on anything, like order</span>
-           genus = <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="kw">mo</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="kw">is.rsi</span>, <span class="kw">resistance</span>) <span class="op">%&gt;%</span> <span class="co"># then get resistance of all drugs</span>
-  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="kw">order</span>, <span class="kw">genus</span>, <span class="kw">AMC</span>, <span class="kw">CXM</span>, <span class="kw">CTX</span>, 
-         <span class="kw">CAZ</span>, <span class="kw">GEN</span>, <span class="kw">TOB</span>, <span class="kw">TMP</span>, <span class="kw">SXT</span>)      <span class="co"># and select only relevant columns</span>
+<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>
+  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">order</span>, <span class="va">genus</span>, <span class="va">AMC</span>, <span class="va">CXM</span>, <span class="va">CTX</span>, 
+         <span class="va">CAZ</span>, <span class="va">GEN</span>, <span class="va">TOB</span>, <span class="va">TMP</span>, <span class="va">SXT</span><span class="op">)</span>      <span class="co"># and select only relevant columns</span>
 
-<span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(<span class="kw">resistance_data</span>)
+<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>
@@ -284,46 +284,40 @@
 <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>
-</pre></div>
+<span class="co"># 6 Actinomycetales Rothia            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">
-<span class="kw">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span>(<span class="kw">resistance_data</span>)
+<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.</span>
-<span class="co">#       Total observations available: 7.</span>
-</pre></div>
+<span class="co">#       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">
-<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(<span class="kw">pca_result</span>)
+<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"># 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>
-</pre></div>
+<span class="co"># Cumulative Proportion  0.580 0.9331 0.98012 0.99449 0.99988 1.00000 1.000e+00</span></pre></div>
 <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">
-<span class="fu"><a href="https://rdrr.io/r/stats/biplot.html">biplot</a></span>(<span class="kw">pca_result</span>)
-</pre></div>
+<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">
-<span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span>(<span class="kw">pca_result</span>)
-</pre></div>
+<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">
-<span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span>(<span class="kw">pca_result</span>, ellipse = <span class="fl">TRUE</span>) <span class="op">+</span>
-  <span class="kw">ggplot2</span>::<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span>(title = <span class="st">"An AMR/PCA biplot!"</span>)
-</pre></div>
+<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>
@@ -343,7 +337,7 @@
 </div>
 
 <div class="pkgdown">
-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
 </div>
 
       </footer>
diff --git a/docs/articles/PCA_files/anchor-sections-1.0/anchor-sections.css b/docs/articles/PCA_files/anchor-sections-1.0/anchor-sections.css
new file mode 100644
index 00000000..07aee5fc
--- /dev/null
+++ b/docs/articles/PCA_files/anchor-sections-1.0/anchor-sections.css
@@ -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;}
diff --git a/docs/articles/PCA_files/anchor-sections-1.0/anchor-sections.js b/docs/articles/PCA_files/anchor-sections-1.0/anchor-sections.js
new file mode 100644
index 00000000..570f99a0
--- /dev/null
+++ b/docs/articles/PCA_files/anchor-sections-1.0/anchor-sections.js
@@ -0,0 +1,33 @@
+// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
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+
+  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
+
+  // Do nothing if sections are already anchored
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+    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 === '') {
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+    }
+    let anchor = document.createElement('a');
+    anchor.href = '#' + id;
+    anchor.classList = ['anchor-section'];
+    x.classList.add('hasAnchor');
+    x.appendChild(anchor);
+  });
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diff --git a/docs/articles/SPSS.html b/docs/articles/SPSS.html
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       </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">1.4.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -187,13 +187,14 @@
 
       
 
-      </header><script src="SPSS_files/header-attrs-2.3/header-attrs.js"></script><script src="SPSS_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
+      </header><script src="SPSS_files/accessible-code-block-0.0.1/empty-anchor.js"></script><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">08 October 2020</h4>
+            <h4 class="date">26 October 2020</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>
@@ -249,38 +250,37 @@
 <p>To demonstrate the first point:</p>
 <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="fl">0.125</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>
-<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span>(<span class="st">"testvalue"</span>)
+<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span><span class="op">(</span><span class="st">"testvalue"</span><span class="op">)</span>
 <span class="co"># Class &lt;mic&gt;</span>
 <span class="co"># [1] &lt;NA&gt;</span>
 
 <span class="co"># the Gram stain is avaiable for all bacteria:</span>
-<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>)
+<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
 <span class="co"># [1] "Gram-negative"</span>
 
 <span class="co"># Klebsiella is intrinsic resistant to amoxicllin, according to EUCAST:</span>
-<span class="kw">klebsiella_test</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(mo = <span class="st">"klebsiella"</span>, 
-                              amox = <span class="st">"S"</span>,
-                              stringsAsFactors = <span class="fl">FALSE</span>)
-<span class="kw">klebsiella_test</span> <span class="co"># (our original data)</span>
+<span class="va">klebsiella_test</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="st">"klebsiella"</span>, 
+                              amox <span class="op">=</span> <span class="st">"S"</span>,
+                              stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
+<span class="va">klebsiella_test</span> <span class="co"># (our original data)</span>
 <span class="co">#           mo amox</span>
 <span class="co"># 1 klebsiella    S</span>
-<span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span>(<span class="kw">klebsiella_test</span>, info = <span class="fl">FALSE</span>) <span class="co"># (the edited data by EUCAST rules)</span>
+<span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">klebsiella_test</span>, info <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span> <span class="co"># (the edited data by EUCAST rules)</span>
 <span class="co">#           mo amox</span>
 <span class="co"># 1 klebsiella    R</span>
 
 <span class="co"># hundreds of trade names can be translated to a name, trade name or an ATC code:</span>
-<span class="fu"><a href="../reference/ab_property.html">ab_name</a></span>(<span class="st">"floxapen"</span>)
+<span class="fu"><a href="../reference/ab_property.html">ab_name</a></span><span class="op">(</span><span class="st">"floxapen"</span><span class="op">)</span>
 <span class="co"># [1] "Flucloxacillin"</span>
-<span class="fu"><a href="../reference/ab_property.html">ab_tradenames</a></span>(<span class="st">"floxapen"</span>)
+<span class="fu"><a href="../reference/ab_property.html">ab_tradenames</a></span><span class="op">(</span><span class="st">"floxapen"</span><span class="op">)</span>
 <span class="co"># [1] "floxacillin"          "floxapen"             "floxapen sodium salt"</span>
 <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="st">"floxapen"</span>)
-<span class="co"># [1] "J01CF05"</span>
-</pre></div>
+<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></pre></div>
 </div>
 <div id="import-data-from-spsssasstata" class="section level2">
 <h2 class="hasAnchor">
@@ -294,10 +294,10 @@
 <p>If additional packages are needed, RStudio will ask you if they should be installed on beforehand.</p>
 <p>In the the window that opens, you can define all options (parameters) that should be used for import and you’re ready to go:</p>
 <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>If you want named variables to be imported as factors so it resembles SPSS more, use <code>as_factor()</code>.</p>
 <p>The difference is this:</p>
 <div class="sourceCode" id="cb2"><pre class="downlit">
-<span class="kw">SPSS_data</span>
+<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>
@@ -313,7 +313,7 @@
 <span class="co"># 10 10018 0         1              66.6</span>
 <span class="co"># # … with 4,193 more rows</span>
 
-<span class="fu">as_factor</span>(<span class="kw">SPSS_data</span>)
+<span class="fu">as_factor</span><span class="op">(</span><span class="va">SPSS_data</span><span class="op">)</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;fct&gt;  &lt;fct&gt;      &lt;dbl&gt;</span>
@@ -327,8 +327,7 @@
 <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>
-</pre></div>
+<span class="co"># # … with 4,193 more rows</span></pre></div>
 </div>
 <div id="base-r" class="section level3">
 <h3 class="hasAnchor">
@@ -336,10 +335,9 @@
 <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">
 <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="st">"haven"</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="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="http://haven.tidyverse.org">haven</a></span>) 
-</pre></div>
+<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va">haven</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">
@@ -347,23 +345,21 @@
 <p>To read files from SPSS into R:</p>
 <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>(file = <span class="st">"path/to/file"</span>)
+<span class="fu">read_spss</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>(file = <span class="st">"path/to/file"</span>)
+<span class="fu">read_sav</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>(file = <span class="st">"path/to/file"</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>
+<span class="fu">read_por</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>as_factor()</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">
 <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>(data = <span class="kw">yourdata</span>, path = <span class="st">"path/to/file"</span>)
+<span class="fu">write_sav</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>(data = <span class="kw">yourdata</span>, path = <span class="st">"path/to/file"</span>, compress = <span class="fl">TRUE</span>)
-</pre></div>
+<span class="fu">write_sav</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">
@@ -371,20 +367,18 @@
 <p>To read files from SAS into R:</p>
 <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>(data_file = <span class="st">"path/to/file"</span>, catalog_file = <span class="kw">NULL</span>)
+<span class="fu">read_sas</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>(file = <span class="st">"path/to/file"</span>)
-</pre></div>
+<span class="fu">read_xpt</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">
 <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>(data = <span class="kw">yourdata</span>, path = <span class="st">"path/to/file"</span>)
+<span class="fu">write_sas</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>(data = <span class="kw">yourdata</span>, path = <span class="st">"path/to/file"</span>, version = <span class="fl">8</span>)
-</pre></div>
+<span class="fu">write_xpt</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">
@@ -392,17 +386,15 @@
 <p>To read files from Stata into R:</p>
 <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>(file = <span class="st">"/path/to/file"</span>)
+<span class="fu">read_stata</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>(file = <span class="st">"/path/to/file"</span>)
-</pre></div>
+<span class="fu">read_dta</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">
 <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>(data = <span class="kw">yourdata</span>, path = <span class="st">"/path/to/file"</span>, version = <span class="fl">14</span>)
-</pre></div>
+<span class="fu">write_dta</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>
@@ -423,7 +415,7 @@
 </div>
 
 <div class="pkgdown">
-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
 </div>
 
       </footer>
diff --git a/docs/articles/SPSS_files/anchor-sections-1.0/anchor-sections.css b/docs/articles/SPSS_files/anchor-sections-1.0/anchor-sections.css
new file mode 100644
index 00000000..07aee5fc
--- /dev/null
+++ b/docs/articles/SPSS_files/anchor-sections-1.0/anchor-sections.css
@@ -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;}
diff --git a/docs/articles/SPSS_files/anchor-sections-1.0/anchor-sections.js b/docs/articles/SPSS_files/anchor-sections-1.0/anchor-sections.js
new file mode 100644
index 00000000..570f99a0
--- /dev/null
+++ b/docs/articles/SPSS_files/anchor-sections-1.0/anchor-sections.js
@@ -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);
+  });
+});
diff --git a/docs/articles/WHONET.html b/docs/articles/WHONET.html
index c2a7e97a..273f3e19 100644
--- a/docs/articles/WHONET.html
+++ b/docs/articles/WHONET.html
@@ -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">1.4.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -187,7 +187,8 @@
 
       
 
-      </header><script src="WHONET_files/header-attrs-2.3/header-attrs.js"></script><script src="WHONET_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
+      </header><script src="WHONET_files/accessible-code-block-0.0.1/empty-anchor.js"></script><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>
@@ -206,9 +207,8 @@
 <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">
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://readxl.tidyverse.org">readxl</a></span>)
-<span class="kw">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html">read_excel</a></span>(path = <span class="st">"path/to/your/file.xlsx"</span>)
-</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://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">
@@ -216,11 +216,10 @@
 <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">
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org">dplyr</a></span>)   <span class="co"># part of tidyverse</span>
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="http://ggplot2.tidyverse.org">ggplot2</a></span>) <span class="co"># part of tidyverse</span>
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://msberends.github.io/AMR">AMR</a></span>)     <span class="co"># this package</span>
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://github.com/msberends/cleaner">cleaner</a></span>) <span class="co"># to create frequency tables</span>
-</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>   <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></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>
@@ -228,19 +227,17 @@
 </ul>
 <div class="sourceCode" id="cb3"><pre class="downlit">
 <span class="co"># transform variables</span>
-<span class="kw">data</span> <span class="op">&lt;-</span> <span class="kw">WHONET</span> <span class="op">%&gt;%</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>(mo = <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="kw">Organism</span>)) <span class="op">%&gt;%</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="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="kw">AMP_ND10</span><span class="op">:</span><span class="kw">CIP_EE</span>), <span class="kw">as.rsi</span>)
-</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">
 <span class="co"># our newly created `mo` variable, put in the mo_name() function</span>
-<span class="kw">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="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="kw">mo</span>), nmax = <span class="fl">10</span>)
-</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="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>
@@ -344,15 +341,16 @@ Longest: 40</p>
 <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="kw">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="kw">AMC_ND2</span>)
-</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>
 Levels: 3: S &lt; I &lt; R<br>
 Available: 481 (96.2%, NA: 19 = 3.8%)<br>
 Unique: 3</p>
-<p>%SI: 78.59%</p>
+<p>Drug: Amoxicillin/clavulanic acid (AMC, J01CR02)<br>
+Drug group: Beta-lactams/penicillins<br>
+%SI: 78.59%</p>
 <table class="table">
 <thead><tr class="header">
 <th align="left"></th>
@@ -395,11 +393,10 @@ Unique: 3</p>
 <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">
-<span class="kw">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="kw">Country</span>) <span class="op">%&gt;%</span>
-  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="kw">Country</span>, <span class="kw">AMP_ND2</span>, <span class="kw">AMC_ED20</span>, <span class="kw">CAZ_ED10</span>, <span class="kw">CIP_ED5</span>) <span class="op">%&gt;%</span>
-  <span class="fu"><a href="../reference/ggplot_rsi.html">ggplot_rsi</a></span>(translate_ab = <span class="st">'ab'</span>, facet = <span class="st">"Country"</span>, datalabels = <span class="fl">FALSE</span>)
-</pre></div>
+<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></pre></div>
 <p><img src="WHONET_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
 </div>
   </div>
@@ -417,7 +414,7 @@ Unique: 3</p>
 </div>
 
 <div class="pkgdown">
-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
 </div>
 
       </footer>
diff --git a/docs/articles/WHONET_files/anchor-sections-1.0/anchor-sections.css b/docs/articles/WHONET_files/anchor-sections-1.0/anchor-sections.css
new file mode 100644
index 00000000..07aee5fc
--- /dev/null
+++ b/docs/articles/WHONET_files/anchor-sections-1.0/anchor-sections.css
@@ -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;}
diff --git a/docs/articles/WHONET_files/anchor-sections-1.0/anchor-sections.js b/docs/articles/WHONET_files/anchor-sections-1.0/anchor-sections.js
new file mode 100644
index 00000000..570f99a0
--- /dev/null
+++ b/docs/articles/WHONET_files/anchor-sections-1.0/anchor-sections.js
@@ -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);
+  });
+});
diff --git a/docs/articles/WHONET_files/figure-html/unnamed-chunk-7-1.png b/docs/articles/WHONET_files/figure-html/unnamed-chunk-7-1.png
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diff --git a/docs/articles/benchmarks.html b/docs/articles/benchmarks.html
index 9cd704c7..b8c3637f 100644
--- a/docs/articles/benchmarks.html
+++ b/docs/articles/benchmarks.html
@@ -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">1.4.0.9000</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -187,7 +187,8 @@
 
       
 
-      </header><script src="benchmarks_files/header-attrs-2.4/header-attrs.js"></script><script src="benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
+      </header><script src="benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js"></script><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>
@@ -227,20 +228,34 @@
   times <span class="op">=</span> <span class="fl">10</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")  12.0  13.0  25.0   15.0  40.0  43    10</span>
-<span class="co">#                          as.mo("stau") 210.0 220.0 230.0  230.0 250.0 260    10</span>
-<span class="co">#                          as.mo("STAU") 210.0 210.0 230.0  250.0 250.0 260    10</span>
-<span class="co">#                        as.mo("staaur")  12.0  13.0  24.0   14.0  41.0  42    10</span>
-<span class="co">#                        as.mo("STAAUR")  13.0  13.0  22.0   14.0  39.0  42    10</span>
-<span class="co">#                     as.mo("S. aureus")  27.0  30.0  42.0   41.0  54.0  61    10</span>
-<span class="co">#                      as.mo("S aureus")  24.0  29.0  45.0   43.0  60.0  66    10</span>
-<span class="co">#         as.mo("Staphylococcus aureus")   2.1   2.5   4.9    2.5   2.9  26    10</span>
-<span class="co">#  as.mo("Staphylococcus aureus (MRSA)") 820.0 860.0 880.0  880.0 900.0 970    10</span>
-<span class="co">#       as.mo("Sthafilokkockus aaureuz") 330.0 340.0 370.0  370.0 390.0 420    10</span>
-<span class="co">#                          as.mo("MRSA")  11.0  13.0  22.0   14.0  41.0  44    10</span>
-<span class="co">#                          as.mo("VISA")  21.0  22.0  48.0   47.0  51.0 140    10</span>
-<span class="co">#                          as.mo("VRSA")  19.0  20.0  23.0   21.0  22.0  47    10</span></pre></div>
+<span class="co">#                                   expr    min     lq   mean median     uq  max</span>
+<span class="co">#                           as.mo("sau")   26.0   26.0   50.0   26.0   26.0  180</span>
+<span class="co">#                          as.mo("stau")  430.0  430.0  470.0  440.0  490.0  630</span>
+<span class="co">#                          as.mo("STAU")  430.0  440.0  470.0  500.0  500.0  500</span>
+<span class="co">#                        as.mo("staaur")   26.0   26.0   32.0   26.0   26.0   76</span>
+<span class="co">#                        as.mo("STAAUR")   26.0   26.0   44.0   26.0   81.0   83</span>
+<span class="co">#                     as.mo("S. aureus")   60.0   60.0   77.0   61.0  110.0  120</span>
+<span class="co">#                      as.mo("S aureus")   60.0   61.0   94.0  110.0  120.0  120</span>
+<span class="co">#         as.mo("Staphylococcus aureus")    4.1    4.1    9.6    4.1    4.2   59</span>
+<span class="co">#  as.mo("Staphylococcus aureus (MRSA)") 2200.0 2200.0 2200.0 2200.0 2300.0 2300</span>
+<span class="co">#       as.mo("Sthafilokkockus aaureuz")  760.0  800.0  810.0  800.0  810.0  840</span>
+<span class="co">#                          as.mo("MRSA")   26.0   26.0   37.0   26.0   26.0   83</span>
+<span class="co">#                          as.mo("VISA")   42.0   42.0   59.0   42.0   92.0   97</span>
+<span class="co">#                          as.mo("VRSA")   42.0   42.0   68.0   67.0   92.0   97</span>
+<span class="co">#  neval</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span>
+<span class="co">#     10</span></pre></div>
 <p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="562.5"></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 100 milliseconds, this is only 10 input values per second. It is clear that accepted taxonomic names are extremely fast, but some variations can take up to 500-1000 times as much time.</p>
 <p>To improve performance, two important calculations take almost no time at all: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
@@ -270,8 +285,8 @@
 <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) 150 154  195    179 197 301    10</span></pre></div>
-<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.179 seconds. You only lose time on your unique input values.</p>
+<span class="co">#  mo_name(x) 308 326  399    331 370 676    10</span></pre></div>
+<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.331 seconds. You only lose time on your unique input values.</p>
 </div>
 <div id="precalculated-results" class="section level3">
 <h3 class="hasAnchor">
@@ -284,11 +299,11 @@
                          times <span class="op">=</span> <span class="fl">10</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  7.11  7.23  7.79   7.74  8.46  8.54    10</span>
-<span class="co">#     B 21.40 21.90 30.40  24.00 25.50 60.00    10</span>
-<span class="co">#     C  1.97  1.98  2.12   2.05  2.34  2.43    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 0.002 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>
+<span class="co">#  expr   min    lq  mean median    uq    max neval</span>
+<span class="co">#     A 16.20 16.20 18.60  17.90 18.90  28.00    10</span>
+<span class="co">#     B 50.90 51.10 57.70  51.20 53.10 108.00    10</span>
+<span class="co">#     C  3.58  3.72  4.03   4.06  4.14   4.91    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 0.0041 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">microbenchmark</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>,
@@ -301,15 +316,15 @@
                          times <span class="op">=</span> <span class="fl">10</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 1.33 1.57 1.70   1.69 1.83  2.18    10</span>
-<span class="co">#     B 1.62 1.67 5.34   1.70 2.15 36.90    10</span>
-<span class="co">#     C 1.43 1.55 1.64   1.59 1.70  2.06    10</span>
-<span class="co">#     D 1.29 1.44 1.53   1.55 1.66  1.70    10</span>
-<span class="co">#     E 1.31 1.58 1.68   1.65 1.71  2.11    10</span>
-<span class="co">#     F 1.54 1.61 1.80   1.67 1.86  2.57    10</span>
-<span class="co">#     G 1.52 1.62 1.73   1.71 1.77  2.04    10</span>
-<span class="co">#     H 1.40 1.55 1.70   1.65 1.92  2.03    10</span></pre></div>
+<span class="co">#  expr  min   lq mean median   uq  max neval</span>
+<span class="co">#     A 3.62 3.62 3.66   3.64 3.67 3.80    10</span>
+<span class="co">#     B 3.57 3.59 3.68   3.64 3.72 4.01    10</span>
+<span class="co">#     C 3.63 3.64 3.65   3.64 3.67 3.71    10</span>
+<span class="co">#     D 3.57 3.58 3.62   3.61 3.67 3.69    10</span>
+<span class="co">#     E 3.56 3.57 3.60   3.59 3.60 3.68    10</span>
+<span class="co">#     F 3.55 3.58 3.73   3.65 3.85 4.01    10</span>
+<span class="co">#     G 3.54 3.56 3.62   3.58 3.61 3.93    10</span>
+<span class="co">#     H 3.53 3.57 3.59   3.58 3.63 3.66    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 ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
 </div>
 <div id="results-in-other-languages" class="section level3">
@@ -336,14 +351,14 @@
                          times <span class="op">=</span> <span class="fl">100</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 14.20 14.66 20.04  15.14 16.90 58.67   100</span>
-<span class="co">#    de 17.15 17.85 24.30  18.27 20.00 59.17   100</span>
-<span class="co">#    nl 29.13 30.50 34.60  31.26 32.86 72.63   100</span>
-<span class="co">#    es 16.95 17.70 22.61  18.35 20.54 59.42   100</span>
-<span class="co">#    it 17.04 17.60 21.72  18.14 19.60 59.19   100</span>
-<span class="co">#    fr 16.82 17.52 21.71  18.05 19.63 61.06   100</span>
-<span class="co">#    pt 16.92 17.58 19.92  18.23 19.19 54.61   100</span></pre></div>
+<span class="co">#  expr   min    lq  mean median    uq    max neval</span>
+<span class="co">#    en 35.85 36.13 41.92  36.29 36.84 318.20   100</span>
+<span class="co">#    de 42.37 42.67 45.11  42.91 43.19  95.04   100</span>
+<span class="co">#    nl 70.13 70.65 75.92  70.95 71.50 140.20   100</span>
+<span class="co">#    es 42.16 42.46 46.88  42.64 43.20  95.37   100</span>
+<span class="co">#    it 41.85 42.24 46.84  42.40 42.84  95.92   100</span>
+<span class="co">#    fr 42.13 42.53 48.41  42.71 43.27  95.21   100</span>
+<span class="co">#    pt 42.25 42.47 48.56  42.71 43.12  96.60   100</span></pre></div>
 <p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
 </div>
   </div>
diff --git a/docs/articles/benchmarks_files/anchor-sections-1.0/anchor-sections.css b/docs/articles/benchmarks_files/anchor-sections-1.0/anchor-sections.css
new file mode 100644
index 00000000..07aee5fc
--- /dev/null
+++ b/docs/articles/benchmarks_files/anchor-sections-1.0/anchor-sections.css
@@ -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;}
diff --git a/docs/articles/benchmarks_files/anchor-sections-1.0/anchor-sections.js b/docs/articles/benchmarks_files/anchor-sections-1.0/anchor-sections.js
new file mode 100644
index 00000000..570f99a0
--- /dev/null
+++ b/docs/articles/benchmarks_files/anchor-sections-1.0/anchor-sections.js
@@ -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);
+  });
+});
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diff --git a/docs/articles/index.html b/docs/articles/index.html
index 938b71e1..5993fb35 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/articles/resistance_predict.html b/docs/articles/resistance_predict.html
index 204a89e6..a7866c12 100644
--- a/docs/articles/resistance_predict.html
+++ b/docs/articles/resistance_predict.html
@@ -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">1.4.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -187,7 +187,8 @@
 
       
 
-      </header><script src="resistance_predict_files/header-attrs-2.3/header-attrs.js"></script><script src="resistance_predict_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
+      </header><script src="resistance_predict_files/accessible-code-block-0.0.1/empty-anchor.js"></script><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>
@@ -206,13 +207,12 @@
 <p>As with many uses in R, we need some additional packages for AMR 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">
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org">dplyr</a></span>)
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="http://ggplot2.tidyverse.org">ggplot2</a></span>)
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://msberends.github.io/AMR">AMR</a></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="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>
-</pre></div>
+<span class="co"># install.packages(c("tidyverse", "AMR"))</span></pre></div>
 </div>
 <div id="prediction-analysis" class="section level2">
 <h2 class="hasAnchor">
@@ -236,7 +236,7 @@
 <pre><code># NOTE: 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">
-<span class="kw">predict_TZP</span>
+<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>
@@ -266,36 +266,31 @@
 <span class="co"># 26 2027 0.41315710 0.3244399 0.5018743           NA         NA 0.41315710</span>
 <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>
-</pre></div>
+<span class="co"># 29 2030 0.48639359 0.3782932 0.5944939           NA         NA 0.48639359</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">
-<span class="fu"><a href="../reference/plot.html">plot</a></span>(<span class="kw">predict_TZP</span>)
-</pre></div>
+<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">
-<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(<span class="kw">predict_TZP</span>)
-</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><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">
 
 <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="kw">predict_TZP</span>, ribbon = <span class="fl">FALSE</span>)
-</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">
-<span class="kw">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="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="kw">mo</span>, language = <span class="kw">NULL</span>) <span class="op">==</span> <span class="st">"Gram-positive"</span>) <span class="op">%&gt;%</span>
-  <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(col_ab = <span class="st">"VAN"</span>, year_min = <span class="fl">2010</span>, info = <span class="fl">FALSE</span>, model = <span class="st">"binomial"</span>) <span class="op">%&gt;%</span> 
-  <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>()
-<span class="co"># NOTE: Using column `date` as input for `col_date`.</span>
-</pre></div>
+<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>
+<span class="co"># NOTE: Using column `date` as input for `col_date`.</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>
@@ -337,28 +332,26 @@
 </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">
-<span class="kw">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="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="kw">mo</span>, language = <span class="kw">NULL</span>) <span class="op">==</span> <span class="st">"Gram-positive"</span>) <span class="op">%&gt;%</span>
-  <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(col_ab = <span class="st">"VAN"</span>, year_min = <span class="fl">2010</span>, info = <span class="fl">FALSE</span>, model = <span class="st">"linear"</span>) <span class="op">%&gt;%</span> 
-  <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>()
-<span class="co"># NOTE: Using column `date` as input for `col_date`.</span>
-</pre></div>
+<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>
+<span class="co"># NOTE: Using column `date` as input for `col_date`.</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">
-<span class="kw">model</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html">attributes</a></span>(<span class="kw">predict_TZP</span>)<span class="op">$</span><span class="kw">model</span>
+<span class="va">model</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span>
 
-<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(<span class="kw">model</span>)<span class="op">$</span><span class="kw">family</span>
+<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">family</span>
 <span class="co"># </span>
 <span class="co"># Family: binomial </span>
 <span class="co"># Link function: logit</span>
 
-<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(<span class="kw">model</span>)<span class="op">$</span><span class="kw">coefficients</span>
+<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">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>
-</pre></div>
+<span class="co"># year           0.09883005  0.02295317  4.305725 1.664395e-05</span></pre></div>
 </div>
 </div>
   </div>
@@ -378,7 +371,7 @@
 </div>
 
 <div class="pkgdown">
-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
 </div>
 
       </footer>
diff --git a/docs/articles/resistance_predict_files/anchor-sections-1.0/anchor-sections.css b/docs/articles/resistance_predict_files/anchor-sections-1.0/anchor-sections.css
new file mode 100644
index 00000000..07aee5fc
--- /dev/null
+++ b/docs/articles/resistance_predict_files/anchor-sections-1.0/anchor-sections.css
@@ -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;}
diff --git a/docs/articles/resistance_predict_files/anchor-sections-1.0/anchor-sections.js b/docs/articles/resistance_predict_files/anchor-sections-1.0/anchor-sections.js
new file mode 100644
index 00000000..570f99a0
--- /dev/null
+++ b/docs/articles/resistance_predict_files/anchor-sections-1.0/anchor-sections.js
@@ -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')) {
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+  }
+
+  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;
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+    let anchor = document.createElement('a');
+    anchor.href = '#' + id;
+    anchor.classList = ['anchor-section'];
+    x.classList.add('hasAnchor');
+    x.appendChild(anchor);
+  });
+});
diff --git a/docs/articles/resistance_predict_files/figure-html/unnamed-chunk-4-1.png b/docs/articles/resistance_predict_files/figure-html/unnamed-chunk-4-1.png
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diff --git a/docs/articles/welcome_to_AMR.html b/docs/articles/welcome_to_AMR.html
index afb92eec..d02b2993 100644
--- a/docs/articles/welcome_to_AMR.html
+++ b/docs/articles/welcome_to_AMR.html
@@ -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">1.4.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -187,7 +187,8 @@
 
       
 
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+<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>
@@ -249,7 +250,7 @@
 </div>
 
 <div class="pkgdown">
-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
 </div>
 
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diff --git a/docs/articles/welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.css b/docs/articles/welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.css
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index 00000000..07aee5fc
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diff --git a/docs/articles/welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.js b/docs/articles/welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.js
new file mode 100644
index 00000000..570f99a0
--- /dev/null
+++ b/docs/articles/welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.js
@@ -0,0 +1,33 @@
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+
+  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);
+  });
+});
diff --git a/docs/authors.html b/docs/authors.html
index 5f89f267..cddf97b3 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/index.html b/docs/index.html
index 6880b98b..efafa8fa 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -43,7 +43,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/news/index.html b/docs/news/index.html
index 520cbd93..47933806 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -236,20 +236,20 @@
       <small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
     </div>
 
-    <div id="amr-1409007" class="section level1">
-<h1 class="page-header" data-toc-text="1.4.0.9007">
-<a href="#amr-1409007" class="anchor"></a>AMR 1.4.0.9007<small> Unreleased </small>
+    <div id="amr-1409008" class="section level1">
+<h1 class="page-header" data-toc-text="1.4.0.9008">
+<a href="#amr-1409008" class="anchor"></a>AMR 1.4.0.9008<small> Unreleased </small>
 </h1>
-<div id="last-updated-21-october-2020" class="section level2">
+<div id="last-updated-26-october-2020" class="section level2">
 <h2 class="hasAnchor">
-<a href="#last-updated-21-october-2020" class="anchor"></a><small>Last updated: 21 October 2020</small>
+<a href="#last-updated-26-october-2020" class="anchor"></a><small>Last updated: 26 October 2020</small>
 </h2>
 <div id="new" class="section level3">
 <h3 class="hasAnchor">
 <a href="#new" class="anchor"></a>New</h3>
 <ul>
 <li>Functions <code><a href="../reference/mo_property.html">is_gram_negative()</a></code> and <code><a href="../reference/mo_property.html">is_gram_positive()</a></code> as wrappers around <code><a href="../reference/mo_property.html">mo_gramstain()</a></code>. They always return <code>TRUE</code> or <code>FALSE</code>, thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</li>
-<li>Functions <code>%not_like%</code> and <code>%like_perl%</code> as wrappers around <code><a href="../reference/like.html">%like%</a></code>.</li>
+<li>Functions <code><a href="../reference/like.html">%not_like%</a></code> and <code><a href="../reference/like.html">%not_like_case%</a></code> as wrappers around <code><a href="../reference/like.html">%like%</a></code> and <code><a href="../reference/like.html">%like_case%</a></code>. The RStudio addin to insert the text " %like% " as provided in this package now iterates over all like variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert <code><a href="../reference/like.html">%like%</a></code> and by pressing it again it will be replaced with <code><a href="../reference/like.html">%not_like%</a></code>, etc.</li>
 </ul>
 </div>
 <div id="changed" class="section level3">
@@ -260,12 +260,14 @@
 <li>Deprecated function <code><a href="../reference/AMR-deprecated.html">p_symbol()</a></code> that not really fits the scope of this package. It will be removed in a future version. See <a href="https://github.com/msberends/AMR/blob/v1.4.0/R/p_symbol.R">here</a> for the source code to preserve it.</li>
 <li>Better determination of disk zones and MIC values when running <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on a data.frame</li>
 <li>Updated coagulase-negative staphylococci with Becker <em>et al.</em> 2020 (PMID 32056452), meaning that the species <em>S. argensis</em>, <em>S. caeli</em>, <em>S. debuckii</em>, <em>S. edaphicus</em> and <em>S. pseudoxylosus</em> are now all considered CoNS</li>
+<li>Fix for using parameter <code>reference_df</code> in <code><a href="../reference/as.mo.html">as.mo()</a></code> and <code>mo_*()</code> functions that contain old microbial codes (from previous package versions)</li>
 </ul>
 </div>
 <div id="other" class="section level3">
 <h3 class="hasAnchor">
 <a href="#other" class="anchor"></a>Other</h3>
 <ul>
+<li>All messages thrown by this package now have correct line breaks</li>
 <li>More extensive unit tests</li>
 </ul>
 </div>
@@ -468,7 +470,7 @@
 <p>Making this package independent of especially the tidyverse (e.g. packages <code>dplyr</code> and <code>tidyr</code>) tremendously increases sustainability on the long term, since tidyverse functions change quite often. Good for users, but hard for package maintainers. Most of our functions are replaced with versions that only rely on base R, which keeps this package fully functional for many years to come, without requiring a lot of maintenance to keep up with other packages anymore. Another upside it that this package can now be used with all versions of R since R-3.0.0 (April 2013). Our package is being used in settings where the resources are very limited. Fewer dependencies on newer software is helpful for such settings.</p>
 <p>Negative effects of this change are:</p>
 <ul>
-<li>Function <code>freq()</code> that was borrowed from the <code>cleaner</code> package was removed. Use <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">cleaner::freq()</a></code>, or run <code><a href="https://github.com/msberends/cleaner">library("cleaner")</a></code> before you use <code>freq()</code>.</li>
+<li>Function <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> that was borrowed from the <code>cleaner</code> package was removed. Use <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">cleaner::freq()</a></code>, or run <code><a href="https://github.com/msberends/cleaner">library("cleaner")</a></code> before you use <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code>.</li>
 <li><del>Printing values of class <code>mo</code> or <code>rsi</code> in a tibble will no longer be in colour and printing <code>rsi</code> in a tibble will show the class <code>&lt;ord&gt;</code>, not <code>&lt;rsi&gt;</code> anymore. This is purely a visual effect.</del></li>
 <li><del>All functions from the <code>mo_*</code> family (like <code><a href="../reference/mo_property.html">mo_name()</a></code> and <code><a href="../reference/mo_property.html">mo_gramstain()</a></code>) are noticeably slower when running on hundreds of thousands of rows.</del></li>
 <li>For developers: classes <code>mo</code> and <code>ab</code> now both also inherit class <code>character</code>, to support any data transformation. This change invalidates code that checks for class length == 1.</li>
@@ -796,7 +798,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="co">#&gt; invalid microorganism code, NA generated</span></pre></div>
 <p>This is important, because a value like <code>"testvalue"</code> could never be understood by e.g. <code><a href="../reference/mo_property.html">mo_name()</a></code>, although the class would suggest a valid microbial code.</p>
 </li>
-<li><p>Function <code>freq()</code> has moved to a new package, <a href="https://github.com/msberends/clean"><code>clean</code></a> (<a href="https://cran.r-project.org/package=clean">CRAN link</a>), since creating frequency tables actually does not fit the scope of this package. The <code>freq()</code> function still works, since it is re-exported from the <code>clean</code> package (which will be installed automatically upon updating this <code>AMR</code> package).</p></li>
+<li><p>Function <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> has moved to a new package, <a href="https://github.com/msberends/clean"><code>clean</code></a> (<a href="https://cran.r-project.org/package=clean">CRAN link</a>), since creating frequency tables actually does not fit the scope of this package. The <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> function still works, since it is re-exported from the <code>clean</code> package (which will be installed automatically upon updating this <code>AMR</code> package).</p></li>
 <li><p>Renamed data set <code>septic_patients</code> to <code>example_isolates</code></p></li>
 </ul>
 </div>
@@ -1059,7 +1061,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li>The <code><a href="../reference/age.html">age()</a></code> function gained a new parameter <code>exact</code> to determine ages with decimals</li>
 <li>Removed deprecated functions <code>guess_mo()</code>, <code>guess_atc()</code>, <code>EUCAST_rules()</code>, <code>interpretive_reading()</code>, <code><a href="../reference/as.rsi.html">rsi()</a></code>
 </li>
-<li>Frequency tables (<code>freq()</code>):
+<li>Frequency tables (<code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code>):
 <ul>
 <li><p>speed improvement for microbial IDs</p></li>
 <li><p>fixed factor level names for R Markdown</p></li>
@@ -1068,12 +1070,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <p>support for boxplots:</p>
 <div class="sourceCode" id="cb20"><pre class="downlit">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span> 
-  <span class="fu">freq</span><span class="op">(</span><span class="va">age</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="va">age</span><span class="op">)</span> <span class="op">%&gt;%</span> 
   <span class="fu"><a href="https://rdrr.io/r/graphics/boxplot.html">boxplot</a></span><span class="op">(</span><span class="op">)</span>
 <span class="co"># grouped boxplots:</span>
 <span class="va">septic_patients</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">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span> 
-  <span class="fu">freq</span><span class="op">(</span><span class="va">age</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="va">age</span><span class="op">)</span> <span class="op">%&gt;%</span>
   <span class="fu"><a href="https://rdrr.io/r/graphics/boxplot.html">boxplot</a></span><span class="op">(</span><span class="op">)</span></pre></div>
 </li>
 </ul>
@@ -1083,7 +1085,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li>Added ceftazidim intrinsic resistance to <em>Streptococci</em>
 </li>
 <li>Changed default settings for <code><a href="../reference/age_groups.html">age_groups()</a></code>, to let groups of fives and tens end with 100+ instead of 120+</li>
-<li>Fix for <code>freq()</code> for when all values are <code>NA</code>
+<li>Fix for <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> for when all values are <code>NA</code>
 </li>
 <li>Fix for <code><a href="../reference/first_isolate.html">first_isolate()</a></code> for when dates are missing</li>
 <li>Improved speed of <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code>
@@ -1315,7 +1317,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 </ul>
 </li>
-<li>Frequency tables (<code>freq()</code> function):
+<li>Frequency tables (<code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> function):
 <ul>
 <li>
 <p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
@@ -1324,15 +1326,15 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="co"># OLD WAY</span>
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span>
   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</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="fu">freq</span><span class="op">(</span><span class="va">genus</span><span class="op">)</span>
+  <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">genus</span><span class="op">)</span>
 <span class="co"># NEW WAY</span>
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span> 
-  <span class="fu">freq</span><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="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_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span>
 
 <span class="co"># Even supports grouping variables:</span>
 <span class="va">septic_patients</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">gender</span><span class="op">)</span> <span class="op">%&gt;%</span> 
-  <span class="fu">freq</span><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></pre></div>
+  <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_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span></pre></div>
 </li>
 <li><p>Header info is now available as a list, with the <code>header</code> function</p></li>
 <li><p>The parameter <code>header</code> is now set to <code>TRUE</code> at default, even for markdown</p></li>
@@ -1414,23 +1416,23 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Using <code>portion_*</code> functions now throws a warning when total available isolate is below parameter <code>minimum</code></p></li>
 <li><p>Functions <code>as.mo</code>, <code>as.rsi</code>, <code>as.mic</code>, <code>as.atc</code> and <code>freq</code> will not set package name as attribute anymore</p></li>
 <li>
-<p>Frequency tables - <code>freq()</code>:</p>
+<p>Frequency tables - <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code>:</p>
 <ul>
 <li>
 <p>Support for grouping variables, test with:</p>
 <div class="sourceCode" id="cb32"><pre class="downlit">
 <span class="va">septic_patients</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">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span> 
-  <span class="fu">freq</span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></pre></div>
+  <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></pre></div>
 </li>
 <li>
 <p>Support for (un)selecting columns:</p>
 <div class="sourceCode" id="cb33"><pre class="downlit">
 <span class="va">septic_patients</span> <span class="op">%&gt;%</span> 
-  <span class="fu">freq</span><span class="op">(</span><span class="va">hospital_id</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="va">hospital_id</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="op">-</span><span class="va">count</span>, <span class="op">-</span><span class="va">cum_count</span><span class="op">)</span> <span class="co"># only get item, percent, cum_percent</span></pre></div>
 </li>
-<li><p>Check for <code><a href="https://hms.tidyverse.org/reference/Deprecated.html">hms::is.hms</a></code></p></li>
+<li><p>Check for <code><a href="https://rdrr.io/pkg/hms/man/Deprecated.html">hms::is.hms</a></code></p></li>
 <li><p>Now prints in markdown at default in non-interactive sessions</p></li>
 <li><p>No longer adds the factor level column and sorts factors on count again</p></li>
 <li><p>Support for class <code>difftime</code></p></li>
@@ -1445,7 +1447,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Removed diacritics from all authors (columns <code>microorganisms$ref</code> and <code>microorganisms.old$ref</code>) to comply with CRAN policy to only allow ASCII characters</p></li>
 <li><p>Fix for <code>mo_property</code> not working properly</p></li>
 <li><p>Fix for <code>eucast_rules</code> where some Streptococci would become ceftazidime R in EUCAST rule 4.5</p></li>
-<li><p>Support for named vectors of class <code>mo</code>, useful for <code>top_freq()</code></p></li>
+<li><p>Support for named vectors of class <code>mo</code>, useful for <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">top_freq()</a></code></p></li>
 <li><p><code>ggplot_rsi</code> and <code>scale_y_percent</code> have <code>breaks</code> parameter</p></li>
 <li>
 <p>AI improvements for <code>as.mo</code>:</p>
@@ -1606,12 +1608,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <p>Support for types (classes) list and matrix for <code>freq</code></p>
 <div class="sourceCode" id="cb40"><pre class="downlit">
 <span class="va">my_matrix</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/with.html">with</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="fu"><a href="https://rdrr.io/r/base/matrix.html">matrix</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="va">age</span>, <span class="va">gender</span><span class="op">)</span>, ncol <span class="op">=</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span>
-<span class="fu">freq</span><span class="op">(</span><span class="va">my_matrix</span><span class="op">)</span></pre></div>
+<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">my_matrix</span><span class="op">)</span></pre></div>
 <p>For lists, subsetting is possible:</p>
 <div class="sourceCode" id="cb41"><pre class="downlit">
 <span class="va">my_list</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span>age <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">age</span>, gender <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">gender</span><span class="op">)</span>
-<span class="va">my_list</span> <span class="op">%&gt;%</span> <span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span>
-<span class="va">my_list</span> <span class="op">%&gt;%</span> <span class="fu">freq</span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></pre></div>
+<span class="va">my_list</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">age</span><span class="op">)</span>
+<span class="va">my_list</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">gender</span><span class="op">)</span></pre></div>
 </li>
 </ul>
 </div>
@@ -1685,13 +1687,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>A vignette to explain its usage</li>
 <li>Support for <code>rsi</code> (antimicrobial resistance) to use as input</li>
-<li>Support for <code>table</code> to use as input: <code>freq(table(x, y))</code>
+<li>Support for <code>table</code> to use as input: <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq(table(x, y))</a></code>
 </li>
 <li>Support for existing functions <code>hist</code> and <code>plot</code> to use a frequency table as input: <code><a href="https://rdrr.io/r/graphics/hist.html">hist(freq(df$age))</a></code>
 </li>
 <li>Support for <code>as.vector</code>, <code>as.data.frame</code>, <code>as_tibble</code> and <code>format</code>
 </li>
-<li>Support for quasiquotation: <code>freq(mydata, mycolumn)</code> is the same as <code>mydata %&gt;% freq(mycolumn)</code>
+<li>Support for quasiquotation: <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq(mydata, mycolumn)</a></code> is the same as <code>mydata %&gt;% freq(mycolumn)</code>
 </li>
 <li>Function <code>top_freq</code> function to return the top/below <em>n</em> items as vector</li>
 <li>Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR)</li>
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index cdcc68f9..c5b3b9a4 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -1,4 +1,4 @@
-pandoc: 2.9.2.1
+pandoc: 2.7.3
 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: 2020-10-21T13:25Z
+last_built: 2020-10-26T10:52Z
 urls:
   reference: https://msberends.github.io/AMR//reference
   article: https://msberends.github.io/AMR//articles
diff --git a/docs/reference/AMR-deprecated.html b/docs/reference/AMR-deprecated.html
index a36f0183..75c040cf 100644
--- a/docs/reference/AMR-deprecated.html
+++ b/docs/reference/AMR-deprecated.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9001</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/age.html b/docs/reference/age.html
index ae1c4d73..b9481718 100644
--- a/docs/reference/age.html
+++ b/docs/reference/age.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9001</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/age_groups.html b/docs/reference/age_groups.html
index b8c07046..df8b7115 100644
--- a/docs/reference/age_groups.html
+++ b/docs/reference/age_groups.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9001</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/antibiotic_class_selectors.html b/docs/reference/antibiotic_class_selectors.html
index 74776212..9878f8be 100644
--- a/docs/reference/antibiotic_class_selectors.html
+++ b/docs/reference/antibiotic_class_selectors.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9001</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/as.mo.html b/docs/reference/as.mo.html
index 2929590f..64a0351b 100644
--- a/docs/reference/as.mo.html
+++ b/docs/reference/as.mo.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/as.rsi.html b/docs/reference/as.rsi.html
index 54b4007e..5dcbf2fc 100644
--- a/docs/reference/as.rsi.html
+++ b/docs/reference/as.rsi.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9004</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/bug_drug_combinations.html b/docs/reference/bug_drug_combinations.html
index 1a483cac..f7ae9ab5 100644
--- a/docs/reference/bug_drug_combinations.html
+++ b/docs/reference/bug_drug_combinations.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9001</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/filter_ab_class.html b/docs/reference/filter_ab_class.html
index c0c462e6..b3a04a3d 100644
--- a/docs/reference/filter_ab_class.html
+++ b/docs/reference/filter_ab_class.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -242,33 +242,33 @@
     <p>Filter isolates on results in specific antimicrobial classes. This makes it easy to filter on isolates that were tested for e.g. any aminoglycoside, or to filter on carbapenem-resistant isolates without the need to specify the drugs.</p>
     </div>
 
-    <pre class="usage"><span class='fu'>filter_ab_class</span>(<span class='kw'>x</span>, <span class='kw'>ab_class</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+    <pre class="usage"><span class='fu'>filter_ab_class</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>ab_class</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_aminoglycosides</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_carbapenems</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_carbapenems</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_1st_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_1st_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_2nd_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_2nd_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_3rd_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_3rd_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_4th_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_4th_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_5th_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_5th_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_fluoroquinolones</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_fluoroquinolones</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_glycopeptides</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_glycopeptides</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_macrolides</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_macrolides</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_penicillins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
+<span class='fu'>filter_penicillins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>filter_tetracyclines</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)</pre>
+<span class='fu'>filter_tetracyclines</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span></pre>
 
     <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
     <table class="ref-arguments">
@@ -310,43 +310,43 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
     <div class='dont-index'><p><code><a href='antibiotic_class_selectors.html'>antibiotic_class_selectors()</a></code> for the <code><a href='https://dplyr.tidyverse.org/reference/select.html'>select()</a></code> equivalent.</p></div>
 
     <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><span class='fu'>filter_aminoglycosides</span>(<span class='kw'>example_isolates</span>)
+    <pre class="examples"><span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='va'>example_isolates</span><span class='op'>)</span>
 
 <span class='co'># \donttest{</span>
-<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
+<span class='kw'>if</span> <span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span>
 
   <span class='co'># filter on isolates that have any result for any aminoglycoside</span>
-  <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>()
-  <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_ab_class</span>(<span class='st'>"aminoglycoside"</span>)
+  <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='op'>)</span>
+  <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_ab_class</span><span class='op'>(</span><span class='st'>"aminoglycoside"</span><span class='op'>)</span>
 
   <span class='co'># this is essentially the same as (but without determination of column names):</span>
-  <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
-    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter_all.html'>filter_at</a></span>(.vars = <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"GEN"</span>, <span class='st'>"TOB"</span>, <span class='st'>"AMK"</span>, <span class='st'>"KAN"</span>)),
-              .vars_predicate = <span class='fu'><a href='https://dplyr.tidyverse.org/reference/all_vars.html'>any_vars</a></span>(<span class='kw'>.</span> <span class='op'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"S"</span>, <span class='st'>"I"</span>, <span class='st'>"R"</span>)))
+  <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
+    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter_all.html'>filter_at</a></span><span class='op'>(</span>.vars <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='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"GEN"</span>, <span class='st'>"TOB"</span>, <span class='st'>"AMK"</span>, <span class='st'>"KAN"</span><span class='op'>)</span><span class='op'>)</span>,
+              .vars_predicate <span class='op'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/all_vars.html'>any_vars</a></span><span class='op'>(</span><span class='va'>.</span> <span class='op'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"S"</span>, <span class='st'>"I"</span>, <span class='st'>"R"</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>
 
 
   <span class='co'># filter on isolates that show resistance to ANY aminoglycoside</span>
-  <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"any"</span>)
+  <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"any"</span><span class='op'>)</span>
  
   <span class='co'># filter on isolates that show resistance to ALL aminoglycosides</span>
-  <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
+  <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span>
  
   <span class='co'># filter on isolates that show resistance to</span>
   <span class='co'># any aminoglycoside and any fluoroquinolone</span>
-  <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
-    <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>) <span class='op'>%&gt;%</span>
-    <span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>)
+  <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
+    <span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='st'>"R"</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
+    <span class='fu'>filter_fluoroquinolones</span><span class='op'>(</span><span class='st'>"R"</span><span class='op'>)</span>
  
   <span class='co'># filter on isolates that show resistance to</span>
   <span class='co'># all aminoglycosides and all fluoroquinolones</span>
-  <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
-    <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>) <span class='op'>%&gt;%</span>
-    <span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
+  <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
+    <span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
+    <span class='fu'>filter_fluoroquinolones</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span>
   
   <span class='co'># with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:</span>
-  <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_carbapenems</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
-  <span class='kw'>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='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span>(), <span class='op'>~</span><span class='kw'>.</span> <span class='op'>==</span> <span class='st'>"R"</span>))
-}
+  <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_carbapenems</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span>
+  <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='https://dplyr.tidyverse.org/reference/across.html'>across</a></span><span class='op'>(</span><span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='op'>~</span><span class='va'>.</span> <span class='op'>==</span> <span class='st'>"R"</span><span class='op'>)</span><span class='op'>)</span>
+<span class='op'>}</span>
 <span class='co'># }</span>
 </pre>
   </div>
@@ -364,7 +364,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
 </div>
 
 <div class="pkgdown">
-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
 </div>
 
       </footer>
diff --git a/docs/reference/ggplot_pca.html b/docs/reference/ggplot_pca.html
index f030146e..8c4335d9 100644
--- a/docs/reference/ggplot_pca.html
+++ b/docs/reference/ggplot_pca.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9001</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/ggplot_rsi.html b/docs/reference/ggplot_rsi.html
index aa0c0863..ed656446 100644
--- a/docs/reference/ggplot_rsi.html
+++ b/docs/reference/ggplot_rsi.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9005</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/guess_ab_col.html b/docs/reference/guess_ab_col.html
index 8d6433eb..6c43b4d4 100644
--- a/docs/reference/guess_ab_col.html
+++ b/docs/reference/guess_ab_col.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9001</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 9bf4c5c6..c080b55b 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -581,9 +581,9 @@
       </tr><tr>
         
         <td>
-          <p><code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> <code><a href="like.html">`%like_case%`</a></code> </p>
+          <p><code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> <code><a href="like.html">`%not_like%`</a></code> <code><a href="like.html">`%like_case%`</a></code> <code><a href="like.html">`%not_like_case%`</a></code> </p>
         </td>
-        <td><p>Pattern Matching</p></td>
+        <td><p>Pattern matching with keyboard shortcut</p></td>
       </tr><tr>
         
         <td>
diff --git a/docs/reference/key_antibiotics.html b/docs/reference/key_antibiotics.html
index 14e314da..89c5d3be 100644
--- a/docs/reference/key_antibiotics.html
+++ b/docs/reference/key_antibiotics.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9001</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/docs/reference/lifecycle.html b/docs/reference/lifecycle.html
index e6a5443d..2372b3f7 100644
--- a/docs/reference/lifecycle.html
+++ b/docs/reference/lifecycle.html
@@ -84,7 +84,7 @@ This page contains a section for every lifecycle (with text borrowed from the af
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -295,7 +295,7 @@ The lifecycle of this function is <strong>questioning</strong>. This function mi
 </div>
 
 <div class="pkgdown">
-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
 </div>
 
       </footer>
diff --git a/docs/reference/like.html b/docs/reference/like.html
index 9459a30f..e7d875a9 100644
--- a/docs/reference/like.html
+++ b/docs/reference/like.html
@@ -6,7 +6,7 @@
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1.0">
 
-<title>Pattern Matching — like • AMR (for R)</title>
+<title>Pattern matching with keyboard shortcut — like • AMR (for R)</title>
 
 <!-- favicons -->
 <link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
@@ -48,7 +48,7 @@
   <link href="../extra.css" rel="stylesheet">
   <script src="../extra.js"></script>
 
-<meta property="og:title" content="Pattern Matching — like" />
+<meta property="og:title" content="Pattern matching with keyboard shortcut — like" />
 <meta property="og:description" content="Convenient wrapper around grep() 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." />
 <meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
 
@@ -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">1.4.0.9000</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -233,7 +233,7 @@
 <div class="row">
   <div class="col-md-9 contents">
     <div class="page-header">
-    <h1>Pattern Matching</h1>
+    <h1>Pattern matching with keyboard shortcut</h1>
     <small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/like.R'><code>R/like.R</code></a></small>
     <div class="hidden name"><code>like.Rd</code></div>
     </div>
@@ -246,7 +246,11 @@
 
 <span class='va'>x</span> <span class='op'>%like%</span> <span class='va'>pattern</span>
 
-<span class='va'>x</span> <span class='op'>%like_case%</span> <span class='va'>pattern</span></pre>
+<span class='va'>x</span> <span class='op'>%not_like%</span> <span class='va'>pattern</span>
+
+<span class='va'>x</span> <span class='op'>%like_case%</span> <span class='va'>pattern</span>
+
+<span class='va'>x</span> <span class='op'>%not_like_case%</span> <span class='va'>pattern</span></pre>
 
     <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
     <table class="ref-arguments">
@@ -280,7 +284,8 @@
 <li><p>Tries again with <code>perl = TRUE</code> if regex fails</p></li>
 </ul>
 
-<p>Using RStudio? This function can also be inserted from the Addins menu and can have its own Keyboard Shortcut like <code>Ctrl+Shift+L</code> or <code>Cmd+Shift+L</code> (see <code>Tools</code> &gt; <code>Modify Keyboard Shortcuts...</code>).</p>
+<p>Using RStudio? This function can also be inserted in your code from the Addins menu and can have its own Keyboard Shortcut like <code>Ctrl+Shift+L</code> or <code>Cmd+Shift+L</code> (see <code>Tools</code> &gt; <code>Modify Keyboard Shortcuts...</code>). This addin iterates over all 'like' variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert <code>%like%</code> and by pressing it again it will be replaced with <code>%not_like%</code>, then <code>%like_case%</code>, then <code>%not_like_case%</code> and then back to <code>%like%</code>.</p>
+<p>The <code>"%not_like%"</code> and <code>"%not_like_case%"</code> functions are wrappers around <code>"%like%"</code> and <code>"%like_case%"</code>.</p>
     <h2 class="hasAnchor" id="stable-lifecycle"><a class="anchor" href="#stable-lifecycle"></a>Stable lifecycle</h2>
 
     
diff --git a/docs/reference/mo_property.html b/docs/reference/mo_property.html
index 38b02145..c7e8aeea 100644
--- a/docs/reference/mo_property.html
+++ b/docs/reference/mo_property.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -270,9 +270,9 @@
 
 <span class='fu'>mo_gramstain</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>is_gram_negative</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>...</span><span class='op'>)</span>
+<span class='fu'>is_gram_negative</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
 
-<span class='fu'>is_gram_positive</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>...</span><span class='op'>)</span>
+<span class='fu'>is_gram_positive</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
 
 <span class='fu'>mo_snomed</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
 
@@ -303,7 +303,7 @@
     </tr>
     <tr>
       <th>language</th>
-      <td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale()</a></code>) and can be overwritten by setting the option <code>AMR_locale</code>, e.g. <code><a href='https://rdrr.io/r/base/options.html'>options(AMR_locale = "de")</a></code>, see <a href='translate.html'>translate</a>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
+      <td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale()</a></code>) and can be overwritten by setting the option <code>AMR_locale</code>, e.g. <code><a href='https://rdrr.io/r/base/options.html'>options(AMR_locale = "de")</a></code>, see <a href='translate.html'>translate</a>. Also used to translate text like "no growth". Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
     </tr>
     <tr>
       <th>...</th>
diff --git a/docs/reference/pca.html b/docs/reference/pca.html
index 0034a047..a7eecbbc 100644
--- a/docs/reference/pca.html
+++ b/docs/reference/pca.html
@@ -82,7 +82,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
@@ -242,15 +242,15 @@
     <p>Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables.</p>
     </div>
 
-    <pre class="usage"><span class='fu'>pca</span>(
-  <span class='kw'>x</span>,
-  <span class='kw'>...</span>,
-  retx = <span class='fl'>TRUE</span>,
-  center = <span class='fl'>TRUE</span>,
-  scale. = <span class='fl'>TRUE</span>,
-  tol = <span class='kw'>NULL</span>,
-  rank. = <span class='kw'>NULL</span>
-)</pre>
+    <pre class="usage"><span class='fu'>pca</span><span class='op'>(</span>
+  <span class='va'>x</span>,
+  <span class='va'>...</span>,
+  retx <span class='op'>=</span> <span class='cn'>TRUE</span>,
+  center <span class='op'>=</span> <span class='cn'>TRUE</span>,
+  scale. <span class='op'>=</span> <span class='cn'>TRUE</span>,
+  tol <span class='op'>=</span> <span class='cn'>NULL</span>,
+  rank. <span class='op'>=</span> <span class='cn'>NULL</span>
+<span class='op'>)</span></pre>
 
     <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
     <table class="ref-arguments">
@@ -324,22 +324,22 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
 
 <span class='co'># \donttest{</span>
 
-<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
+<span class='kw'>if</span> <span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span>
   <span class='co'># calculate the resistance per group first </span>
-  <span class='kw'>resistance_data</span> <span class='op'>&lt;-</span> <span class='kw'>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>(order = <span class='fu'><a href='mo_property.html'>mo_order</a></span>(<span class='kw'>mo</span>),       <span class='co'># group on anything, like order</span>
-             genus = <span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='kw'>mo</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='kw'>is.rsi</span>, <span class='kw'>resistance</span>)     <span class='co'># then get resistance of all drugs</span>
+  <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='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='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='co'># then get resistance of all drugs</span>
     
   <span class='co'># now conduct PCA for certain antimicrobial agents</span>
-  <span class='kw'>pca_result</span> <span class='op'>&lt;-</span> <span class='kw'>resistance_data</span> <span class='op'>%&gt;%</span>         
-    <span class='fu'>pca</span>(<span class='kw'>AMC</span>, <span class='kw'>CXM</span>, <span class='kw'>CTX</span>, <span class='kw'>CAZ</span>, <span class='kw'>GEN</span>, <span class='kw'>TOB</span>, <span class='kw'>TMP</span>, <span class='kw'>SXT</span>) 
+  <span class='va'>pca_result</span> <span class='op'>&lt;-</span> <span class='va'>resistance_data</span> <span class='op'>%&gt;%</span>         
+    <span class='fu'>pca</span><span class='op'>(</span><span class='va'>AMC</span>, <span class='va'>CXM</span>, <span class='va'>CTX</span>, <span class='va'>CAZ</span>, <span class='va'>GEN</span>, <span class='va'>TOB</span>, <span class='va'>TMP</span>, <span class='va'>SXT</span><span class='op'>)</span> 
     
-  <span class='kw'>pca_result</span>
-  <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='kw'>pca_result</span>)
-  <span class='fu'><a href='https://rdrr.io/r/stats/biplot.html'>biplot</a></span>(<span class='kw'>pca_result</span>)
-  <span class='fu'><a href='ggplot_pca.html'>ggplot_pca</a></span>(<span class='kw'>pca_result</span>) <span class='co'># a new and convenient plot function</span>
-}
+  <span class='va'>pca_result</span>
+  <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='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>
+  <span class='fu'><a href='ggplot_pca.html'>ggplot_pca</a></span><span class='op'>(</span><span class='va'>pca_result</span><span class='op'>)</span> <span class='co'># a new and convenient plot function</span>
+<span class='op'>}</span>
 <span class='co'># }</span>
 </pre>
   </div>
@@ -357,7 +357,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
 </div>
 
 <div class="pkgdown">
-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
 </div>
 
       </footer>
diff --git a/docs/survey.html b/docs/survey.html
index 287f0388..a4eb760e 100644
--- a/docs/survey.html
+++ b/docs/survey.html
@@ -81,7 +81,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
       </span>
     </div>
 
diff --git a/inst/rstudio/addins.dcf b/inst/rstudio/addins.dcf
index d43c060a..738ce92b 100644
--- a/inst/rstudio/addins.dcf
+++ b/inst/rstudio/addins.dcf
@@ -2,6 +2,6 @@ Name: Insert %in%
 Binding: addin_insert_in
 Interactive: false
 
-Name: Insert %like%
+Name: Insert %like% / %not_like%
 Binding: addin_insert_like
 Interactive: false
diff --git a/man/like.Rd b/man/like.Rd
index ebefb15a..a7067402 100755
--- a/man/like.Rd
+++ b/man/like.Rd
@@ -3,8 +3,10 @@
 \name{like}
 \alias{like}
 \alias{\%like\%}
+\alias{\%not_like\%}
 \alias{\%like_case\%}
-\title{Pattern Matching}
+\alias{\%not_like_case\%}
+\title{Pattern matching with keyboard shortcut}
 \source{
 Idea from the \href{https://github.com/Rdatatable/data.table/blob/master/R/like.R}{\code{like} function from the \code{data.table} package}
 }
@@ -13,7 +15,11 @@ like(x, pattern, ignore.case = TRUE)
 
 x \%like\% pattern
 
+x \%not_like\% pattern
+
 x \%like_case\% pattern
+
+x \%not_like_case\% pattern
 }
 \arguments{
 \item{x}{a character vector where matches are sought, or an object which can be coerced by \code{\link[=as.character]{as.character()}} to a character vector.}
@@ -37,7 +43,9 @@ The \verb{\%like\%} function:
 \item Tries again with \code{perl = TRUE} if regex fails
 }
 
-Using RStudio? This function can also be inserted from the Addins menu and can have its own Keyboard Shortcut like \code{Ctrl+Shift+L} or \code{Cmd+Shift+L} (see \code{Tools} > \verb{Modify Keyboard Shortcuts...}).
+Using RStudio? This function can also be inserted in your code from the Addins menu and can have its own Keyboard Shortcut like \code{Ctrl+Shift+L} or \code{Cmd+Shift+L} (see \code{Tools} > \verb{Modify Keyboard Shortcuts...}). This addin iterates over all 'like' variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert \verb{\%like\%} and by pressing it again it will be replaced with \verb{\%not_like\%}, then \verb{\%like_case\%}, then \verb{\%not_like_case\%} and then back to \verb{\%like\%}.
+
+The \code{"\%not_like\%"} and \code{"\%not_like_case\%"} functions are wrappers around \code{"\%like\%"} and \code{"\%like_case\%"}.
 }
 \section{Stable lifecycle}{
 
diff --git a/man/mo_property.Rd b/man/mo_property.Rd
index 62e2ae07..fac2dfaf 100644
--- a/man/mo_property.Rd
+++ b/man/mo_property.Rd
@@ -57,9 +57,9 @@ mo_type(x, language = get_locale(), ...)
 
 mo_gramstain(x, language = get_locale(), ...)
 
-is_gram_negative(x, ...)
+is_gram_negative(x, language = get_locale(), ...)
 
-is_gram_positive(x, ...)
+is_gram_positive(x, language = get_locale(), ...)
 
 mo_snomed(x, language = get_locale(), ...)
 
@@ -84,7 +84,7 @@ mo_property(x, property = "fullname", language = get_locale(), ...)
 \arguments{
 \item{x}{any character (vector) that can be coerced to a valid microorganism code with \code{\link[=as.mo]{as.mo()}}}
 
-\item{language}{language of the returned text, defaults to system language (see \code{\link[=get_locale]{get_locale()}}) and can be overwritten by setting the option \code{AMR_locale}, e.g. \code{options(AMR_locale = "de")}, see \link{translate}. Use \code{language = NULL} or \code{language = ""} to prevent translation.}
+\item{language}{language of the returned text, defaults to system language (see \code{\link[=get_locale]{get_locale()}}) and can be overwritten by setting the option \code{AMR_locale}, e.g. \code{options(AMR_locale = "de")}, see \link{translate}. Also used to translate text like "no growth". Use \code{language = NULL} or \code{language = ""} to prevent translation.}
 
 \item{...}{other parameters passed on to \code{\link[=as.mo]{as.mo()}}, such as 'allow_uncertain' and 'ignore_pattern'}
 
diff --git a/tests/testthat/test-like.R b/tests/testthat/test-like.R
index 276d346f..c941fda0 100644
--- a/tests/testthat/test-like.R
+++ b/tests/testthat/test-like.R
@@ -28,8 +28,13 @@ context("like.R")
 test_that("`like` works", {
   skip_on_cran()
   expect_true(sum("test" %like% c("^t", "^s")) == 1)
+  
   expect_true("test" %like% "test")
-  expect_true("test" %like% "TEST")
+  expect_false("test" %like_case% "TEST")
+  
+  expect_false("test" %not_like% "test")
+  expect_true("test" %not_like_case% "TEST")
+  
   expect_true(as.factor("test") %like% "TEST")
   expect_identical(factor(c("Test case", "Something different", "Yet another thing")) %like% c("case", "diff", "yet"),
                    c(TRUE, TRUE, TRUE))