(v1.3.0.9004) data sets, as.disk() improvement

2025-07-08 17:21:49 +02:00 · 2020-08-16 21:38:42 +02:00
parent e73f0e211c
commit dab017a50f
56 changed files with 1702 additions and 164 deletions
--- a/4
+++ b/4
@ -1,6 +1,6 @@
 Package: AMR
-Version: 1.3.0.9003
-Date: 2020-08-15
+Version: 1.3.0.9004
+Date: 2020-08-16
 Title: Antimicrobial Resistance Analysis
 Authors@R: c(
    person(role = c("aut", "cre"), 
--- a/NEWS.md
+++ b/NEWS.md
@ -1,5 +1,5 @@
-# AMR 1.3.0.9003
-## <small>Last updated: 15 August 2020</small>
+# AMR 1.3.0.9004
+## <small>Last updated: 16 August 2020</small>

 ### New
 * Data set `intrinsic_resistant`. This data set contains all bug-drug combinations where the 'bug' is intrinsic resistant to the 'drug' according to the latest EUCAST insights. It contains just two columns: `microorganism` and `antibiotic`.
@ -11,7 +11,7 @@
  intrinsic_resistant %>%
    filter(antibiotic == "Vancomycin", microorganism %like% "Enterococcus") %>% 
    pull(microorganism)
-  # [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"   
+  #> [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"   
  ```

 ### Changed
@ -27,6 +27,13 @@
    your_data %>% mutate(across(where(is.disk), as.rsi))
    ```
  * Big speed improvement for interpreting MIC values and disk zone diameters. When interpreting 5,000 MIC values of two antibiotics (10,000 values in total), our benchmarks showed a total run time going from 80.7-85.1 seconds to 1.8-2.0 seconds.
+  * Added parameter 'add_intrinsic_resistance' (defaults to `FALSE`), that considers intrinsic resistance according to EUCAST
+* Added intelligent data cleaning to `as.disk()`, so numbers can also be extracted from text and decimal numbers will always be rounded up:
+  ```r
+  as.disk(c("disk zone: 23.4 mm", 23.4))
+  #> Class <disk>
+  #> [1] 24 24
+  ```
 * Overall speed improvement by tweaking joining functions

 # AMR 1.3.0
--- a/R/aa_helper_functions.R
+++ b/R/aa_helper_functions.R
@ -575,3 +575,9 @@ isFALSE <- function(x) {
 deparse1 <- function(expr, collapse = " ", width.cutoff = 500L, ...) {
  paste(deparse(expr, width.cutoff, ...), collapse = collapse)
 }
+file.size <- function (...) {
+  base::file.info(...)$size
+}
+file.mtime <- function (...) {
+  base::file.info(...)$mtime
+}
--- a/R/data.R
+++ b/R/data.R
@ -221,7 +221,7 @@ catalogue_of_life <- list(

 #' Data set for R/SI interpretation
 #'
-#' Data set to interpret MIC and disk diffusion to R/SI values. Included guidelines are CLSI (2011-2019) and EUCAST (2011-2020). Use [as.rsi()] to transform MICs or disks measurements to R/SI values.
+#' Data set to interpret MIC and disk diffusion to R/SI values. Included guidelines are CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`) and EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`). Use [as.rsi()] to transform MICs or disks measurements to R/SI values.
 #' @format A [`data.frame`] with `r format(nrow(rsi_translation), big.mark = ",")` observations and `r ncol(rsi_translation)` variables:
 #' - `guideline`\cr Name of the guideline
 #' - `method`\cr Either "MIC" or "DISK"
@ -234,6 +234,8 @@ catalogue_of_life <- list(
 #' - `breakpoint_R`\cr Highest MIC value or lowest number of millimetres that leads to "R"
 #' - `uti`\cr A logical value (`TRUE`/`FALSE`) to indicate whether the rule applies to a urinary tract infection (UTI)
 #' @details The repository of this `AMR` package contains a file comprising this exact data set: <https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt>. This file **allows for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically.
+#' 
+#' 
 #' @inheritSection AMR Read more on our website!
 #' @seealso [intrinsic_resistant]
 "rsi_translation"
--- a/R/disk.R
+++ b/R/disk.R
@ -62,8 +62,27 @@ as.disk <- function(x, na.rm = FALSE) {
    
    na_before <- length(x[is.na(x)])
    
-    # force it to be integer
-    x <- suppressWarnings(as.integer(x))
+    # heavily based on the function from our cleaner package:
+    clean_double2 <- function(x, remove = "[^0-9.,-]", fixed = FALSE) {
+      x <- gsub(",", ".", x)
+      # remove ending dot/comma
+      x <- gsub("[,.]$", "", x)
+      # only keep last dot/comma
+      reverse <- function(x) sapply(lapply(strsplit(x, NULL), rev), paste, collapse = "")
+      x <- sub("{{dot}}", ".", 
+               gsub(".", "",
+                    reverse(sub(".", "}}tod{{",
+                                reverse(x), 
+                                fixed = TRUE)),
+                    fixed = TRUE), 
+               fixed = TRUE)
+      x_clean <- gsub(remove, "", x, ignore.case = TRUE, fixed = fixed)
+      # remove everything that is not a number or dot
+      as.numeric(gsub("[^0-9.]+", "", x_clean))
+    }
+    
+    # round up and make it an integer
+    x <- as.integer(ceiling(clean_double2(x)))
    
    # disks can never be less than 6 mm (size of smallest disk) or more than 50 mm
    x[x < 6 | x > 50] <- NA_integer_
--- a/R/rsi.R
+++ b/R/rsi.R
@ -31,6 +31,7 @@
 #' @inheritParams first_isolate
 #' @param guideline defaults to the latest included EUCAST guideline, see Details for all options
 #' @param conserve_capped_values a logical to indicate that MIC values starting with `">"` (but not `">="`) must always return "R" , and that MIC values starting with `"<"` (but not `"<="`) must always return "S"
+#' @param add_intrinsic_resistance *(only useful when using a EUCAST guideline)* a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in *Klebsiella* species. Determination is based on the [intrinsic_resistant] data set, that itself is based on 'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes', version `r EUCAST_VERSION_EXPERT_RULES`.
 #' @param threshold maximum fraction of invalid antimicrobial interpretations of `x`, please see *Examples*
 #' @param ... parameters passed on to methods
 #' @details 
@ -108,6 +109,9 @@
 #' 
 #' # the dplyr way
 #' library(dplyr)
+#' df %>% mutate_if(is.mic, as.rsi)
+#' df %>% mutate_if(function(x) is.mic(x) | is.disk(x), as.rsi)
+#' df %>% mutate(across(where(is.mic), as.rsi))
 #' df %>% mutate_at(vars(AMP:TOB), as.rsi)
 #' df %>% mutate(across(AMP:TOB), as.rsi)
 #'
@ -282,6 +286,7 @@ as.rsi.mic <- function(x,
                       guideline = "EUCAST", 
                       uti = FALSE,
                       conserve_capped_values = FALSE,
+                       add_intrinsic_resistance = FALSE,
                       ...) {
  
  # for dplyr's across()
@ -339,7 +344,8 @@ as.rsi.mic <- function(x,
                        ab = ab_coerced,
                        guideline = guideline_coerced,
                        uti = uti,
-                        conserve_capped_values = conserve_capped_values) # exec_as.rsi will return message(font_blue(" OK."))
+                        conserve_capped_values = conserve_capped_values,
+                        add_intrinsic_resistance = add_intrinsic_resistance) # exec_as.rsi will return message(font_blue(" OK."))
  result
 }

@ -350,6 +356,7 @@ as.rsi.disk <- function(x,
                        ab = deparse(substitute(x)), 
                        guideline = "EUCAST", 
                        uti = FALSE,
+                        add_intrinsic_resistance = FALSE,
                        ...) {
  
  # for dplyr's across()
@ -405,7 +412,9 @@ as.rsi.disk <- function(x,
                        mo = mo_coerced,
                        ab = ab_coerced,
                        guideline = guideline_coerced,
-                        uti = uti) # exec_as.rsi will return message(font_blue(" OK."))
+                        uti = uti,
+                        conserve_capped_values = FALSE,
+                        add_intrinsic_resistance = add_intrinsic_resistance) # exec_as.rsi will return message(font_blue(" OK."))
  result
 }

@ -416,6 +425,7 @@ as.rsi.data.frame <- function(x,
                              guideline = "EUCAST",
                              uti = NULL,
                              conserve_capped_values = FALSE,
+                              add_intrinsic_resistance = FALSE,
                              ...) {
  # try to find columns based on type
  # -- mo
@ -534,7 +544,15 @@ get_guideline <- function(guideline) {
  
 }

-exec_as.rsi <- function(method, x, mo, ab, guideline, uti, conserve_capped_values) {
+exec_as.rsi <- function(method,
+                        x,
+                        mo,
+                        ab,
+                        guideline,
+                        uti,
+                        conserve_capped_values, 
+                        add_intrinsic_resistance) {
+  
  x_bak <- data.frame(x_mo = paste0(x, mo))
  df <- unique(data.frame(x, mo), stringsAsFactors = FALSE)
  x <- df$x
@ -582,8 +600,21 @@ exec_as.rsi <- function(method, x, mo, ab, guideline, uti, conserve_capped_value
  }
  
  for (i in seq_len(length(x))) {
+    if (isTRUE(add_intrinsic_resistance)) {
+      if (!guideline_coerced %like% "EUCAST") {
+        warning("Using 'add_intrinsic_resistance' is only useful when using EUCAST guidelines, since the rules for intrinsic resistance are based on EUCAST.", call. = FALSE)
+      } else {
+        get_record <- subset(intrinsic_resistant, 
+                             microorganism == mo_name(mo[i], language = NULL) & antibiotic == ab_name(ab, language = NULL))
+        if (nrow(get_record) > 0) {
+          new_rsi[i] <- "R"
+          next
+        }
+      }
+    }
+    
    get_record <- trans %>%
-      # no sebsetting to UTI for now
+      # no subsetting to UTI for now
      subset(lookup %in% c(lookup_mo[i],
                           lookup_genus[i],
                           lookup_family[i],
--- a/README.md
+++ b/README.md
@ -1,6 +1,10 @@
 % AMR (for R)

 # `AMR` (for R)
+
+<img src="https://www.r-pkg.org/badges/version-ago/AMR" />
+<img src="https://cranlogs.r-pkg.org/badges/grand-total/AMR" />
+
 <img src="https://msberends.github.io/AMR/works_great_on.png" align="center" height="150px" />

 `AMR` is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@ -44,6 +44,9 @@ navbar:
      - text: "Predict antimicrobial resistance"
        icon: "fa-dice"
        href: "articles/resistance_predict.html"
+      - text: "Download our free data sets"
+        icon: "fa-database"
+        href: "articles/datasets.html"
      - text: "Conduct principal component analysis for AMR"
        icon: "fa-compress"
        href: "articles/PCA.html"
--- a/data-raw/antibiotics.dta
+++ b/data-raw/antibiotics.dta
--- a/data-raw/antibiotics.rds
+++ b/data-raw/antibiotics.rds
--- a/data-raw/antibiotics.sas
+++ b/data-raw/antibiotics.sas
--- a/data-raw/antibiotics.sav
+++ b/data-raw/antibiotics.sav
--- a/data-raw/antibiotics.xlsx
+++ b/data-raw/antibiotics.xlsx
--- a/data-raw/antivirals.dta
+++ b/data-raw/antivirals.dta
--- a/data-raw/antivirals.rds
+++ b/data-raw/antivirals.rds
--- a/data-raw/antivirals.sas
+++ b/data-raw/antivirals.sas
--- a/data-raw/antivirals.sav
+++ b/data-raw/antivirals.sav
--- a/data-raw/antivirals.txt
+++ b/data-raw/antivirals.txt
@ -1,31 +1,31 @@
 "atc"	"cid"	"name"	"atc_group"	"synonyms"	"oral_ddd"	"oral_units"	"iv_ddd"	"iv_units"
-"J05AF06"	"441300"	"abacavir"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Abacavir\", \"Abacavir sulfate\", \"Ziagen\")"	"0.6"	"g"		
-"J05AB01"	"135398513"	"aciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Acicloftal\", \"Aciclovier\", \"Aciclovir\", \"Aciclovirum\", \"Activir\", \"AcycloFoam\", \"Acycloguanosine\", \"Acyclovir\", \"Acyclovir Lauriad\", \"ACYCLOVIR SODIUM\", \"Avirax\", \"Cargosil\", \"Cyclovir\", \"Genvir\", \"Gerpevir\", \"Hascovir\", \"Herpevir\", \"Maynar\", \"Poviral\", \"Sitavig\", \"Sitavir\", \"Vipral\", \"Virolex\", \"Viropump\", \"Virorax\", \"Zovirax\", \"Zovirax topical\", \"Zyclir\")"	"4"	"g"	"4"	"g"
-"J05AF08"	"60871"	"adefovir dipivoxil"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Adefovir di ester\", \"Adefovir dipivoxil\", \"Adefovir Dipivoxil\", \"Adefovir dipivoxyl\", \"Adefovir pivoxil\", \"Adefovirdipivoxl\", \"Bisadenine\", \"BISADENINE\", \"BisPMEA\", \"Hepsera\", \"Preveon\", \"YouHeDing\")"	"10"	"mg"		
-"J05AE05"	"65016"	"amprenavir"	"Protease inhibitors"	"c(\"Agenerase\", \"Amprenavir\", \"Amprenavirum\", \"Prozei\", \"Vertex\")"	"1.2"	"g"		
-"J05AP06"	"16076883"	"asunaprevir"	"Antivirals for treatment of HCV infections"	"c(\"Asunaprevir\", \"Sunvepra\")"				
-"J05AE08"	"148192"	"atazanavir"	"Protease inhibitors"	"c(\"Atazanavir\", \"Atazanavir Base\", \"Latazanavir\", \"Reyataz\", \"Zrivada\")"	"0.3"	"g"		
-"J05AR15"	"86583336"	"atazanavir and cobicistat"	"Antivirals for treatment of HIV infections, combinations"	""				
-"J05AR23"		"atazanavir and ritonavir"	"Antivirals for treatment of HIV infections, combinations"	""	"0.3"	"g"		
-"J05AP03"	"10324367"	"boceprevir"	"Antivirals for treatment of HCV infections"	"c(\"Bocepravir\", \"Boceprevir\", \"Victrelis\")"	"2.4"	"g"		
-"J05AB15"	"446727"	"brivudine"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Bridic\", \"Brivox\", \"Brivudin\", \"Brivudina\", \"Brivudine\", \"Brivudinum\", \"BrVdUrd\", \"Helpin\", \"Zerpex\", \"Zostex\")"	"0.125"	"g"		
-"J05AB12"	"60613"	"cidofovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Cidofovir\", \"Cidofovir anhydrous\", \"Cidofovir gel\", \"Cidofovirum\", \"Forvade\", \"Vistide\")"			"25"	"mg"
-"J05AF12"	"73115"	"clevudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Clevudine\", \"Levovir\", \"Revovir\")"	"30"	"mg"		
-"J05AP07"	"25154714"	"daclatasvir"	"Antivirals for treatment of HCV infections"	"c(\"Daclatasvir\", \"Daklinza\")"	"60"	"mg"		
-"J05AE10"	"213039"	"darunavir"	"Protease inhibitors"	"c(\"Darunavir\", \"Darunavirum\", \"Prezista\", \"Prezista Naive\")"	"1.2"	"g"		
+"J05AF06"	441300	"abacavir"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Abacavir\", \"Abacavir sulfate\", \"Ziagen\")"	0.6	"g"		
+"J05AB01"	135398513	"aciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Acicloftal\", \"Aciclovier\", \"Aciclovir\", \"Aciclovirum\", \"Activir\", \"AcycloFoam\", \"Acycloguanosine\", \"Acyclovir\", \"Acyclovir Lauriad\", \"ACYCLOVIR SODIUM\", \"Avirax\", \"Cargosil\", \"Cyclovir\", \"Genvir\", \"Gerpevir\", \"Hascovir\", \"Herpevir\", \"Maynar\", \"Poviral\", \"Sitavig\", \"Sitavir\", \"Vipral\", \"Virolex\", \"Viropump\", \"Virorax\", \"Zovirax\", \"Zovirax topical\", \"Zyclir\")"	4	"g"	4	"g"
+"J05AF08"	60871	"adefovir dipivoxil"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Adefovir di ester\", \"Adefovir dipivoxil\", \"Adefovir Dipivoxil\", \"Adefovir dipivoxyl\", \"Adefovir pivoxil\", \"Adefovirdipivoxl\", \"Bisadenine\", \"BISADENINE\", \"BisPMEA\", \"Hepsera\", \"Preveon\", \"YouHeDing\")"	10	"mg"		
+"J05AE05"	65016	"amprenavir"	"Protease inhibitors"	"c(\"Agenerase\", \"Amprenavir\", \"Amprenavirum\", \"Prozei\", \"Vertex\")"	1.2	"g"		
+"J05AP06"	16076883	"asunaprevir"	"Antivirals for treatment of HCV infections"	"c(\"Asunaprevir\", \"Sunvepra\")"				
+"J05AE08"	148192	"atazanavir"	"Protease inhibitors"	"c(\"Atazanavir\", \"Atazanavir Base\", \"Latazanavir\", \"Reyataz\", \"Zrivada\")"	0.3	"g"		
+"J05AR15"	86583336	"atazanavir and cobicistat"	"Antivirals for treatment of HIV infections, combinations"	""				
+"J05AR23"		"atazanavir and ritonavir"	"Antivirals for treatment of HIV infections, combinations"	""	0.3	"g"		
+"J05AP03"	10324367	"boceprevir"	"Antivirals for treatment of HCV infections"	"c(\"Bocepravir\", \"Boceprevir\", \"Victrelis\")"	2.4	"g"		
+"J05AB15"	446727	"brivudine"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Bridic\", \"Brivox\", \"Brivudin\", \"Brivudina\", \"Brivudine\", \"Brivudinum\", \"BrVdUrd\", \"Helpin\", \"Zerpex\", \"Zostex\")"	0.125	"g"		
+"J05AB12"	60613	"cidofovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Cidofovir\", \"Cidofovir anhydrous\", \"Cidofovir gel\", \"Cidofovirum\", \"Forvade\", \"Vistide\")"			25	"mg"
+"J05AF12"	73115	"clevudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Clevudine\", \"Levovir\", \"Revovir\")"	30	"mg"		
+"J05AP07"	25154714	"daclatasvir"	"Antivirals for treatment of HCV infections"	"c(\"Daclatasvir\", \"Daklinza\")"	60	"mg"		
+"J05AE10"	213039	"darunavir"	"Protease inhibitors"	"c(\"Darunavir\", \"Darunavirum\", \"Prezista\", \"Prezista Naive\")"	1.2	"g"		
 "J05AR14"		"darunavir and cobicistat"	"Antivirals for treatment of HIV infections, combinations"	""				
-"J05AP09"	"56640146"	"dasabuvir"	"Antivirals for treatment of HCV infections"	"Dasabuvir"	"0.5"	"g"		
+"J05AP09"	56640146	"dasabuvir"	"Antivirals for treatment of HCV infections"	"Dasabuvir"	0.5	"g"		
 "J05AP52"		"dasabuvir, ombitasvir, paritaprevir and ritonavir"	"Antivirals for treatment of HCV infections"	""				
-"J05AG02"	"5625"	"delavirdine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"BHAP der\", \"Delavirdin\", \"Delavirdina\", \"Delavirdine\", \"Delavirdinum\", \"PIPERAZINE\", \"Rescriptor\")"	"1.2"	"g"		
-"J05AF02"	"135398739"	"didanosine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Didanosina\", \"Didanosine\", \"Didanosinum\", \"Dideoxyinosine\", \"DIDEOXYINOSINE\", \"Hypoxanthine ddN\", \"Videx\", \"Videx EC\")"	"0.4"	"g"		
-"J05AX12"	"54726191"	"dolutegravir"	"Other antivirals"	"c(\"Dolutegravir\", \"Dolutegravir Sodium\", \"Soltegravir\", \"Tivicay\")"	"50"	"mg"		
-"J05AR21"	"131801472"	"dolutegravir and rilpivirine"	"Antivirals for treatment of HIV infections, combinations"	""				
-"J05AG06"	"58460047"	"doravirine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"Doravirine\", \"Pifeltro\")"				
-"J05AG03"	"64139"	"efavirenz"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"Efavirenz\", \"Efavirenzum\", \"Eravirenz\", \"Stocrin\", \"Strocin\", \"Sustiva\")"	"0.6"	"g"		
-"J05AP54"	"91669168"	"elbasvir and grazoprevir"	"Antivirals for treatment of HCV infections"	""				
-"J05AX11"	"5277135"	"elvitegravir"	"Other antivirals"	"c(\"Elvitegravir\", \"Vitekta\")"				
-"J05AF09"	"60877"	"emtricitabine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Coviracil\", \"Emtricitabin\", \"Emtricitabina\", \"Emtricitabine\", \"Emtricitabinum\", \"Emtritabine\", \"Emtriva\", \"Racivir\")"	"0.2"	"g"		
-"J05AR17"	"90469070"	"emtricitabine and tenofovir alafenamide"	"Antivirals for treatment of HIV infections, combinations"	""				
+"J05AG02"	5625	"delavirdine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"BHAP der\", \"Delavirdin\", \"Delavirdina\", \"Delavirdine\", \"Delavirdinum\", \"PIPERAZINE\", \"Rescriptor\")"	1.2	"g"		
+"J05AF02"	135398739	"didanosine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Didanosina\", \"Didanosine\", \"Didanosinum\", \"Dideoxyinosine\", \"DIDEOXYINOSINE\", \"Hypoxanthine ddN\", \"Videx\", \"Videx EC\")"	0.4	"g"		
+"J05AX12"	54726191	"dolutegravir"	"Other antivirals"	"c(\"Dolutegravir\", \"Dolutegravir Sodium\", \"Soltegravir\", \"Tivicay\")"	50	"mg"		
+"J05AR21"	131801472	"dolutegravir and rilpivirine"	"Antivirals for treatment of HIV infections, combinations"	""				
+"J05AG06"	58460047	"doravirine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"Doravirine\", \"Pifeltro\")"				
+"J05AG03"	64139	"efavirenz"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"Efavirenz\", \"Efavirenzum\", \"Eravirenz\", \"Stocrin\", \"Strocin\", \"Sustiva\")"	0.6	"g"		
+"J05AP54"	91669168	"elbasvir and grazoprevir"	"Antivirals for treatment of HCV infections"	""				
+"J05AX11"	5277135	"elvitegravir"	"Other antivirals"	"c(\"Elvitegravir\", \"Vitekta\")"				
+"J05AF09"	60877	"emtricitabine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Coviracil\", \"Emtricitabin\", \"Emtricitabina\", \"Emtricitabine\", \"Emtricitabinum\", \"Emtritabine\", \"Emtriva\", \"Racivir\")"	0.2	"g"		
+"J05AR17"	90469070	"emtricitabine and tenofovir alafenamide"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR20"		"emtricitabine, tenofovir alafenamide and bictegravir"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR19"		"emtricitabine, tenofovir alafenamide and rilpivirine"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR22"		"emtricitabine, tenofovir alafenamide, darunavir and cobicistat"	"Antivirals for treatment of HIV infections, combinations"	""				
@ -33,71 +33,71 @@
 "J05AR06"		"emtricitabine, tenofovir disoproxil and efavirenz"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR08"		"emtricitabine, tenofovir disoproxil and rilpivirine"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR09"		"emtricitabine, tenofovir disoproxil, elvitegravir and cobicistat"	"Antivirals for treatment of HIV infections, combinations"	""				
-"J05AX07"	"16130199"	"enfuvirtide"	"Other antivirals"	"c(\"Enfurvitide\", \"Enfuvirtide\", \"Fuzeon\", \"Pentafuside\")"			"0.18"	"g"
-"J05AX17"	"10089466"	"enisamium iodide"	"Other antivirals"	"Enisamium iodide"	"1.5"	"g"		
-"J05AF10"	"135398508"	"entecavir"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Baraclude\", \"Entecavir\", \"Entecavir anhydrous\", \"Entecavirum\")"	"0.5"	"mg"		
-"J05AG04"	"193962"	"etravirine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"DAPY deriv\", \"Etravine\", \"Etravirine\", \"Intelence\")"	"0.4"	"g"		
-"J05AP04"	"42601552"	"faldaprevir"	"Antivirals for treatment of HCV infections"	"Faldaprevir"				
-"J05AB09"	"3324"	"famciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Famciclovir\", \"Famciclovirum\", \"Famvir\", \"Oravir\")"	"0.75"	"g"		
-"J05AE07"	"131536"	"fosamprenavir"	"Protease inhibitors"	"c(\"Amprenavir phosphate\", \"Fosamprenavir\", \"Lexiva\", \"Telzir\")"	"1.4"	"g"		
-"J05AD01"	"3415"	"foscarnet"	"Phosphonic acid derivatives"	"c(\"Forscarnet\", \"Forscarnet sodium\", \"Foscarmet\", \"Foscarnet\", \"Phosphonoformate\", \"Phosphonoformic acid\")"			"6.5"	"g"
-"J05AD02"	"546"	"fosfonet"	"Phosphonic acid derivatives"	"c(\"Fosfonet\", \"Fosfonet sodium\", \"Fosfonet Sodium\", \"Fosfonoacetate\", \"Fosfonoacetic acid\", \"Phosphonacetate\", \"Phosphonacetic acid\")"				
-"J05AB06"	"135398740"	"ganciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Citovirax\", \"Cymevan\", \"Cymeven\", \"Cymevene\", \"Cytovene\", \"Cytovene IV\", \"Ganciclovir\", \"Ganciclovirum\", \"Gancyclovir\", \"Hydroxyacyclovir\", \"Virgan\", \"Vitrasert\", \"Zirgan\")"	"3"	"g"	"0.5"	"g"
+"J05AX07"	16130199	"enfuvirtide"	"Other antivirals"	"c(\"Enfurvitide\", \"Enfuvirtide\", \"Fuzeon\", \"Pentafuside\")"			0.18	"g"
+"J05AX17"	10089466	"enisamium iodide"	"Other antivirals"	"Enisamium iodide"	1.5	"g"		
+"J05AF10"	135398508	"entecavir"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Baraclude\", \"Entecavir\", \"Entecavir anhydrous\", \"Entecavirum\")"	0.5	"mg"		
+"J05AG04"	193962	"etravirine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"DAPY deriv\", \"Etravine\", \"Etravirine\", \"Intelence\")"	0.4	"g"		
+"J05AP04"	42601552	"faldaprevir"	"Antivirals for treatment of HCV infections"	"Faldaprevir"				
+"J05AB09"	3324	"famciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Famciclovir\", \"Famciclovirum\", \"Famvir\", \"Oravir\")"	0.75	"g"		
+"J05AE07"	131536	"fosamprenavir"	"Protease inhibitors"	"c(\"Amprenavir phosphate\", \"Fosamprenavir\", \"Lexiva\", \"Telzir\")"	1.4	"g"		
+"J05AD01"	3415	"foscarnet"	"Phosphonic acid derivatives"	"c(\"Forscarnet\", \"Forscarnet sodium\", \"Foscarmet\", \"Foscarnet\", \"Phosphonoformate\", \"Phosphonoformic acid\")"			6.5	"g"
+"J05AD02"	546	"fosfonet"	"Phosphonic acid derivatives"	"c(\"Fosfonet\", \"Fosfonet sodium\", \"Fosfonet Sodium\", \"Fosfonoacetate\", \"Fosfonoacetic acid\", \"Phosphonacetate\", \"Phosphonacetic acid\")"				
+"J05AB06"	135398740	"ganciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Citovirax\", \"Cymevan\", \"Cymeven\", \"Cymevene\", \"Cytovene\", \"Cytovene IV\", \"Ganciclovir\", \"Ganciclovirum\", \"Gancyclovir\", \"Hydroxyacyclovir\", \"Virgan\", \"Vitrasert\", \"Zirgan\")"	3	"g"	0.5	"g"
 "J05AP57"		"glecaprevir and pibrentasvir"	"Antivirals for treatment of HCV infections"	""				
 "J05AX23"		"ibalizumab"	"Other antivirals"	""				
-"J05AB02"	"5905"	"idoxuridine"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Antizona\", \"Dendrid\", \"Emanil\", \"Heratil\", \"Herpesil\", \"Herpid\", \"Herpidu\", \"Herplex\", \"HERPLEX\", \"Herplex liquifilm\", \"Idexur\", \"Idossuridina\", \"Idoxene\", \"Idoxuridin\", \"Idoxuridina\", \"Idoxuridine\", \"Idoxuridinum\", \"Idu Oculos\", \"Iducher\", \"Idulea\", \"Iduoculos\", \"Iduridin\", \"Iduviran\", \"Iododeoxyridine\", \"Iododeoxyuridine\", \"Iodoxuridine\", \"Joddeoxiuridin\", \"Kerecid\", \"Kerecide\", \"Ophthalmadine\", \"Spectanefran\", \"Stoxil\", \"Synmiol\", \"Virudox\")"				
-"J05AE02"	"5362440"	"indinavir"	"Protease inhibitors"	"c(\"Compound J\", \"Crixivan\", \"Indinavir\", \"Indinavir anhydrous\", \"Propolis+Indinavir\")"	"2.4"	"g"		
-"J05AX05"	"135449284"	"inosine pranobex"	"Other antivirals"	"c(\"Aviral\", \"Delimmun\", \"Immunovir\", \"Imunovir\", \"Inosine pranobex\", \"Inosiplex\", \"Isoprinosin\", \"Isoprinosina\", \"Isoprinosine\", \"Isoviral\", \"Methisoprinol\", \"Methysoprinol\", \"Metisoprinol\", \"Viruxan\")"	"3"	"g"		
-"J05AF05"	"60825"	"lamivudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Epivir\", \"Hepitec\", \"Heptivir\", \"Heptodin\", \"Heptovir\", \"Lamivir\", \"Lamivudin\", \"Lamivudina\", \"Lamivudine\", \"Lamivudinum\", \"Zeffix\")"	"0.3"	"g"		
+"J05AB02"	5905	"idoxuridine"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Antizona\", \"Dendrid\", \"Emanil\", \"Heratil\", \"Herpesil\", \"Herpid\", \"Herpidu\", \"Herplex\", \"HERPLEX\", \"Herplex liquifilm\", \"Idexur\", \"Idossuridina\", \"Idoxene\", \"Idoxuridin\", \"Idoxuridina\", \"Idoxuridine\", \"Idoxuridinum\", \"Idu Oculos\", \"Iducher\", \"Idulea\", \"Iduoculos\", \"Iduridin\", \"Iduviran\", \"Iododeoxyridine\", \"Iododeoxyuridine\", \"Iodoxuridine\", \"Joddeoxiuridin\", \"Kerecid\", \"Kerecide\", \"Ophthalmadine\", \"Spectanefran\", \"Stoxil\", \"Synmiol\", \"Virudox\")"				
+"J05AE02"	5362440	"indinavir"	"Protease inhibitors"	"c(\"Compound J\", \"Crixivan\", \"Indinavir\", \"Indinavir anhydrous\", \"Propolis+Indinavir\")"	2.4	"g"		
+"J05AX05"	135449284	"inosine pranobex"	"Other antivirals"	"c(\"Aviral\", \"Delimmun\", \"Immunovir\", \"Imunovir\", \"Inosine pranobex\", \"Inosiplex\", \"Isoprinosin\", \"Isoprinosina\", \"Isoprinosine\", \"Isoviral\", \"Methisoprinol\", \"Methysoprinol\", \"Metisoprinol\", \"Viruxan\")"	3	"g"		
+"J05AF05"	60825	"lamivudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Epivir\", \"Hepitec\", \"Heptivir\", \"Heptodin\", \"Heptovir\", \"Lamivir\", \"Lamivudin\", \"Lamivudina\", \"Lamivudine\", \"Lamivudinum\", \"Zeffix\")"	0.3	"g"		
 "J05AR02"		"lamivudine and abacavir"	"Antivirals for treatment of HIV infections, combinations"	""				
-"J05AR16"	"73386700"	"lamivudine and raltegravir"	"Antivirals for treatment of HIV infections, combinations"	""				
+"J05AR16"	73386700	"lamivudine and raltegravir"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR12"		"lamivudine and tenofovir disoproxil"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR13"		"lamivudine, abacavir and dolutegravir"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR24"		"lamivudine, tenofovir disoproxil and doravirine"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR11"		"lamivudine, tenofovir disoproxil and efavirenz"	"Antivirals for treatment of HIV infections, combinations"	""				
-"J05AX18"	"45138674"	"letermovir"	"Other antivirals"	"c(\"Letermovir\", \"Prevymis\")"	"0.48"	"g"	"0.48"	"g"
-"J05AR10"	"11979606"	"lopinavir and ritonavir"	"Antivirals for treatment of HIV infections, combinations"	"c(\"Aluvia\", \"Kaletra\")"	"0.8"	"g"		
-"J05AX02"	"24839946"	"lysozyme"	"Other antivirals"	"c(\"Lysozyme chloride\", \"Lysozyme Chloride\", \"Lysozyme G\")"				
-"J05AX09"	"3002977"	"maraviroc"	"Other antivirals"	"c(\"Celsentri\", \"Maraviroc\", \"Selzentry\")"	"0.6"	"g"		
-"J05AX10"	"471161"	"maribavir"	"Other antivirals"	"c(\"Benzimidavir\", \"Camvia\", \"Maribavir\")"				
-"J05AA01"	"667492"	"metisazone"	"Thiosemicarbazones"	"c(\"Kemoviran\", \"Marboran\", \"Marborane\", \"Methisazon\", \"Methisazone\", \"Methsazone\", \"Metisazon\", \"Metisazona\", \"Metisazone\", \"Metisazonum\", \"Viruzona\")"				
-"J05AX01"	"71655"	"moroxydine"	"Other antivirals"	"c(\"Bimolin\", \"Flumidine\", \"Influmine\", \"Moroxidina\", \"Moroxydine\", \"Moroxydinum\", \"Vironil\", \"Virugon\", \"Virumin\", \"Wirumin\")"	"0.3"	"g"		
-"J05AE04"	"64143"	"nelfinavir"	"Protease inhibitors"	"c(\"Nelfinavir\", \"Viracept\")"	"2.25"	"g"		
-"J05AG01"	"4463"	"nevirapine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"Nevirapine\", \"Nevirapine anhydrous\", \"Viramune\", \"Viramune IR\", \"Viramune XR\")"	"0.4"	"g"		
+"J05AX18"	45138674	"letermovir"	"Other antivirals"	"c(\"Letermovir\", \"Prevymis\")"	0.48	"g"	0.48	"g"
+"J05AR10"	11979606	"lopinavir and ritonavir"	"Antivirals for treatment of HIV infections, combinations"	"c(\"Aluvia\", \"Kaletra\")"	0.8	"g"		
+"J05AX02"	24839946	"lysozyme"	"Other antivirals"	"c(\"Lysozyme chloride\", \"Lysozyme Chloride\", \"Lysozyme G\")"				
+"J05AX09"	3002977	"maraviroc"	"Other antivirals"	"c(\"Celsentri\", \"Maraviroc\", \"Selzentry\")"	0.6	"g"		
+"J05AX10"	471161	"maribavir"	"Other antivirals"	"c(\"Benzimidavir\", \"Camvia\", \"Maribavir\")"				
+"J05AA01"	667492	"metisazone"	"Thiosemicarbazones"	"c(\"Kemoviran\", \"Marboran\", \"Marborane\", \"Methisazon\", \"Methisazone\", \"Methsazone\", \"Metisazon\", \"Metisazona\", \"Metisazone\", \"Metisazonum\", \"Viruzona\")"				
+"J05AX01"	71655	"moroxydine"	"Other antivirals"	"c(\"Bimolin\", \"Flumidine\", \"Influmine\", \"Moroxidina\", \"Moroxydine\", \"Moroxydinum\", \"Vironil\", \"Virugon\", \"Virumin\", \"Wirumin\")"	0.3	"g"		
+"J05AE04"	64143	"nelfinavir"	"Protease inhibitors"	"c(\"Nelfinavir\", \"Viracept\")"	2.25	"g"		
+"J05AG01"	4463	"nevirapine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"Nevirapine\", \"Nevirapine anhydrous\", \"Viramune\", \"Viramune IR\", \"Viramune XR\")"	0.4	"g"		
 "J05AP53"		"ombitasvir, paritaprevir and ritonavir"	"Antivirals for treatment of HCV infections"	""				
-"J05AH02"	"65028"	"oseltamivir"	"Neuraminidase inhibitors"	"c(\"Agucort\", \"Oseltamivir\", \"Tamiflu\", \"Tamvir\")"	"0.15"	"g"		
-"J05AB13"	"135398748"	"penciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Adenovir\", \"Denavir\", \"Penciceovir\", \"Penciclovir\", \"Penciclovirum\", \"Pencyclovir\", \"Vectavir\")"				
-"J05AX21"	"9942657"	"pentanedioic acid imidazolyl ethanamide"	"Other antivirals"	"Ingamine"	"90"	"mg"		
-"J05AH03"	"154234"	"peramivir"	"Neuraminidase inhibitors"	"c(\"PeramiFlu\", \"Peramivir\", \"Rapiacta\", \"RAPIVAB\")"				
-"J05AX06"	"1684"	"pleconaril"	"Other antivirals"	"c(\"Picovir\", \"Pleconaril\", \"Pleconarilis\")"				
-"J05AX08"	"54671008"	"raltegravir"	"Other antivirals"	"c(\"Isentress\", \"Raltegravir\")"	"0.8"	"g"		
-"J05AP01"	"37542"	"ribavirin"	"Antivirals for treatment of HCV infections"	"c(\"Copegus\", \"Cotronak\", \"Drug:  Ribavirin\", \"Ravanex\", \"Rebetol\", \"Rebetron\", \"Rebretron\", \"Ribacine\", \"Ribamide\", \"Ribamidil\", \"Ribamidyl\", \"Ribasphere\", \"Ribavirin\", \"Ribavirin Capsules\", \"Ribavirina\", \"Ribavirine\", \"Ribavirinum\", \"Ribovirin\", \"Tribavirin\", \"Varazid\", \"Vilona\", \"Viramid\", \"Viramide\", \"Virazid\", \"Virazide\", \"Virazole\")"	"1"	"g"		
-"J05AG05"	"6451164"	"rilpivirine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"Edurant\", \"Rilpivirine\")"	"25"	"mg"		
-"J05AC02"	"5071"	"rimantadine"	"Cyclic amines"	"c(\"Remantadine\", \"Riamantadine\", \"Rimant\", \"RIMANTADIN\", \"Rimantadin A\", \"Rimantadina\", \"Rimantadine\", \"Rimantadinum\")"	"0.2"	"g"		
-"J05AE03"	"392622"	"ritonavir"	"Protease inhibitors"	"c(\"Norvir\", \"Norvir Sec\", \"Norvir Softgel\", \"Ritonavir\", \"Ritonavire\", \"Ritonavirum\")"	"1.2"	"g"		
-"J05AE01"	"441243"	"saquinavir"	"Protease inhibitors"	"c(\"Fortovase\", \"Invirase\", \"Saquinavir\")"	"1.8"	"g"		
-"J05AP05"	"24873435"	"simeprevir"	"Antivirals for treatment of HCV infections"	"c(\"Olysio\", \"Simeprevir sodium\")"	"0.15"	"g"		
-"J05AP08"	"45375808"	"sofosbuvir"	"Antivirals for treatment of HCV infections"	"c(\"Hepcinat\", \"Hepcvir\", \"Sofosbuvir\", \"Sovaldi\", \"SOVALDI\", \"SoviHep\")"	"0.4"	"g"		
-"J05AP51"	"72734365"	"sofosbuvir and ledipasvir"	"Antivirals for treatment of HCV infections"	""				
-"J05AP55"	"91885554"	"sofosbuvir and velpatasvir"	"Antivirals for treatment of HCV infections"	"Epclusa Tablet"				
+"J05AH02"	65028	"oseltamivir"	"Neuraminidase inhibitors"	"c(\"Agucort\", \"Oseltamivir\", \"Tamiflu\", \"Tamvir\")"	0.15	"g"		
+"J05AB13"	135398748	"penciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Adenovir\", \"Denavir\", \"Penciceovir\", \"Penciclovir\", \"Penciclovirum\", \"Pencyclovir\", \"Vectavir\")"				
+"J05AX21"	9942657	"pentanedioic acid imidazolyl ethanamide"	"Other antivirals"	"Ingamine"	90	"mg"		
+"J05AH03"	154234	"peramivir"	"Neuraminidase inhibitors"	"c(\"PeramiFlu\", \"Peramivir\", \"Rapiacta\", \"RAPIVAB\")"				
+"J05AX06"	1684	"pleconaril"	"Other antivirals"	"c(\"Picovir\", \"Pleconaril\", \"Pleconarilis\")"				
+"J05AX08"	54671008	"raltegravir"	"Other antivirals"	"c(\"Isentress\", \"Raltegravir\")"	0.8	"g"		
+"J05AP01"	37542	"ribavirin"	"Antivirals for treatment of HCV infections"	"c(\"Copegus\", \"Cotronak\", \"Drug:  Ribavirin\", \"Ravanex\", \"Rebetol\", \"Rebetron\", \"Rebretron\", \"Ribacine\", \"Ribamide\", \"Ribamidil\", \"Ribamidyl\", \"Ribasphere\", \"Ribavirin\", \"Ribavirin Capsules\", \"Ribavirina\", \"Ribavirine\", \"Ribavirinum\", \"Ribovirin\", \"Tribavirin\", \"Varazid\", \"Vilona\", \"Viramid\", \"Viramide\", \"Virazid\", \"Virazide\", \"Virazole\")"	1	"g"		
+"J05AG05"	6451164	"rilpivirine"	"Non-nucleoside reverse transcriptase inhibitors"	"c(\"Edurant\", \"Rilpivirine\")"	25	"mg"		
+"J05AC02"	5071	"rimantadine"	"Cyclic amines"	"c(\"Remantadine\", \"Riamantadine\", \"Rimant\", \"RIMANTADIN\", \"Rimantadin A\", \"Rimantadina\", \"Rimantadine\", \"Rimantadinum\")"	0.2	"g"		
+"J05AE03"	392622	"ritonavir"	"Protease inhibitors"	"c(\"Norvir\", \"Norvir Sec\", \"Norvir Softgel\", \"Ritonavir\", \"Ritonavire\", \"Ritonavirum\")"	1.2	"g"		
+"J05AE01"	441243	"saquinavir"	"Protease inhibitors"	"c(\"Fortovase\", \"Invirase\", \"Saquinavir\")"	1.8	"g"		
+"J05AP05"	24873435	"simeprevir"	"Antivirals for treatment of HCV infections"	"c(\"Olysio\", \"Simeprevir sodium\")"	0.15	"g"		
+"J05AP08"	45375808	"sofosbuvir"	"Antivirals for treatment of HCV infections"	"c(\"Hepcinat\", \"Hepcvir\", \"Sofosbuvir\", \"Sovaldi\", \"SOVALDI\", \"SoviHep\")"	0.4	"g"		
+"J05AP51"	72734365	"sofosbuvir and ledipasvir"	"Antivirals for treatment of HCV infections"	""				
+"J05AP55"	91885554	"sofosbuvir and velpatasvir"	"Antivirals for treatment of HCV infections"	"Epclusa Tablet"				
 "J05AP56"		"sofosbuvir, velpatasvir and voxilaprevir"	"Antivirals for treatment of HCV infections"	""				
-"J05AF04"	"18283"	"stavudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Estavudina\", \"Sanilvudine\", \"Stavudin\", \"Stavudine\", \"Stavudinum\", \"Zerit Xr\", \"Zerut XR\")"	"80"	"mg"		
-"J05AR07"	"15979285"	"stavudine, lamivudine and nevirapine"	"Antivirals for treatment of HIV infections, combinations"	"STAVUDIINE"				
-"J05AP02"	"3010818"	"telaprevir"	"Antivirals for treatment of HCV infections"	"c(\"Incivek\", \"Incivo\", \"Telaprevir\", \"Telavic\")"	"2.25"	"g"		
-"J05AF11"	"159269"	"telbivudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Epavudine\", \"Sebivo\", \"Telbivudin\", \"Telbivudine\", \"Tyzeka\")"	"0.6"	"g"		
-"J05AF13"	"9574768"	"tenofovir alafenamide"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"Vemlidy"	"25"	"mg"		
-"J05AF07"	"5481350"	"tenofovir disoproxil"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"BisPMPA\", \"PMPA prodrug\", \"Tenofovir\", \"Viread\")"	"0.245"	"g"		
+"J05AF04"	18283	"stavudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Estavudina\", \"Sanilvudine\", \"Stavudin\", \"Stavudine\", \"Stavudinum\", \"Zerit Xr\", \"Zerut XR\")"	80	"mg"		
+"J05AR07"	15979285	"stavudine, lamivudine and nevirapine"	"Antivirals for treatment of HIV infections, combinations"	"STAVUDIINE"				
+"J05AP02"	3010818	"telaprevir"	"Antivirals for treatment of HCV infections"	"c(\"Incivek\", \"Incivo\", \"Telaprevir\", \"Telavic\")"	2.25	"g"		
+"J05AF11"	159269	"telbivudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Epavudine\", \"Sebivo\", \"Telbivudin\", \"Telbivudine\", \"Tyzeka\")"	0.6	"g"		
+"J05AF13"	9574768	"tenofovir alafenamide"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"Vemlidy"	25	"mg"		
+"J05AF07"	5481350	"tenofovir disoproxil"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"BisPMPA\", \"PMPA prodrug\", \"Tenofovir\", \"Viread\")"	0.245	"g"		
 "J05AR03"		"tenofovir disoproxil and emtricitabine"	"Antivirals for treatment of HIV infections, combinations"	""				
-"J05AX19"	"5475"	"tilorone"	"Other antivirals"	"c(\"Amiksin\", \"Amixin\", \"Amixin IC\", \"Amyxin\", \"Tiloron\", \"Tilorona\", \"Tilorone\", \"Tiloronum\")"	"0.125"	"g"		
-"J05AE09"	"54682461"	"tipranavir"	"Protease inhibitors"	"c(\"Aptivus\", \"Tipranavir\")"	"1"	"g"		
-"J05AC03"	"64377"	"tromantadine"	"Cyclic amines"	"c(\"Tromantadina\", \"Tromantadine\", \"Tromantadinum\", \"Viruserol\")"				
-"J05AX13"	"131411"	"umifenovir"	"Other antivirals"	"c(\"Arbidol\", \"Arbidol base\", \"Umifenovir\")"	"0.8"	"g"		
-"J05AB11"	"135398742"	"valaciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Talavir\", \"Valaciclovir\", \"Valaciclovirum\", \"ValACV\", \"Valcivir\", \"Valcyclovir\", \"Valtrex\", \"Virval\", \"Zelitrex\")"	"3"	"g"		
-"J05AB14"	"135413535"	"valganciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Cymeval\", \"Valganciclovir\")"	"0.9"	"g"		
-"J05AB03"	"21704"	"vidarabine"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Adenine arabinoside\", \"Araadenosine\", \"Arabinoside adenine\", \"Arabinosyl adenine\", \"Arabinosyladenine\", \"Spongoadenosine\", \"Vidarabin\", \"Vidarabina\", \"Vidarabine\", \"Vidarabine anhydrous\", \"Vidarabinum\", \"Vira A\", \"Vira ATM\")"				
-"J05AF03"	"24066"	"zalcitabine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Dideoxycytidine\", \"Interferon AD + ddC\", \"Zalcitabine\", \"Zalcitibine\")"	"2.25"	"mg"		
-"J05AH01"	"60855"	"zanamivir"	"Neuraminidase inhibitors"	"c(\"MODIFIED SIALIC ACID\", \"Relenza\", \"Zanamavir\", \"Zanamir\", \"Zanamivi\", \"Zanamivir\", \"Zanamivir hydrate\")"				
-"J05AF01"	"35370"	"zidovudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Azidothymidine\", \"AZT Antiviral\", \"Beta interferon\", \"Compound S\", \"Propolis+AZT\", \"Retrovir\", \"Zidovudina\", \"Zidovudine\", \"ZIDOVUDINE\", \"Zidovudine EP III\", \"Zidovudinum\")"	"0.6"	"g"	"0.6"	"g"
+"J05AX19"	5475	"tilorone"	"Other antivirals"	"c(\"Amiksin\", \"Amixin\", \"Amixin IC\", \"Amyxin\", \"Tiloron\", \"Tilorona\", \"Tilorone\", \"Tiloronum\")"	0.125	"g"		
+"J05AE09"	54682461	"tipranavir"	"Protease inhibitors"	"c(\"Aptivus\", \"Tipranavir\")"	1	"g"		
+"J05AC03"	64377	"tromantadine"	"Cyclic amines"	"c(\"Tromantadina\", \"Tromantadine\", \"Tromantadinum\", \"Viruserol\")"				
+"J05AX13"	131411	"umifenovir"	"Other antivirals"	"c(\"Arbidol\", \"Arbidol base\", \"Umifenovir\")"	0.8	"g"		
+"J05AB11"	135398742	"valaciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Talavir\", \"Valaciclovir\", \"Valaciclovirum\", \"ValACV\", \"Valcivir\", \"Valcyclovir\", \"Valtrex\", \"Virval\", \"Zelitrex\")"	3	"g"		
+"J05AB14"	135413535	"valganciclovir"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Cymeval\", \"Valganciclovir\")"	0.9	"g"		
+"J05AB03"	21704	"vidarabine"	"Nucleosides and nucleotides excl. reverse transcriptase inhibitors"	"c(\"Adenine arabinoside\", \"Araadenosine\", \"Arabinoside adenine\", \"Arabinosyl adenine\", \"Arabinosyladenine\", \"Spongoadenosine\", \"Vidarabin\", \"Vidarabina\", \"Vidarabine\", \"Vidarabine anhydrous\", \"Vidarabinum\", \"Vira A\", \"Vira ATM\")"				
+"J05AF03"	24066	"zalcitabine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Dideoxycytidine\", \"Interferon AD + ddC\", \"Zalcitabine\", \"Zalcitibine\")"	2.25	"mg"		
+"J05AH01"	60855	"zanamivir"	"Neuraminidase inhibitors"	"c(\"MODIFIED SIALIC ACID\", \"Relenza\", \"Zanamavir\", \"Zanamir\", \"Zanamivi\", \"Zanamivir\", \"Zanamivir hydrate\")"				
+"J05AF01"	35370	"zidovudine"	"Nucleoside and nucleotide reverse transcriptase inhibitors"	"c(\"Azidothymidine\", \"AZT Antiviral\", \"Beta interferon\", \"Compound S\", \"Propolis+AZT\", \"Retrovir\", \"Zidovudina\", \"Zidovudine\", \"ZIDOVUDINE\", \"Zidovudine EP III\", \"Zidovudinum\")"	0.6	"g"	0.6	"g"
 "J05AR01"		"zidovudine and lamivudine"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR04"		"zidovudine, lamivudine and abacavir"	"Antivirals for treatment of HIV infections, combinations"	""				
 "J05AR05"		"zidovudine, lamivudine and nevirapine"	"Antivirals for treatment of HIV infections, combinations"	""				
--- a/data-raw/antivirals.xlsx
+++ b/data-raw/antivirals.xlsx
--- a/data-raw/internals.R
+++ b/data-raw/internals.R
@ -73,13 +73,41 @@ rm(microorganisms.translation)
 usethis::ui_done(paste0("Saving raw data to {usethis::ui_value('/data-raw/')}"))
 devtools::load_all(quiet = TRUE)
 # give official names to ABs and MOs
-write.table(dplyr::mutate(rsi_translation, ab = ab_name(ab), mo = mo_name(mo)),
-            "data-raw/rsi_translation.txt", sep = "\t", na = "", row.names = FALSE)
-write.table(dplyr::mutate_if(microorganisms, ~!is.numeric(.), as.character),
-            "data-raw/microorganisms.txt", sep = "\t", na = "", row.names = FALSE)
-write.table(dplyr::mutate_if(antibiotics, ~!is.numeric(.), as.character),
-            "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE)
-write.table(dplyr::mutate_all(antivirals, as.character),
-            "data-raw/antivirals.txt", sep = "\t", na = "", row.names = FALSE)
-write.table(intrinsic_resistant,
-            "data-raw/intrinsic_resistant.txt", sep = "\t", na = "", row.names = FALSE)
+rsi <- dplyr::mutate(rsi_translation, ab = ab_name(ab), mo = mo_name(mo))
+saveRDS(rsi, "data-raw/rsi_translation.rds", version = 2)
+write.table(rsi, "data-raw/rsi_translation.txt", sep = "\t", na = "", row.names = FALSE)
+haven::write_sas(rsi, "data-raw/rsi_translation.sas")
+haven::write_sav(rsi, "data-raw/rsi_translation.sav")
+haven::write_dta(rsi, "data-raw/rsi_translation.dta")
+openxlsx::write.xlsx(rsi, "data-raw/rsi_translation.xlsx")
+
+mo <- dplyr::mutate_if(microorganisms, ~!is.numeric(.), as.character)
+saveRDS(mo, "data-raw/microorganisms.rds", version = 2)
+write.table(mo, "data-raw/microorganisms.txt", sep = "\t", na = "", row.names = FALSE)
+haven::write_sas(mo, "data-raw/microorganisms.sas")
+haven::write_sav(mo, "data-raw/microorganisms.sav")
+haven::write_dta(mo, "data-raw/microorganisms.dta")
+openxlsx::write.xlsx(mo, "data-raw/microorganisms.xlsx")
+
+ab <- dplyr::mutate_if(antibiotics, ~!is.numeric(.), as.character)
+saveRDS(ab, "data-raw/antibiotics.rds", version = 2)
+write.table(ab, "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE)
+haven::write_sas(ab, "data-raw/antibiotics.sas")
+haven::write_sav(ab, "data-raw/antibiotics.sav")
+haven::write_dta(ab, "data-raw/antibiotics.dta")
+openxlsx::write.xlsx(ab, "data-raw/antibiotics.xlsx")
+
+av <- dplyr::mutate_if(antivirals, ~!is.numeric(.), as.character)
+saveRDS(av, "data-raw/antivirals.rds", version = 2)
+write.table(av, "data-raw/antivirals.txt", sep = "\t", na = "", row.names = FALSE)
+haven::write_sas(av, "data-raw/antivirals.sas")
+haven::write_sav(av, "data-raw/antivirals.sav")
+haven::write_dta(av, "data-raw/antivirals.dta")
+openxlsx::write.xlsx(av, "data-raw/antivirals.xlsx")
+
+saveRDS(intrinsic_resistant, "data-raw/intrinsic_resistant.rds", version = 2)
+write.table(intrinsic_resistant, "data-raw/intrinsic_resistant.txt", sep = "\t", na = "", row.names = FALSE)
+haven::write_sas(intrinsic_resistant, "data-raw/intrinsic_resistant.sas")
+haven::write_sav(intrinsic_resistant, "data-raw/intrinsic_resistant.sav")
+haven::write_dta(intrinsic_resistant, "data-raw/intrinsic_resistant.dta")
+openxlsx::write.xlsx(intrinsic_resistant, "data-raw/intrinsic_resistant.xlsx")
--- a/data-raw/intrinsic_resistant.dta
+++ b/data-raw/intrinsic_resistant.dta
--- a/data-raw/intrinsic_resistant.rds
+++ b/data-raw/intrinsic_resistant.rds
--- a/data-raw/intrinsic_resistant.sas
+++ b/data-raw/intrinsic_resistant.sas
--- a/data-raw/intrinsic_resistant.sav
+++ b/data-raw/intrinsic_resistant.sav
--- a/data-raw/intrinsic_resistant.xlsx
+++ b/data-raw/intrinsic_resistant.xlsx
--- a/data-raw/microorganisms.dta
+++ b/data-raw/microorganisms.dta
--- a/data-raw/microorganisms.rds
+++ b/data-raw/microorganisms.rds
--- a/data-raw/microorganisms.sas
+++ b/data-raw/microorganisms.sas
--- a/data-raw/microorganisms.sav
+++ b/data-raw/microorganisms.sav
--- a/data-raw/microorganisms.xlsx
+++ b/data-raw/microorganisms.xlsx
--- a/data-raw/rsi_translation.dta
+++ b/data-raw/rsi_translation.dta
--- a/data-raw/rsi_translation.rds
+++ b/data-raw/rsi_translation.rds
--- a/data-raw/rsi_translation.sas
+++ b/data-raw/rsi_translation.sas
--- a/data-raw/rsi_translation.sav
+++ b/data-raw/rsi_translation.sav
--- a/data-raw/rsi_translation.xlsx
+++ b/data-raw/rsi_translation.xlsx
--- 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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -117,6 +117,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="articles/PCA.html">
        <span class="fa fa-compress"></span>
--- 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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -117,6 +117,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="articles/PCA.html">
        <span class="fa fa-compress"></span>
--- a/docs/articles/datasets.html
+++ b/docs/articles/datasets.html
@ -0,0 +1,958 @@
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+        <span class="fa fa-dice"></span>
+         
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+      </a>
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+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
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+        <span class="fa fa-skull-crossbones"></span>
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+        <span class="fa fa-globe-americas"></span>
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+      </a>
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+      <a href="../articles/SPSS.html">
+        <span class="fa fa-file-upload"></span>
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+        <span class="fa fa-exchange-alt"></span>
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+        <span class="fa fa-bug"></span>
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+      </a>
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+        <span class="fa fa-capsules"></span>
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+  <div class="col-md-9 contents">
+    <div class="page-header toc-ignore">
+      <h1 data-toc-skip>Data sets for download</h1>
+            
+      
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/datasets.Rmd"><code>vignettes/datasets.Rmd</code></a></small>
+      <div class="hidden name"><code>datasets.Rmd</code></div>
+
+    </div>
+
+    
+    
+<p>This package contains a lot of reference data sets that are all reliable, up-to-date and free to download. You can even use them outside of R, for example to train your laboratory information system (LIS) about intrinsic resistance!</p>
+<p>We included them in our <code>AMR</code> package, but also automatically ‘mirror’ them to our public repository in different software formats. On this page, we explain how to download them and how the structure of the data sets look like. The tab separated files <strong>allow for machine reading taxonomic data and EUCAST and CLSI interpretation guidelines</strong>, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI.</p>
+<p><em>Note: Years and dates of updates mentioned on this page, are from on <code>AMR</code> package version 1.3.0.9004, online released on 16 August 2020. <strong>If you are reading this page from within R, please <a href="https://msberends.github.io/AMR/articles/datasets.html">visit our website</a> for the latest update.</strong></em></p>
+<div id="microorganisms" class="section level2">
+<h2 class="hasAnchor">
+<a href="#microorganisms" class="anchor"></a>Microorganisms</h2>
+<p>This data set is in R available as <code>microorganisms</code>, after you load the <code>AMR</code> package.</p>
+<div id="source" class="section level4">
+<h4 class="hasAnchor">
+<a href="#source" class="anchor"></a>Source</h4>
+<p>Our full taxonomy of microorganisms is based on the authoritative and comprehensive:</p>
+<ul>
+<li>
+<a href="http://www.catalogueoflife.org">Catalogue of Life</a> (included version: 2019)</li>
+<li>
+<a href="https://lpsn.dsmz.de">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN, included version: May 2020)</li>
+</ul>
+</div>
+<div id="structure" class="section level4">
+<h4 class="hasAnchor">
+<a href="#structure" class="anchor"></a>Structure</h4>
+<p>A data set with 67,151 rows and 16 columns, containing the following column names:</p>
+<p><em>mo, fullname, kingdom, phylum, class, order, family, genus, species, subspecies, rank, ref, species_id, source, prevalence, snomed</em>.</p>
+<p>Included per taxonomic kingdom:</p>
+<table class="table">
+<thead><tr class="header">
+<th align="center">Kingdom</th>
+<th align="center">Number of (sub)species</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td align="center">(unknown kingdom)</td>
+<td align="center">1</td>
+</tr>
+<tr class="even">
+<td align="center">Animalia</td>
+<td align="center">2,153</td>
+</tr>
+<tr class="odd">
+<td align="center">Archaea</td>
+<td align="center">697</td>
+</tr>
+<tr class="even">
+<td align="center">Bacteria</td>
+<td align="center">19,244</td>
+</tr>
+<tr class="odd">
+<td align="center">Chromista</td>
+<td align="center">32,164</td>
+</tr>
+<tr class="even">
+<td align="center">Fungi</td>
+<td align="center">9,582</td>
+</tr>
+</tbody>
+</table>
+</div>
+<div id="download" class="section level4">
+<h4 class="hasAnchor">
+<a href="#download" class="anchor"></a>Download</h4>
+<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 28 July 2020 20:52:40 CEST.</p>
+<ul>
+<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.rds">from GitLab</a> (file size: 2.7 MB)</p></li>
+<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.xlsx">from GitLab</a> (file size: 6.1 MB)</p></li>
+<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.sav">from GitLab</a> (file size: 28.2 MB)</p></li>
+<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.sav">from GitLab</a> (file size: 28.2 MB)</p></li>
+<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.dta">from GitLab</a> (file size: 25.2 MB)</p></li>
+<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.txt">from GitLab</a> (file size: 13.3 MB)</p></li>
+</ul>
+</div>
+<div id="example" class="section level4">
+<h4 class="hasAnchor">
+<a href="#example" class="anchor"></a>Example</h4>
+<p>Example rows when filtering on genus <em>Escherichia</em>:</p>
+<table class="table">
+<colgroup>
+<col width="5%">
+<col width="9%">
+<col width="3%">
+<col width="6%">
+<col width="8%">
+<col width="6%">
+<col width="7%">
+<col width="5%">
+<col width="4%">
+<col width="4%">
+<col width="3%">
+<col width="9%">
+<col width="13%">
+<col width="3%">
+<col width="4%">
+<col width="4%">
+</colgroup>
+<thead><tr class="header">
+<th align="center">mo</th>
+<th align="center">fullname</th>
+<th align="center">kingdom</th>
+<th align="center">phylum</th>
+<th align="center">class</th>
+<th align="center">order</th>
+<th align="center">family</th>
+<th align="center">genus</th>
+<th align="center">species</th>
+<th align="center">subspecies</th>
+<th align="center">rank</th>
+<th align="center">ref</th>
+<th align="center">species_id</th>
+<th align="center">source</th>
+<th align="center">prevalence</th>
+<th align="center">snomed</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td align="center">B_ESCHR</td>
+<td align="center">Escherichia</td>
+<td align="center">Bacteria</td>
+<td align="center">Proteobacteria</td>
+<td align="center">Gammaproteobacteria</td>
+<td align="center">Enterobacterales</td>
+<td align="center">Enterobacteriaceae</td>
+<td align="center">Escherichia</td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center">genus</td>
+<td align="center"></td>
+<td align="center">bc4fdde6867d5ecfc728000b0bfb49a3</td>
+<td align="center">CoL</td>
+<td align="center">1</td>
+<td align="center">64735005</td>
+</tr>
+<tr class="even">
+<td align="center">B_ESCHR_ALBR</td>
+<td align="center">Escherichia albertii</td>
+<td align="center">Bacteria</td>
+<td align="center">Proteobacteria</td>
+<td align="center">Gammaproteobacteria</td>
+<td align="center">Enterobacterales</td>
+<td align="center">Enterobacteriaceae</td>
+<td align="center">Escherichia</td>
+<td align="center">albertii</td>
+<td align="center"></td>
+<td align="center">species</td>
+<td align="center">Huys et al., 2003</td>
+<td align="center">36618b1ed3b8b7e5a61f40eb9386e63c</td>
+<td align="center">CoL</td>
+<td align="center">1</td>
+<td align="center">419388003</td>
+</tr>
+<tr class="odd">
+<td align="center">B_ESCHR_COLI</td>
+<td align="center">Escherichia coli</td>
+<td align="center">Bacteria</td>
+<td align="center">Proteobacteria</td>
+<td align="center">Gammaproteobacteria</td>
+<td align="center">Enterobacterales</td>
+<td align="center">Enterobacteriaceae</td>
+<td align="center">Escherichia</td>
+<td align="center">coli</td>
+<td align="center"></td>
+<td align="center">species</td>
+<td align="center">Castellani et al., 1919</td>
+<td align="center">3254b3db31bf16fdde669ac57bf8c4fe</td>
+<td align="center">CoL</td>
+<td align="center">1</td>
+<td align="center">112283007</td>
+</tr>
+<tr class="even">
+<td align="center">B_ESCHR_FRGS</td>
+<td align="center">Escherichia fergusonii</td>
+<td align="center">Bacteria</td>
+<td align="center">Proteobacteria</td>
+<td align="center">Gammaproteobacteria</td>
+<td align="center">Enterobacterales</td>
+<td align="center">Enterobacteriaceae</td>
+<td align="center">Escherichia</td>
+<td align="center">fergusonii</td>
+<td align="center"></td>
+<td align="center">species</td>
+<td align="center">Farmer et al., 1985</td>
+<td align="center">82d98b10c456ce5f4c8c515f4e1567e2</td>
+<td align="center">CoL</td>
+<td align="center">1</td>
+<td align="center">72461005</td>
+</tr>
+<tr class="odd">
+<td align="center">B_ESCHR_HRMN</td>
+<td align="center">Escherichia hermannii</td>
+<td align="center">Bacteria</td>
+<td align="center">Proteobacteria</td>
+<td align="center">Gammaproteobacteria</td>
+<td align="center">Enterobacterales</td>
+<td align="center">Enterobacteriaceae</td>
+<td align="center">Escherichia</td>
+<td align="center">hermannii</td>
+<td align="center"></td>
+<td align="center">species</td>
+<td align="center">Brenner et al., 1983</td>
+<td align="center">b16086aee36e3b46b565510083ab4b65</td>
+<td align="center">CoL</td>
+<td align="center">1</td>
+<td align="center">85786000</td>
+</tr>
+<tr class="even">
+<td align="center">B_ESCHR_MRMT</td>
+<td align="center">Escherichia marmotae</td>
+<td align="center">Bacteria</td>
+<td align="center">Proteobacteria</td>
+<td align="center">Gammaproteobacteria</td>
+<td align="center">Enterobacterales</td>
+<td align="center">Enterobacteriaceae</td>
+<td align="center">Escherichia</td>
+<td align="center">marmotae</td>
+<td align="center"></td>
+<td align="center">species</td>
+<td align="center">Liu et al., 2015</td>
+<td align="center">792928</td>
+<td align="center">DSMZ</td>
+<td align="center">1</td>
+<td align="center"></td>
+</tr>
+</tbody>
+</table>
+</div>
+</div>
+<div id="antibiotic-agents" class="section level2">
+<h2 class="hasAnchor">
+<a href="#antibiotic-agents" class="anchor"></a>Antibiotic agents</h2>
+<p>This data set is in R available as <code>antibiotics</code>, after you load the <code>AMR</code> package.</p>
+<div id="source-1" class="section level4">
+<h4 class="hasAnchor">
+<a href="#source-1" class="anchor"></a>Source</h4>
+<p>This data set contains all EARS-Net and ATC codes gathered from WHO and WHONET, and all compound IDs from PubChem. It also contains all brand names (synonyms) as found on PubChem and Defined Daily Doses (DDDs) for oral and parenteral administration.</p>
+<ul>
+<li>
+<a href="https://www.whocc.no/atc_ddd_index/">ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology</a> (note: this may not be used for commercial purposes, but is frelly available from the WHO CC website for personal use)</li>
+<li><a href="https://pubchem.ncbi.nlm.nih.gov">PubChem by the US National Library of Medicine</a></li>
+<li><a href="https://whonet.org">WHONET software 2019</a></li>
+</ul>
+</div>
+<div id="structure-1" class="section level4">
+<h4 class="hasAnchor">
+<a href="#structure-1" class="anchor"></a>Structure</h4>
+<p>A data set with 456 rows and 14 columns, containing the following column names:</p>
+<p><em>ab, atc, cid, name, group, atc_group1, atc_group2, abbreviations, synonyms, oral_ddd, oral_units, iv_ddd, iv_units, loinc</em>.</p>
+</div>
+<div id="download-1" class="section level4">
+<h4 class="hasAnchor">
+<a href="#download-1" class="anchor"></a>Download</h4>
+<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 31 July 2020 12:12:13 CEST.</p>
+<ul>
+<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.rds">from GitLab</a> (file size: 37.3 kB)</p></li>
+<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.xlsx">from GitLab</a> (file size: 64.5 kB)</p></li>
+<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.sav">from GitLab</a> (file size: 1.3 MB)</p></li>
+<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.sav">from GitLab</a> (file size: 1.3 MB)</p></li>
+<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.dta">from GitLab</a> (file size: 321.8 kB)</p></li>
+<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.txt">from GitLab</a> (file size: 146.1 kB)</p></li>
+</ul>
+</div>
+<div id="example-1" class="section level4">
+<h4 class="hasAnchor">
+<a href="#example-1" class="anchor"></a>Example</h4>
+<p>Example rows:</p>
+<table class="table">
+<colgroup>
+<col width="1%">
+<col width="2%">
+<col width="3%">
+<col width="9%">
+<col width="8%">
+<col width="14%">
+<col width="19%">
+<col width="6%">
+<col width="11%">
+<col width="3%">
+<col width="3%">
+<col width="2%">
+<col width="3%">
+<col width="10%">
+</colgroup>
+<thead><tr class="header">
+<th align="center">ab</th>
+<th align="center">atc</th>
+<th align="center">cid</th>
+<th align="center">name</th>
+<th align="center">group</th>
+<th align="center">atc_group1</th>
+<th align="center">atc_group2</th>
+<th align="center">abbreviations</th>
+<th align="center">synonyms</th>
+<th align="center">oral_ddd</th>
+<th align="center">oral_units</th>
+<th align="center">iv_ddd</th>
+<th align="center">iv_units</th>
+<th align="center">loinc</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td align="center">AMK</td>
+<td align="center">J01GB06</td>
+<td align="center">37768</td>
+<td align="center">Amikacin</td>
+<td align="center">Aminoglycosides</td>
+<td align="center">Aminoglycoside antibacterials</td>
+<td align="center">Other aminoglycosides</td>
+<td align="center">ak, ami, amik, …</td>
+<td align="center">amicacin, amikacillin, amikacin, …</td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center">1.0</td>
+<td align="center">g</td>
+<td align="center">13546-7, 15098-7, 17798-0, …</td>
+</tr>
+<tr class="even">
+<td align="center">AMX</td>
+<td align="center">J01CA04</td>
+<td align="center">33613</td>
+<td align="center">Amoxicillin</td>
+<td align="center">Beta-lactams/penicillins</td>
+<td align="center">Beta-lactam antibacterials, penicillins</td>
+<td align="center">Penicillins with extended spectrum</td>
+<td align="center">ac, amox, amx</td>
+<td align="center">actimoxi, amoclen, amolin, …</td>
+<td align="center">1.0</td>
+<td align="center">g</td>
+<td align="center">1.0</td>
+<td align="center">g</td>
+<td align="center">16365-9, 25274-2, 3344-9, …</td>
+</tr>
+<tr class="odd">
+<td align="center">AMC</td>
+<td align="center">J01CR02</td>
+<td align="center">23665637</td>
+<td align="center">Amoxicillin/clavulanic acid</td>
+<td align="center">Beta-lactams/penicillins</td>
+<td align="center">Beta-lactam antibacterials, penicillins</td>
+<td align="center">Combinations of penicillins, incl. beta-lactamase inhibitors</td>
+<td align="center">a/c, amcl, aml, …</td>
+<td align="center">amocla, amoclan, amoclav, …</td>
+<td align="center">1.0</td>
+<td align="center">g</td>
+<td align="center">3.0</td>
+<td align="center">g</td>
+<td align="center"></td>
+</tr>
+<tr class="even">
+<td align="center">AMP</td>
+<td align="center">J01CA01</td>
+<td align="center">6249</td>
+<td align="center">Ampicillin</td>
+<td align="center">Beta-lactams/penicillins</td>
+<td align="center">Beta-lactam antibacterials, penicillins</td>
+<td align="center">Penicillins with extended spectrum</td>
+<td align="center">am, amp, ampi</td>
+<td align="center">acillin, adobacillin, amblosin, …</td>
+<td align="center">2.0</td>
+<td align="center">g</td>
+<td align="center">2.0</td>
+<td align="center">g</td>
+<td align="center">21066-6, 3355-5, 33562-0, …</td>
+</tr>
+<tr class="odd">
+<td align="center">AZM</td>
+<td align="center">J01FA10</td>
+<td align="center">447043</td>
+<td align="center">Azithromycin</td>
+<td align="center">Macrolides/lincosamides</td>
+<td align="center">Macrolides, lincosamides and streptogramins</td>
+<td align="center">Macrolides</td>
+<td align="center">az, azi, azit, …</td>
+<td align="center">aritromicina, azasite, azenil, …</td>
+<td align="center">0.3</td>
+<td align="center">g</td>
+<td align="center">0.5</td>
+<td align="center">g</td>
+<td align="center">16420-2, 25233-8</td>
+</tr>
+<tr class="even">
+<td align="center">CZO</td>
+<td align="center">J01DB04</td>
+<td align="center">33255</td>
+<td align="center">Cefazolin</td>
+<td align="center">Cephalosporins (1st gen.)</td>
+<td align="center">Other beta-lactam antibacterials</td>
+<td align="center">First-generation cephalosporins</td>
+<td align="center">cfz, cfzl, cz, …</td>
+<td align="center">atirin, cefamezin, cefamezine, …</td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center">3.0</td>
+<td align="center">g</td>
+<td align="center">16566-2, 25235-3, 3442-1, …</td>
+</tr>
+</tbody>
+</table>
+</div>
+</div>
+<div id="antiviral-agents" class="section level2">
+<h2 class="hasAnchor">
+<a href="#antiviral-agents" class="anchor"></a>Antiviral agents</h2>
+<p>This data set is in R available as <code>antivirals</code>, after you load the <code>AMR</code> package.</p>
+<div id="source-2" class="section level4">
+<h4 class="hasAnchor">
+<a href="#source-2" class="anchor"></a>Source</h4>
+<p>This data set contains all ATC codes gathered from WHO and all compound IDs from PubChem. It also contains all brand names (synonyms) as found on PubChem and Defined Daily Doses (DDDs) for oral and parenteral administration.</p>
+<ul>
+<li>
+<a href="https://www.whocc.no/atc_ddd_index/">ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology</a> (note: this may not be used for commercial purposes, but is frelly available from the WHO CC website for personal use)</li>
+<li><a href="https://pubchem.ncbi.nlm.nih.gov">PubChem by the US National Library of Medicine</a></li>
+</ul>
+</div>
+<div id="structure-2" class="section level4">
+<h4 class="hasAnchor">
+<a href="#structure-2" class="anchor"></a>Structure</h4>
+<p>A data set with 102 rows and 9 columns, containing the following column names:</p>
+<p><em>atc, cid, name, atc_group, synonyms, oral_ddd, oral_units, iv_ddd, iv_units</em>.</p>
+</div>
+<div id="download-2" class="section level4">
+<h4 class="hasAnchor">
+<a href="#download-2" class="anchor"></a>Download</h4>
+<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 23 November 2019 19:03:43 CET.</p>
+<ul>
+<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.rds">from GitLab</a> (file size: 4.6 kB)</p></li>
+<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.xlsx">from GitLab</a> (file size: 13.6 kB)</p></li>
+<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.sav">from GitLab</a> (file size: 67.7 kB)</p></li>
+<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.sav">from GitLab</a> (file size: 67.7 kB)</p></li>
+<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.dta">from GitLab</a> (file size: 67.2 kB)</p></li>
+<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.txt">from GitLab</a> (file size: 16.2 kB)</p></li>
+</ul>
+</div>
+<div id="example-2" class="section level4">
+<h4 class="hasAnchor">
+<a href="#example-2" class="anchor"></a>Example</h4>
+<p>Example rows:</p>
+<table class="table">
+<colgroup>
+<col width="4%">
+<col width="5%">
+<col width="9%">
+<col width="32%">
+<col width="30%">
+<col width="4%">
+<col width="5%">
+<col width="3%">
+<col width="4%">
+</colgroup>
+<thead><tr class="header">
+<th align="center">atc</th>
+<th align="center">cid</th>
+<th align="center">name</th>
+<th align="center">atc_group</th>
+<th align="center">synonyms</th>
+<th align="center">oral_ddd</th>
+<th align="center">oral_units</th>
+<th align="center">iv_ddd</th>
+<th align="center">iv_units</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td align="center">J05AF06</td>
+<td align="center">441300</td>
+<td align="center">abacavir</td>
+<td align="center">Nucleoside and nucleotide reverse transcriptase inhibitors</td>
+<td align="center">Abacavir, Abacavir sulfate, Ziagen</td>
+<td align="center">0.6</td>
+<td align="center">g</td>
+<td align="center"></td>
+<td align="center"></td>
+</tr>
+<tr class="even">
+<td align="center">J05AB01</td>
+<td align="center">135398513</td>
+<td align="center">aciclovir</td>
+<td align="center">Nucleosides and nucleotides excl. reverse transcriptase inhibitors</td>
+<td align="center">Acicloftal, Aciclovier, Aciclovir, …</td>
+<td align="center">4.0</td>
+<td align="center">g</td>
+<td align="center">4</td>
+<td align="center">g</td>
+</tr>
+<tr class="odd">
+<td align="center">J05AF08</td>
+<td align="center">60871</td>
+<td align="center">adefovir dipivoxil</td>
+<td align="center">Nucleoside and nucleotide reverse transcriptase inhibitors</td>
+<td align="center">Adefovir di ester, Adefovir dipivoxil, Adefovir Dipivoxil, …</td>
+<td align="center">10.0</td>
+<td align="center">mg</td>
+<td align="center"></td>
+<td align="center"></td>
+</tr>
+<tr class="even">
+<td align="center">J05AE05</td>
+<td align="center">65016</td>
+<td align="center">amprenavir</td>
+<td align="center">Protease inhibitors</td>
+<td align="center">Agenerase, Amprenavir, Amprenavirum, …</td>
+<td align="center">1.2</td>
+<td align="center">g</td>
+<td align="center"></td>
+<td align="center"></td>
+</tr>
+<tr class="odd">
+<td align="center">J05AP06</td>
+<td align="center">16076883</td>
+<td align="center">asunaprevir</td>
+<td align="center">Antivirals for treatment of HCV infections</td>
+<td align="center">Asunaprevir, Sunvepra</td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
+</tr>
+<tr class="even">
+<td align="center">J05AE08</td>
+<td align="center">148192</td>
+<td align="center">atazanavir</td>
+<td align="center">Protease inhibitors</td>
+<td align="center">Atazanavir, Atazanavir Base, Latazanavir, …</td>
+<td align="center">0.3</td>
+<td align="center">g</td>
+<td align="center"></td>
+<td align="center"></td>
+</tr>
+</tbody>
+</table>
+</div>
+</div>
+<div id="intrinsic-bacterial-resistance" class="section level2">
+<h2 class="hasAnchor">
+<a href="#intrinsic-bacterial-resistance" class="anchor"></a>Intrinsic bacterial resistance</h2>
+<p>This data set is in R available as <code>intrinsic_resistant</code>, after you load the <code>AMR</code> package.</p>
+<div id="source-3" class="section level4">
+<h4 class="hasAnchor">
+<a href="#source-3" class="anchor"></a>Source</h4>
+<p>This data set contains all defined intrinsic resistance by EUCAST of all bug-drug combinations.</p>
+<p>The data set is based on ‘EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes’, version 3.1, 2016.</p>
+</div>
+<div id="structure-3" class="section level4">
+<h4 class="hasAnchor">
+<a href="#structure-3" class="anchor"></a>Structure</h4>
+<p>A data set with 49,462 rows and 2 columns, containing the following column names:</p>
+<p><em>microorganism, antibiotic</em>.</p>
+</div>
+<div id="download-3" class="section level4">
+<h4 class="hasAnchor">
+<a href="#download-3" class="anchor"></a>Download</h4>
+<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 14 August 2020 14:18:20 CEST.</p>
+<ul>
+<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.rds">from GitLab</a> (file size: 96.6 kB)</p></li>
+<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.xlsx">from GitLab</a> (file size: 0.5 MB)</p></li>
+<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">from GitLab</a> (file size: 4.2 MB)</p></li>
+<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">from GitLab</a> (file size: 4.2 MB)</p></li>
+<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.dta">from GitLab</a> (file size: 3.7 MB)</p></li>
+<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.txt">from GitLab</a> (file size: 1.8 MB)</p></li>
+</ul>
+</div>
+<div id="example-3" class="section level4">
+<h4 class="hasAnchor">
+<a href="#example-3" class="anchor"></a>Example</h4>
+<p>Example rows:</p>
+<table class="table">
+<thead><tr class="header">
+<th align="center">microorganism</th>
+<th align="center">antibiotic</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td align="center">Klebsiella</td>
+<td align="center">Amoxicillin</td>
+</tr>
+<tr class="even">
+<td align="center">Klebsiella</td>
+<td align="center">Ampicillin</td>
+</tr>
+<tr class="odd">
+<td align="center">Klebsiella</td>
+<td align="center">Azithromycin</td>
+</tr>
+<tr class="even">
+<td align="center">Klebsiella</td>
+<td align="center">Clarithromycin</td>
+</tr>
+<tr class="odd">
+<td align="center">Klebsiella</td>
+<td align="center">Daptomycin</td>
+</tr>
+<tr class="even">
+<td align="center">Klebsiella</td>
+<td align="center">Erythromycin</td>
+</tr>
+</tbody>
+</table>
+</div>
+</div>
+<div id="interpretation-from-mic-values-disk-diameters-to-rsi" class="section level2">
+<h2 class="hasAnchor">
+<a href="#interpretation-from-mic-values-disk-diameters-to-rsi" class="anchor"></a>Interpretation from MIC values / disk diameters to R/SI</h2>
+<p>This data set is in R available as <code>rsi_translation</code>, after you load the <code>AMR</code> package.</p>
+<div id="source-4" class="section level4">
+<h4 class="hasAnchor">
+<a href="#source-4" class="anchor"></a>Source</h4>
+<p>This data set contains interpretation rules for MIC values and disk diffusion diameters. Included guidelines are CLSI (2010-2019) and EUCAST (2011-2020).</p>
+</div>
+<div id="structure-4" class="section level4">
+<h4 class="hasAnchor">
+<a href="#structure-4" class="anchor"></a>Structure</h4>
+<p>A data set with 18,650 rows and 10 columns, containing the following column names:</p>
+<p><em>guideline, method, site, mo, ab, ref_tbl, disk_dose, breakpoint_S, breakpoint_R, uti</em>.</p>
+</div>
+<div id="download-4" class="section level4">
+<h4 class="hasAnchor">
+<a href="#download-4" class="anchor"></a>Download</h4>
+<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 29 July 2020 13:12:34 CEST.</p>
+<ul>
+<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.rds">from GitLab</a> (file size: 55.1 kB)</p></li>
+<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.xlsx">from GitLab</a> (file size: 0.6 MB)</p></li>
+<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.sav">from GitLab</a> (file size: 3.4 MB)</p></li>
+<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.sav">from GitLab</a> (file size: 3.4 MB)</p></li>
+<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.dta">from GitLab</a> (file size: 3 MB)</p></li>
+<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.txt">from GitLab</a> (file size: 1.5 MB)</p></li>
+</ul>
+</div>
+<div id="example-4" class="section level4">
+<h4 class="hasAnchor">
+<a href="#example-4" class="anchor"></a>Example</h4>
+<p>Example rows:</p>
+<table class="table">
+<colgroup>
+<col width="8%">
+<col width="5%">
+<col width="4%">
+<col width="12%">
+<col width="20%">
+<col width="17%">
+<col width="7%">
+<col width="9%">
+<col width="9%">
+<col width="4%">
+</colgroup>
+<thead><tr class="header">
+<th align="center">guideline</th>
+<th align="center">method</th>
+<th align="center">site</th>
+<th align="center">mo</th>
+<th align="center">ab</th>
+<th align="center">ref_tbl</th>
+<th align="center">disk_dose</th>
+<th align="center">breakpoint_S</th>
+<th align="center">breakpoint_R</th>
+<th align="center">uti</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td align="center">EUCAST 2020</td>
+<td align="center">DISK</td>
+<td align="center"></td>
+<td align="center">Enterobacterales</td>
+<td align="center">Amoxicillin/clavulanic acid</td>
+<td align="center">Enterobacterales</td>
+<td align="center">20-10ug</td>
+<td align="center">19</td>
+<td align="center">19</td>
+<td align="center">FALSE</td>
+</tr>
+<tr class="even">
+<td align="center">EUCAST 2020</td>
+<td align="center">DISK</td>
+<td align="center">UTI</td>
+<td align="center">Enterobacterales</td>
+<td align="center">Amoxicillin/clavulanic acid</td>
+<td align="center">Enterobacterales</td>
+<td align="center">20-10ug</td>
+<td align="center">16</td>
+<td align="center">16</td>
+<td align="center">TRUE</td>
+</tr>
+<tr class="odd">
+<td align="center">EUCAST 2020</td>
+<td align="center">MIC</td>
+<td align="center"></td>
+<td align="center">Enterobacterales</td>
+<td align="center">Amoxicillin/clavulanic acid</td>
+<td align="center">Enterobacterales</td>
+<td align="center"></td>
+<td align="center">8</td>
+<td align="center">8</td>
+<td align="center">FALSE</td>
+</tr>
+<tr class="even">
+<td align="center">EUCAST 2020</td>
+<td align="center">MIC</td>
+<td align="center">UTI</td>
+<td align="center">Enterobacterales</td>
+<td align="center">Amoxicillin/clavulanic acid</td>
+<td align="center">Enterobacterales</td>
+<td align="center"></td>
+<td align="center">32</td>
+<td align="center">32</td>
+<td align="center">TRUE</td>
+</tr>
+<tr class="odd">
+<td align="center">EUCAST 2020</td>
+<td align="center">MIC</td>
+<td align="center"></td>
+<td align="center">Actinomyces</td>
+<td align="center">Amoxicillin/clavulanic acid</td>
+<td align="center">Anaerobes, Grampositive</td>
+<td align="center"></td>
+<td align="center">4</td>
+<td align="center">8</td>
+<td align="center">FALSE</td>
+</tr>
+<tr class="even">
+<td align="center">EUCAST 2020</td>
+<td align="center">MIC</td>
+<td align="center"></td>
+<td align="center">Bacteroides</td>
+<td align="center">Amoxicillin/clavulanic acid</td>
+<td align="center">Anaerobes, Gramnegative</td>
+<td align="center"></td>
+<td align="center">4</td>
+<td align="center">8</td>
+<td align="center">FALSE</td>
+</tr>
+</tbody>
+</table>
+</div>
+</div>
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+
+        <nav id="toc" data-toggle="toc"><h2 data-toc-skip>Contents</h2>
+    </nav>
+</div>
+
+</div>
+
+
+
+      <footer><div class="copyright">
+  <p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/">Corinna Glasner</a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
+</div>
+
+      </footer>
+</div>
+
+  
+
+
+  </body>
+</html>
--- a/docs/articles/datasets_files/accessible-code-block-0.0.1/empty-anchor.js
+++ b/docs/articles/datasets_files/accessible-code-block-0.0.1/empty-anchor.js
@ -0,0 +1,15 @@
+// Hide empty <a> tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
+// v0.0.1
+// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
+
+document.addEventListener('DOMContentLoaded', function() {
+  const codeList = document.getElementsByClassName("sourceCode");
+  for (var i = 0; i < codeList.length; i++) {
+    var linkList = codeList[i].getElementsByTagName('a');
+    for (var j = 0; j < linkList.length; j++) {
+      if (linkList[j].innerHTML === "") {
+        linkList[j].setAttribute('aria-hidden', 'true');
+      }
+    }
+  }
+});
--- 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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -117,6 +117,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="../articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="../articles/PCA.html">
        <span class="fa fa-compress"></span>
@ -247,6 +254,8 @@
        <dd></dt>
        <dt><a href="benchmarks.html">Benchmarks</a></dt>
        <dd></dt>
+        <dt><a href="datasets.html">Data sets for download</a></dt>
+        <dd></dt>
        <dt><a href="resistance_predict.html">How to predict antimicrobial resistance</a></dt>
        <dd></dt>
        <dt><a href="welcome_to_AMR.html">Welcome to the AMR package</a></dt>
--- 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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -117,6 +117,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="articles/PCA.html">
        <span class="fa fa-compress"></span>
--- a/docs/extra.css
+++ b/docs/extra.css
@ -250,3 +250,24 @@ table a:not(.btn):hover, .table a:not(.btn):hover {
  background: #128f7645;
  color: #2c3e50;
 }
+.home-buttons {
+  display: flex;
+  margin-bottom: 5px;
+}
+.home-buttons a {
+	display: grid;
+	text-align: center;
+	font-size: 16px;
+	text-transform: uppercase;
+	width: 25%;
+}
+.home-buttons a:hover {
+	text-decoration: none;
+}
+.home-buttons div {
+	display: grid;
+	padding: 10px;
+}
+.home-buttons .fa {
+	font-size: 3.5em;
+}
--- 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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -79,6 +79,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="articles/PCA.html">
        <span class="fa fa-compress"></span>
@ -207,6 +214,33 @@ Since you are one of our users, we would like to know how you use the package an
 </p>
 <br><br>
 </div>
+<div class="home-buttons">
+<a href="articles/datasets.html">
+<div style="background-color: #128f7635;">
+<div class="fa fa-database">
+</div>
+<span>Download free data sets</span>
+</div>
+</a> <a href="articles/AMR.html">
+<div style="background-color: #138F3865;">
+<div class="fa fa-chalkboard-teacher">
+</div>
+<span>Start learning AMR analysis</span>
+</div>
+</a> <a href="reference/as.rsi.html">
+<div style="background-color: #128f7650;">
+<div class="fa fa-language">
+</div>
+<span>Interpret MIC/disk values to R/SI</span>
+</div>
+</a> <a href="articles/MDR.html">
+<div style="background-color: #138F3835;">
+<div class="fa fa-skull-crossbones">
+</div>
+<span>Determine multi-drug resistance (MDR)</span>
+</div>
+</a>
+</div>
 <div id="partners" class="section level4">
 <h4 class="hasAnchor">
 <a href="#partners" class="anchor"></a>Partners</h4>
@ -245,6 +279,7 @@ Since you are one of our users, we would like to know how you use the package an
 <div id="latest-released-version" class="section level4">
 <h4 class="hasAnchor">
 <a href="#latest-released-version" class="anchor"></a>Latest released version</h4>
+<p><img src="https://www.r-pkg.org/badges/version-ago/AMR"><img src="https://cranlogs.r-pkg.org/badges/grand-total/AMR"></p>
 <p>This package is available <a href="https://cran.r-project.org/package=AMR">here on the official R network (CRAN)</a>, which has a peer-reviewed submission process. Install this package in R from CRAN by using the command:</p>
 <div class="sourceCode" id="cb1"><pre class="downlit">
 <span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span>(<span class="st">"AMR"</span>)
--- 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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -117,6 +117,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="../articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="../articles/PCA.html">
        <span class="fa fa-compress"></span>
@ -229,13 +236,13 @@
      <small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
    </div>

-    <div id="amr-1309003" class="section level1">
-<h1 class="page-header" data-toc-text="1.3.0.9003">
-<a href="#amr-1309003" class="anchor"></a>AMR 1.3.0.9003<small> Unreleased </small>
+    <div id="amr-1309004" class="section level1">
+<h1 class="page-header" data-toc-text="1.3.0.9004">
+<a href="#amr-1309004" class="anchor"></a>AMR 1.3.0.9004<small> Unreleased </small>
 </h1>
-<div id="last-updated-15-august-2020" class="section level2">
+<div id="last-updated-16-august-2020" class="section level2">
 <h2 class="hasAnchor">
-<a href="#last-updated-15-august-2020" class="anchor"></a><small>Last updated: 15 August 2020</small>
+<a href="#last-updated-16-august-2020" class="anchor"></a><small>Last updated: 16 August 2020</small>
 </h2>
 <div id="new" class="section level3">
 <h3 class="hasAnchor">
@ -250,7 +257,7 @@
 <span class="kw">intrinsic_resistant</span> <span class="op">%&gt;%</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="kw">antibiotic</span> <span class="op">==</span> <span class="st">"Vancomycin"</span>, <span class="kw">microorganism</span> <span class="op">%like%</span> <span class="st">"Enterococcus"</span>) <span class="op">%&gt;%</span> 
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span>(<span class="kw">microorganism</span>)
-<span class="co"># [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"   </span>
+<span class="co">#&gt; [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"   </span>
 </pre></div>
 </li>
 </ul>
@ -259,7 +266,8 @@
 <h3 class="hasAnchor">
 <a href="#changed" class="anchor"></a>Changed</h3>
 <ul>
-<li>Improvements for <code><a href="../reference/as.rsi.html">as.rsi()</a></code>:
+<li>
+<p>Improvements for <code><a href="../reference/as.rsi.html">as.rsi()</a></code>:</p>
 <ul>
 <li>
 <p>Support for using <code>dplyr</code>’s <code><a href="https://dplyr.tidyverse.org/reference/across.html">across()</a></code> to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.</p>
@ -274,9 +282,18 @@
 </pre></div>
 </li>
 <li><p>Big speed improvement for interpreting MIC values and disk zone diameters. When interpreting 5,000 MIC values of two antibiotics (10,000 values in total), our benchmarks showed a total run time going from 80.7-85.1 seconds to 1.8-2.0 seconds.</p></li>
+<li><p>Added parameter ‘add_intrinsic_resistance’ (defaults to <code>FALSE</code>), that considers intrinsic resistance according to EUCAST</p></li>
 </ul>
 </li>
-<li>Overall speed improvement by tweaking joining functions</li>
+<li>
+<p>Added intelligent data cleaning to <code><a href="../reference/as.disk.html">as.disk()</a></code>, so numbers can also be extracted from text and decimal numbers will always be rounded up:</p>
+<div class="sourceCode" id="cb3"><pre class="downlit">
+<span class="fu"><a href="../reference/as.disk.html">as.disk</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"disk zone: 23.4 mm"</span>, <span class="fl">23.4</span>))
+<span class="co">#&gt; Class &lt;disk&gt;</span>
+<span class="co">#&gt; [1] 24 24</span>
+</pre></div>
+</li>
+<li><p>Overall speed improvement by tweaking joining functions</p></li>
 </ul>
 </div>
 </div>
@ -292,7 +309,7 @@
 <li><p>Function <code><a href="../reference/ab_from_text.html">ab_from_text()</a></code> to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses <code><a href="../reference/as.ab.html">as.ab()</a></code> internally</p></li>
 <li>
 <p><a href="https://tidyselect.r-lib.org/reference/language.html">Tidyverse selection helpers</a> for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> and <code><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html">tidyr::pivot_longer()</a></code>:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit">
+<div class="sourceCode" id="cb4"><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"># Columns 'IPM' and 'MEM' are in the example_isolates data set</span>
@ -481,7 +498,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline</p></li>
 <li>
 <p>Interpretation from MIC values (and disk zones) to R/SI can now be used with <code><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at()</a></code> of the <code>dplyr</code> package:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit">
+<div class="sourceCode" id="cb5"><pre class="downlit">
 <span class="kw">yourdata</span> <span class="op">%&gt;%</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">antibiotic1</span><span class="op">:</span><span class="kw">antibiotic25</span>), <span class="kw">as.rsi</span>, mo = <span class="st">"E. coli"</span>)

@ -510,7 +527,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Support for LOINC codes in the <code>antibiotics</code> data set. Use <code><a href="../reference/ab_property.html">ab_loinc()</a></code> to retrieve LOINC codes, or use a LOINC code for input in any <code>ab_*</code> function:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit">
+<div class="sourceCode" id="cb6"><pre class="downlit">
 <span class="fu"><a href="../reference/ab_property.html">ab_loinc</a></span>(<span class="st">"ampicillin"</span>)
 <span class="co">#&gt; [1] "21066-6" "3355-5"  "33562-0" "33919-2" "43883-8" "43884-6" "87604-5"</span>
 <span class="fu"><a href="../reference/ab_property.html">ab_name</a></span>(<span class="st">"21066-6"</span>)
@ -521,7 +538,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>Support for SNOMED CT codes in the <code>microorganisms</code> data set. Use <code><a href="../reference/mo_property.html">mo_snomed()</a></code> to retrieve SNOMED codes, or use a SNOMED code for input in any <code>mo_*</code> function:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit">
+<div class="sourceCode" id="cb7"><pre class="downlit">
 <span class="fu"><a href="../reference/mo_property.html">mo_snomed</a></span>(<span class="st">"S. aureus"</span>)
 <span class="co">#&gt; [1] 115329001   3092008 113961008</span>
 <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="fl">115329001</span>)
@ -586,11 +603,11 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit">
+<div class="sourceCode" id="cb8"><pre class="downlit">
 <span class="co">if</span> (<span class="fu"><a href="../reference/mo_property.html">mo_family</a></span>(<span class="kw">somebugs</span>) <span class="op">==</span> <span class="st">"Enterobacteriaceae"</span>) <span class="kw">...</span>
 </pre></div>
 <p>then please adjust this to:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit">
+<div class="sourceCode" id="cb9"><pre class="downlit">
 <span class="co">if</span> (<span class="fu"><a href="../reference/mo_property.html">mo_order</a></span>(<span class="kw">somebugs</span>) <span class="op">==</span> <span class="st">"Enterobacterales"</span>) <span class="kw">...</span>
 </pre></div>
 </li>
@ -604,7 +621,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Functions <code><a href="../reference/proportion.html">susceptibility()</a></code> and <code><a href="../reference/proportion.html">resistance()</a></code> as aliases of <code><a href="../reference/proportion.html">proportion_SI()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code>, respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.</p>
-<div class="sourceCode" id="cb9"><pre class="downlit">
+<div class="sourceCode" id="cb10"><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="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>(bug = <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="kw">mo</span>)) <span class="op">%&gt;%</span> 
@ -633,7 +650,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>More intelligent way of coping with some consonants like “l” and “r”</p></li>
 <li>
 <p>Added a score (a certainty percentage) to <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code>, that is calculated using the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance</a>:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit">
+<div class="sourceCode" id="cb11"><pre class="downlit">
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Stafylococcus aureus"</span>,
        <span class="st">"staphylokok aureuz"</span>))
 <span class="co">#&gt; Warning: </span>
@ -692,14 +709,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Determination of first isolates now <strong>excludes</strong> all ‘unknown’ microorganisms at default, i.e. microbial code <code>"UNKNOWN"</code>. They can be included with the new parameter <code>include_unknown</code>:</p>
-<div class="sourceCode" id="cb11"><pre class="downlit">
+<div class="sourceCode" id="cb12"><pre class="downlit">
 <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span>(<span class="kw">...</span>, include_unknown = <span class="fl">TRUE</span>)
 </pre></div>
 <p>For WHONET users, this means that all records/isolates with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default, since <code>as.mo("con") = "UNKNOWN"</code>. The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.</p>
 </li>
 <li>
 <p>For code consistency, classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in <code>NA</code>:</p>
-<div class="sourceCode" id="cb12"><pre class="downlit">
+<div class="sourceCode" id="cb13"><pre class="downlit">
 <span class="co"># how it works in base R:</span>
 <span class="kw">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span>(<span class="st">"A"</span>)
 <span class="kw">x</span>[<span class="fl">1</span>] <span class="op">&lt;-</span> <span class="st">"B"</span>
@ -724,7 +741,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Function <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with <code><a href="../reference/mo_property.html">mo_shortname()</a></code> at default:</p>
-<div class="sourceCode" id="cb13"><pre class="downlit">
+<div class="sourceCode" id="cb14"><pre class="downlit">
 <span class="kw">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span>(<span class="kw">example_isolates</span>)
 <span class="co">#&gt; NOTE: Using column `mo` as input for `col_mo`.</span>
 <span class="kw">x</span>[<span class="fl">1</span><span class="op">:</span><span class="fl">4</span>, ]
@ -747,13 +764,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="co">#&gt; NOTE: Use 'format()' on this result to get a publicable/printable format.</span>
 </pre></div>
 <p>You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R <code><a href="https://rdrr.io/r/base/format.html">format()</a></code> function:</p>
-<div class="sourceCode" id="cb14"><pre class="downlit">
+<div class="sourceCode" id="cb15"><pre class="downlit">
 <span class="fu"><a href="https://rdrr.io/r/base/format.html">format</a></span>(<span class="kw">x</span>, combine_IR = <span class="fl">FALSE</span>)
 </pre></div>
 </li>
 <li>
 <p>Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for <code>portion_*</code> functions or <code>count_*</code> functions. This can be used to determine the empiric susceptibility of a combination therapy. A new parameter <code>only_all_tested</code> (<strong>which defaults to <code>FALSE</code></strong>) replaces the old <code>also_single_tested</code> and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the <code>portion</code> and <code>count</code> help pages), where the %SI is being determined:</p>
-<div class="sourceCode" id="cb15"><pre class="downlit">
+<div class="sourceCode" id="cb16"><pre class="downlit">
 <span class="co"># --------------------------------------------------------------------</span>
 <span class="co">#                     only_all_tested = FALSE  only_all_tested = TRUE</span>
 <span class="co">#                     -----------------------  -----------------------</span>
@ -775,7 +792,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p><code>tibble</code> printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code> <code>mo</code>. When using <code>tibble</code>s containing antimicrobial columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
-<div class="sourceCode" id="cb16"><pre class="downlit">
+<div class="sourceCode" id="cb17"><pre class="downlit">
 <span class="co"># (run this on your own console, as this page does not support colour printing)</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="kw">example_isolates</span> <span class="op">%&gt;%</span>
@ -858,7 +875,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Function <code><a href="../reference/proportion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><a href="../reference/count.html">count_df()</a></code> and <code><a href="../reference/AMR-deprecated.html">portion_df()</a></code> to immediately show resistance percentages and number of available isolates:</p>
-<div class="sourceCode" id="cb17"><pre class="downlit">
+<div class="sourceCode" id="cb18"><pre class="downlit">
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="kw">AMX</span>, <span class="kw">CIP</span>) <span class="op">%&gt;%</span>
  <span class="fu"><a href="../reference/proportion.html">rsi_df</a></span>()
@ -885,7 +902,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li>UPEC (Uropathogenic <em>E. coli</em>)</li>
 </ul>
 <p>All these lead to the microbial ID of <em>E. coli</em>:</p>
-<div class="sourceCode" id="cb18"><pre class="downlit">
+<div class="sourceCode" id="cb19"><pre class="downlit">
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"UPEC"</span>)
 <span class="co"># B_ESCHR_COL</span>
 <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"UPEC"</span>)
@ -990,7 +1007,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>when all values are unique it now shows a message instead of a warning</p></li>
 <li>
 <p>support for boxplots:</p>
-<div class="sourceCode" id="cb19"><pre class="downlit">
+<div class="sourceCode" id="cb20"><pre class="downlit">
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span> 
  <span class="fu">freq</span>(<span class="kw">age</span>) <span class="op">%&gt;%</span> 
  <span class="fu"><a href="https://rdrr.io/r/graphics/boxplot.html">boxplot</a></span>()
@ -1085,7 +1102,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:</p>
-<div class="sourceCode" id="cb20"><pre class="downlit">
+<div class="sourceCode" id="cb21"><pre class="downlit">
 <span class="fu"><a href="../reference/filter_ab_class.html">filter_aminoglycosides</a></span>()
 <span class="fu"><a href="../reference/filter_ab_class.html">filter_carbapenems</a></span>()
 <span class="fu"><a href="../reference/filter_ab_class.html">filter_cephalosporins</a></span>()
@ -1099,7 +1116,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="fu"><a href="../reference/filter_ab_class.html">filter_tetracyclines</a></span>()
 </pre></div>
 <p>The <code>antibiotics</code> data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set. For example:</p>
-<div class="sourceCode" id="cb21"><pre class="downlit">
+<div class="sourceCode" id="cb22"><pre class="downlit">
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>(result = <span class="st">"R"</span>)
 <span class="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span>
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>(result = <span class="st">"R"</span>, scope = <span class="st">"all"</span>)
@ -1108,7 +1125,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
-<div class="sourceCode" id="cb22"><pre class="downlit">
+<div class="sourceCode" id="cb23"><pre class="downlit">
 <span class="kw">ab_property</span> <span class="op">-&gt;</span> <span class="fu">atc_property</span>()
 <span class="kw">ab_name</span> <span class="op">-&gt;</span> <span class="fu">atc_name</span>()
 <span class="kw">ab_official</span> <span class="op">-&gt;</span> <span class="fu">atc_official</span>()
@ -1129,7 +1146,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>New function <code><a href="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</p></li>
 <li>
 <p>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="https://rdrr.io/r/graphics/plot.default.html">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
-<div class="sourceCode" id="cb23"><pre class="downlit">
+<div class="sourceCode" id="cb24"><pre class="downlit">
 <span class="kw">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(<span class="kw">septic_patients</span>, col_ab = <span class="st">"amox"</span>)
 <span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html">plot</a></span>(<span class="kw">x</span>)
 <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(<span class="kw">x</span>)
@ -1137,13 +1154,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
-<div class="sourceCode" id="cb24"><pre class="downlit">
+<div class="sourceCode" id="cb25"><pre class="downlit">
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(<span class="kw">...</span>)
 <span class="co"># or</span>
 <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(<span class="kw">septic_patients</span>, <span class="kw">...</span>)
 </pre></div>
 <p>is equal to:</p>
-<div class="sourceCode" id="cb25"><pre class="downlit">
+<div class="sourceCode" id="cb26"><pre class="downlit">
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(only_firsts = <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span>(<span class="kw">septic_patients</span>, <span class="kw">...</span>)) <span class="op">%&gt;%</span>
  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="kw">only_firsts</span> <span class="op">==</span> <span class="fl">TRUE</span>) <span class="op">%&gt;%</span>
@ -1176,7 +1193,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Now handles incorrect spelling, like <code>i</code> instead of <code>y</code> and <code>f</code> instead of <code>ph</code>:</p>
-<div class="sourceCode" id="cb26"><pre class="downlit">
+<div class="sourceCode" id="cb27"><pre class="downlit">
 <span class="co"># mo_fullname() uses as.mo() internally</span>

 <span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"Sthafilokockus aaureuz"</span>)
@ -1188,7 +1205,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default <code>allow_uncertain = TRUE</code> is equal to uncertainty level 2. Run <code><a href="../reference/as.mo.html">?as.mo</a></code> for more info about these levels.</p>
-<div class="sourceCode" id="cb27"><pre class="downlit">
+<div class="sourceCode" id="cb28"><pre class="downlit">
 <span class="co"># equal:</span>
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="kw">...</span>, allow_uncertain = <span class="fl">TRUE</span>)
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="kw">...</span>, allow_uncertain = <span class="fl">2</span>)
@ -1203,7 +1220,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>All microbial IDs that found are now saved to a local file <code>~/.Rhistory_mo</code>. Use the new function <code>clean_mo_history()</code> to delete this file, which resets the algorithms.</p></li>
 <li>
 <p>Incoercible results will now be considered ‘unknown’, MO code <code>UNKNOWN</code>. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:</p>
-<div class="sourceCode" id="cb28"><pre class="downlit">
+<div class="sourceCode" id="cb29"><pre class="downlit">
 <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"qwerty"</span>, language = <span class="st">"es"</span>)
 <span class="co"># Warning: </span>
 <span class="co"># one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.</span>
@ -1253,7 +1270,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
-<div class="sourceCode" id="cb29"><pre class="downlit">
+<div class="sourceCode" id="cb30"><pre class="downlit">
 <span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span>
 <span class="co"># OLD WAY</span>
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span>
@ -1337,7 +1354,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Fewer than 3 characters as input for <code>as.mo</code> will return NA</p></li>
 <li>
 <p>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached</p>
-<div class="sourceCode" id="cb30"><pre class="downlit">
+<div class="sourceCode" id="cb31"><pre class="downlit">
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. species"</span>)        <span class="co"># B_ESCHR</span>
 <span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"E. spp."</span>)     <span class="co"># "Escherichia species"</span>
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. spp"</span>)            <span class="co"># B_STPHY</span>
@ -1354,7 +1371,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <ul>
 <li>
 <p>Support for grouping variables, test with:</p>
-<div class="sourceCode" id="cb31"><pre class="downlit">
+<div class="sourceCode" id="cb32"><pre class="downlit">
 <span class="kw">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="kw">hospital_id</span>) <span class="op">%&gt;%</span> 
  <span class="fu">freq</span>(<span class="kw">gender</span>)
@ -1362,7 +1379,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 <li>
 <p>Support for (un)selecting columns:</p>
-<div class="sourceCode" id="cb32"><pre class="downlit">
+<div class="sourceCode" id="cb33"><pre class="downlit">
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span> 
  <span class="fu">freq</span>(<span class="kw">hospital_id</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="kw">count</span>, <span class="op">-</span><span class="kw">cum_count</span>) <span class="co"># only get item, percent, cum_percent</span>
@ -1442,7 +1459,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 </li>
 </ul>
 <p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
-<div class="sourceCode" id="cb33"><pre class="downlit">
+<div class="sourceCode" id="cb34"><pre class="downlit">
 <span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>)
 <span class="co"># [1] "Gram negative"</span>
 <span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, language = <span class="st">"de"</span>) <span class="co"># German</span>
@ -1453,7 +1470,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="co"># [1] "Streptococcus grupo A"</span>
 </pre></div>
 <p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
-<div class="sourceCode" id="cb34"><pre class="downlit">
+<div class="sourceCode" id="cb35"><pre class="downlit">
 <span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"Esc blattae"</span>)
 <span class="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span>
 <span class="co"># [1] "Gram negative"</span>
@ -1468,7 +1485,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Function <code>is.rsi.eligible</code> to check for columns that have valid antimicrobial results, but do not have the <code>rsi</code> class yet. Transform the columns of your raw data with: <code>data %&gt;% mutate_if(is.rsi.eligible, as.rsi)</code></p></li>
 <li>
 <p>Functions <code>as.mo</code> and <code>is.mo</code> as replacements for <code>as.bactid</code> and <code>is.bactid</code> (since the <code>microoganisms</code> data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The <code>as.mo</code> function determines microbial IDs using intelligent rules:</p>
-<div class="sourceCode" id="cb35"><pre class="downlit">
+<div class="sourceCode" id="cb36"><pre class="downlit">
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. coli"</span>)
 <span class="co"># [1] B_ESCHR_COL</span>
 <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"MRSA"</span>)
@ -1477,7 +1494,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <span class="co"># [1] B_STRPTC_GRA</span>
 </pre></div>
 <p>And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:</p>
-<div class="sourceCode" id="cb36"><pre class="downlit">
+<div class="sourceCode" id="cb37"><pre class="downlit">
 <span class="kw">thousands_of_E_colis</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html">rep</a></span>(<span class="st">"E. coli"</span>, <span class="fl">25000</span>)
 <span class="kw">microbenchmark</span>::<span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="kw">thousands_of_E_colis</span>), unit = <span class="st">"s"</span>)
 <span class="co"># Unit: seconds</span>
@ -1511,7 +1528,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</p></li>
 <li>
 <p>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.:</p>
-<div class="sourceCode" id="cb37"><pre class="downlit">
+<div class="sourceCode" id="cb38"><pre class="downlit">
 <span class="fu">ab_official</span>(<span class="st">"Bactroban"</span>)
 <span class="co"># [1] "Mupirocin"</span>
 <span class="fu"><a href="../reference/ab_property.html">ab_name</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))
@ -1528,7 +1545,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Added parameters <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code></p></li>
 <li>
 <p>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns.</p>
-<div class="sourceCode" id="cb38"><pre class="downlit">
+<div class="sourceCode" id="cb39"><pre class="downlit">
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="kw">amox</span>, <span class="kw">cipr</span>) <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/count.html">count_IR</a></span>()
 <span class="co"># which is the same as:</span>
 <span class="kw">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/count.html">count_IR</a></span>(<span class="kw">amox</span>, <span class="kw">cipr</span>)
@ -1548,12 +1565,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 <li><p>Added longest en shortest character length in the frequency table (<code>freq</code>) header of class <code>character</code></p></li>
 <li>
 <p>Support for types (classes) list and matrix for <code>freq</code></p>
-<div class="sourceCode" id="cb39"><pre class="downlit">
+<div class="sourceCode" id="cb40"><pre class="downlit">
 <span class="kw">my_matrix</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/with.html">with</a></span>(<span class="kw">septic_patients</span>, <span class="fu"><a href="https://rdrr.io/r/base/matrix.html">matrix</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="kw">age</span>, <span class="kw">gender</span>), ncol = <span class="fl">2</span>))
 <span class="fu">freq</span>(<span class="kw">my_matrix</span>)
 </pre></div>
 <p>For lists, subsetting is possible:</p>
-<div class="sourceCode" id="cb40"><pre class="downlit">
+<div class="sourceCode" id="cb41"><pre class="downlit">
 <span class="kw">my_list</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(age = <span class="kw">septic_patients</span><span class="op">$</span><span class="kw">age</span>, gender = <span class="kw">septic_patients</span><span class="op">$</span><span class="kw">gender</span>)
 <span class="kw">my_list</span> <span class="op">%&gt;%</span> <span class="fu">freq</span>(<span class="kw">age</span>)
 <span class="kw">my_list</span> <span class="op">%&gt;%</span> <span class="fu">freq</span>(<span class="kw">gender</span>)
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@ -2,7 +2,7 @@ pandoc: 2.7.3
 pkgdown: 1.5.1.9000
 pkgdown_sha: eae56f08694abebf93cdfc0dd8e9ede06d8c815f
 articles: []
-last_built: 2020-08-15T10:52Z
+last_built: 2020-08-16T19:34Z
 urls:
  reference: https://msberends.github.io/AMR/reference
  article: https://msberends.github.io/AMR/articles
--- 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">1.3.0.9002</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -118,6 +118,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="../articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="../articles/PCA.html">
        <span class="fa fa-compress"></span>
@ -249,6 +256,7 @@
  guideline = <span class='st'>"EUCAST"</span>,
  uti = <span class='fl'>FALSE</span>,
  conserve_capped_values = <span class='fl'>FALSE</span>,
+  add_intrinsic_resistance = <span class='fl'>FALSE</span>,
  <span class='kw'>...</span>
 )

@ -259,6 +267,7 @@
  ab = <span class='fu'><a href='https://rdrr.io/r/base/deparse.html'>deparse</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/substitute.html'>substitute</a></span>(<span class='kw'>x</span>)),
  guideline = <span class='st'>"EUCAST"</span>,
  uti = <span class='fl'>FALSE</span>,
+  add_intrinsic_resistance = <span class='fl'>FALSE</span>,
  <span class='kw'>...</span>
 )

@ -269,6 +278,7 @@
  guideline = <span class='st'>"EUCAST"</span>,
  uti = <span class='kw'>NULL</span>,
  conserve_capped_values = <span class='fl'>FALSE</span>,
+  add_intrinsic_resistance = <span class='fl'>FALSE</span>,
  <span class='kw'>...</span>
 )</pre>

@ -307,6 +317,10 @@
      <th>conserve_capped_values</th>
      <td><p>a logical to indicate that MIC values starting with <code>"&gt;"</code> (but not <code>"&gt;="</code>) must always return "R" , and that MIC values starting with <code>"&lt;"</code> (but not <code>"&lt;="</code>) must always return "S"</p></td>
    </tr>
+    <tr>
+      <th>add_intrinsic_resistance</th>
+      <td><p><em>(only useful when using a EUCAST guideline)</em> a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in <em>Klebsiella</em> species. Determination is based on the <a href='intrinsic_resistant.html'>intrinsic_resistant</a> data set, that itself is based on 'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes', version 3.1, 2016.</p></td>
+    </tr>
    <tr>
      <th>col_mo</th>
      <td><p>column name of the IDs of the microorganisms (see <code><a href='as.mo.html'>as.mo()</a></code>), defaults to the first column of class <code><a href='as.mo.html'>mo</a></code>. Values will be coerced using <code><a href='as.mo.html'>as.mo()</a></code>.</p></td>
@ -406,6 +420,9 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s

 <span class='co'># the dplyr way</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='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_if</a></span>(<span class='kw'>is.mic</span>, <span class='kw'>as.rsi</span>)
+<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_if</a></span>(<span class='fu'>function</span>(<span class='kw'>x</span>) <span class='fu'><a href='as.mic.html'>is.mic</a></span>(<span class='kw'>x</span>) <span class='op'>|</span> <span class='fu'><a href='as.disk.html'>is.disk</a></span>(<span class='kw'>x</span>), <span class='kw'>as.rsi</span>)
+<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='fu'>where</span>(<span class='kw'>is.mic</span>), <span class='kw'>as.rsi</span>))
 <span class='kw'>df</span> <span class='op'>%&gt;%</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</span><span class='op'>:</span><span class='kw'>TOB</span>), <span class='kw'>as.rsi</span>)
 <span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>TOB</span>), <span class='kw'>as.rsi</span>)

--- 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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -117,6 +117,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="../articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="../articles/PCA.html">
        <span class="fa fa-compress"></span>
--- a/docs/reference/intrinsic_resistant.html
+++ b/docs/reference/intrinsic_resistant.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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -118,6 +118,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="../articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="../articles/PCA.html">
        <span class="fa fa-compress"></span>
--- a/docs/reference/rsi_translation.html
+++ b/docs/reference/rsi_translation.html
@ -49,7 +49,7 @@
  <script src="../extra.js"></script>

 <meta property="og:title" content="Data set for R/SI interpretation — rsi_translation" />
-<meta property="og:description" content="Data set to interpret MIC and disk diffusion to R/SI values. Included guidelines are CLSI (2011-2019) and EUCAST (2011-2020). Use as.rsi() to transform MICs or disks measurements to R/SI values." />
+<meta property="og:description" content="Data set to interpret MIC and disk diffusion to R/SI values. Included guidelines are CLSI (2010-2019) and EUCAST (2011-2020). Use as.rsi() to transform MICs or disks measurements to R/SI values." />
 <meta property="og:image" content="https://msberends.github.io/AMR/logo.svg" />


@ -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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -118,6 +118,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="../articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="../articles/PCA.html">
        <span class="fa fa-compress"></span>
@ -232,7 +239,7 @@
    </div>

    <div class="ref-description">
-    <p>Data set to interpret MIC and disk diffusion to R/SI values. Included guidelines are CLSI (2011-2019) and EUCAST (2011-2020). Use <code><a href='as.rsi.html'>as.rsi()</a></code> to transform MICs or disks measurements to R/SI values.</p>
+    <p>Data set to interpret MIC and disk diffusion to R/SI values. Included guidelines are CLSI (2010-2019) and EUCAST (2011-2020). Use <code><a href='as.rsi.html'>as.rsi()</a></code> to transform MICs or disks measurements to R/SI values.</p>
    </div>

    <pre class="usage"><span class='kw'>rsi_translation</span></pre>
--- a/docs/sitemap.xml
+++ b/docs/sitemap.xml
@ -171,6 +171,9 @@
  <url>
    <loc>https://msberends.github.io/AMR/articles/benchmarks.html</loc>
  </url>
+  <url>
+    <loc>https://msberends.github.io/AMR/articles/datasets.html</loc>
+  </url>
  <url>
    <loc>https://msberends.github.io/AMR/articles/resistance_predict.html</loc>
  </url>
--- 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">1.3.0.9003</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
      </span>
    </div>

@ -117,6 +117,13 @@
        Predict antimicrobial resistance
      </a>
    </li>
+    <li>
+      <a href="articles/datasets.html">
+        <span class="fa fa-database"></span>
+         
+        Download our free data sets
+      </a>
+    </li>
    <li>
      <a href="articles/PCA.html">
        <span class="fa fa-compress"></span>
--- a/index.md
+++ b/index.md
@ -23,6 +23,33 @@ This package is [fully independent of any other R package](https://en.wikipedia.
    Since its first public release in early 2018, this package has been downloaded from more than 100 countries. Click the map to enlarge and to also see the names of the countries.</p><br><br>
 </div>

+<div class="home-buttons">
+	<a href="articles/datasets.html">
+		<div style="background-color: #128f7635;">
+			<div class="fa fa-database"></div>
+			<span>Download free data sets</span>
+		</div>
+	</a>
+	<a href="articles/AMR.html">
+		<div style="background-color: #138F3865;">
+			<div class="fa fa-chalkboard-teacher"></div>
+			<span>Start learning AMR analysis</span>
+		</div>
+	</a>
+	<a href="reference/as.rsi.html">
+		<div style="background-color: #128f7650;">
+			<div class="fa fa-language"></div>
+			<span>Interpret MIC/disk values to R/SI</span>
+		</div>
+	</a>
+	<a href="articles/MDR.html">
+		<div style="background-color: #138F3835;">
+			<div class="fa fa-skull-crossbones"></div>
+			<span>Determine multi-drug resistance (MDR)</span>
+		</div>
+	</a>
+</div>
+
 #### Partners

 The development of this package is part of, related to, or made possible by:
@ -59,6 +86,8 @@ This package can be used for:
 ### Get this package

 #### Latest released version
+<img src="https://www.r-pkg.org/badges/version-ago/AMR" />
+<img src="https://cranlogs.r-pkg.org/badges/grand-total/AMR" />

 This package is available [here on the official R network (CRAN)](https://cran.r-project.org/package=AMR), which has a peer-reviewed submission process. Install this package in R from CRAN by using the command:

--- a/man/as.rsi.Rd
+++ b/man/as.rsi.Rd
@ -23,6 +23,7 @@ is.rsi.eligible(x, threshold = 0.05)
  guideline = "EUCAST",
  uti = FALSE,
  conserve_capped_values = FALSE,
+  add_intrinsic_resistance = FALSE,
  ...
 )

@ -32,6 +33,7 @@ is.rsi.eligible(x, threshold = 0.05)
  ab = deparse(substitute(x)),
  guideline = "EUCAST",
  uti = FALSE,
+  add_intrinsic_resistance = FALSE,
  ...
 )

@ -41,6 +43,7 @@ is.rsi.eligible(x, threshold = 0.05)
  guideline = "EUCAST",
  uti = NULL,
  conserve_capped_values = FALSE,
+  add_intrinsic_resistance = FALSE,
  ...
 )
 }
@ -61,6 +64,8 @@ is.rsi.eligible(x, threshold = 0.05)

 \item{conserve_capped_values}{a logical to indicate that MIC values starting with \code{">"} (but not \code{">="}) must always return "R" , and that MIC values starting with \code{"<"} (but not \code{"<="}) must always return "S"}

+\item{add_intrinsic_resistance}{\emph{(only useful when using a EUCAST guideline)} a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in \emph{Klebsiella} species. Determination is based on the \link{intrinsic_resistant} data set, that itself is based on 'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes', version 3.1, 2016.}
+
 \item{col_mo}{column name of the IDs of the microorganisms (see \code{\link[=as.mo]{as.mo()}}), defaults to the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
 }
 \value{
@ -160,6 +165,9 @@ as.rsi(df)

 # the dplyr way
 library(dplyr)
+df \%>\% mutate_if(is.mic, as.rsi)
+df \%>\% mutate_if(function(x) is.mic(x) | is.disk(x), as.rsi)
+df \%>\% mutate(across(where(is.mic), as.rsi))
 df \%>\% mutate_at(vars(AMP:TOB), as.rsi)
 df \%>\% mutate(across(AMP:TOB), as.rsi)

--- a/man/rsi_translation.Rd
+++ b/man/rsi_translation.Rd
@ -23,7 +23,7 @@ A \code{\link{data.frame}} with 18,650 observations and 10 variables:
 rsi_translation
 }
 \description{
-Data set to interpret MIC and disk diffusion to R/SI values. Included guidelines are CLSI (2011-2019) and EUCAST (2011-2020). Use \code{\link[=as.rsi]{as.rsi()}} to transform MICs or disks measurements to R/SI values.
+Data set to interpret MIC and disk diffusion to R/SI values. Included guidelines are CLSI (2010-2019) and EUCAST (2011-2020). Use \code{\link[=as.rsi]{as.rsi()}} to transform MICs or disks measurements to R/SI values.
 }
 \details{
 The repository of this \code{AMR} package contains a file comprising this exact data set: \url{https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt}. This file \strong{allows for machine reading EUCAST and CLSI guidelines}, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically.
--- a/pkgdown/extra.css
+++ b/pkgdown/extra.css
@ -250,3 +250,24 @@ table a:not(.btn):hover, .table a:not(.btn):hover {
  background: #128f7645;
  color: #2c3e50;
 }
+.home-buttons {
+  display: flex;
+  margin-bottom: 5px;
+}
+.home-buttons a {
+	display: grid;
+	text-align: center;
+	font-size: 16px;
+	text-transform: uppercase;
+	width: 25%;
+}
+.home-buttons a:hover {
+	text-decoration: none;
+}
+.home-buttons div {
+	display: grid;
+	padding: 10px;
+}
+.home-buttons .fa {
+	font-size: 3.5em;
+}
--- a/vignettes/datasets.Rmd
+++ b/vignettes/datasets.Rmd
@ -0,0 +1,256 @@
+---
+title: "Data sets for download"
+output: 
+  rmarkdown::html_vignette:
+    toc: true
+    toc_depth: 3
+vignette: >
+  %\VignetteIndexEntry{Data sets for download}
+  %\VignetteEncoding{UTF-8}
+  %\VignetteEngine{knitr::rmarkdown}
+editor_options: 
+  chunk_output_type: console
+---
+
+```{r setup, include = FALSE, results = 'markup'}
+knitr::opts_chunk$set(
+  warning = FALSE,
+  collapse = TRUE,
+  comment = "#",
+  fig.width = 7.5,
+  fig.height = 5
+)
+options(knitr.kable.NA = '')
+
+file_size <- function(...) {
+  size_kb <- file.size(...) / 1024
+  if (size_kb > 500) {
+    paste(round(size_kb / 1024, 1), "MB")
+  } else {
+    paste(round(size_kb, 1), "kB")
+  }
+}
+
+structure_txt <- function(dataset) {
+  paste0("A data set with ",
+         format(nrow(dataset), big.mark = ","), " rows and ", 
+         ncol(dataset), " columns, containing the following column names:\n\n*",
+         paste0(colnames(dataset), collapse = ", "), "*.")
+}
+
+download_txt <- function(filename) {
+    msg <- paste0("Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on ", 
+                trimws(format(file.mtime(paste0("../data/", filename, ".rda")), "%e %B %Y %H:%M:%S %Z")), ".")
+                github_base <- "https://github.com/msberends/AMR/raw/master/data-raw/"
+  gitlab_base <- "https://gitlab.com/msberends/AMR/-/raw/master/data-raw/"
+  filename <- paste0("../data-raw/", filename)
+  txt <- paste0(filename, ".txt")
+  rds <- paste0(filename, ".rds")
+  spss <- paste0(filename, ".sav")
+  stata <- paste0(filename, ".sav")
+  sas <- paste0(filename, ".dta")
+  excel <- paste0(filename, ".xlsx")
+  create_txt <- function(filename, type) {
+    paste0("* ", type, ": ",
+           "[from GitHub](", github_base, filename, "), ",
+           "[from GitLab](", gitlab_base, filename, ") ",
+           "(file size: ", file_size(filename), ")")
+  }
+
+  if (file.exists(rds)) msg <- c(msg, create_txt(rds, "R file (.rds)"))
+  if (file.exists(excel)) msg <- c(msg, create_txt(excel, "Excel workbook (.xlsx)"))
+  if (file.exists(spss)) msg <- c(msg, create_txt(spss, "SPSS file (.sav)"))
+  if (file.exists(stata)) msg <- c(msg, create_txt(stata, "Stata file (.dta)"))
+  if (file.exists(sas)) msg <- c(msg, create_txt(sas, "SAS file (.sas)"))
+  if (file.exists(txt)) msg <- c(msg, create_txt(txt, "Tab separated file (.txt)"))
+  paste0(msg, collapse = "\n\n")
+}
+
+library(AMR)
+library(dplyr)
+
+print_df <- function(x) {
+  x %>% 
+    head() %>% 
+    mutate_all(function(x) {
+      if (is.list(x)) {
+        sapply(x, function(y) {
+          if (length(y) > 3) {
+            paste0(paste(y[1:3], collapse = ", "), ", ...")
+          } else if (length(y) == 0 || is.na(y)) {
+            ""
+          } else {
+            paste(y, collapse = ", ")
+          }
+        })
+      } else {
+        x
+      }
+    }) %>%
+    knitr::kable(align = "c")
+}
+
+```
+
+This package contains a lot of reference data sets that are all reliable, up-to-date and free to download. You can even use them outside of R, for example to train your laboratory information system (LIS) about intrinsic resistance! 
+
+We included them in our `AMR` package, but also automatically 'mirror' them to our public repository in different software formats. On this page, we explain how to download them and how the structure of the data sets look like. The tab separated files **allow for machine reading taxonomic data and EUCAST and CLSI interpretation guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI.
+
+*Note: Years and dates of updates mentioned on this page, are from on `AMR` package version `r utils::packageVersion("AMR")`, online released on `r format(utils::packageDate("AMR"), "%e %B %Y")`. **If you are reading this page from within R, please [visit our website](https://msberends.github.io/AMR/articles/datasets.html) for the latest update.***
+
+## Microorganisms
+
+This data set is in R available as `microorganisms`, after you load the `AMR` package.
+
+#### Source
+
+Our full taxonomy of microorganisms is based on the authoritative and comprehensive:
+
+* [Catalogue of Life](http://www.catalogueoflife.org) (included version: `r AMR:::catalogue_of_life$year`)
+* [List of Prokaryotic names with Standing in Nomenclature](https://lpsn.dsmz.de) (LPSN, included version: `r AMR:::catalogue_of_life$yearmonth_DSMZ`)
+
+#### Structure
+
+`r structure_txt(microorganisms)`
+
+Included per taxonomic kingdom:
+
+```{r, echo = FALSE}
+microorganisms %>% 
+  pull(kingdom) %>% 
+  table() %>% 
+  as.data.frame() %>% 
+  mutate(Freq = format(Freq, big.mark = ",")) %>% 
+  setNames(c("Kingdom", "Number of (sub)species")) %>% 
+  print_df()
+```
+
+
+#### Download
+
+`r download_txt("microorganisms")`
+
+#### Example
+
+Example rows when filtering on genus *Escherichia*:
+
+```{r, echo = FALSE}
+microorganisms %>%
+  filter(genus == "Escherichia") %>% 
+  print_df()
+```
+
+## Antibiotic agents
+
+This data set is in R available as `antibiotics`, after you load the `AMR` package.
+
+#### Source
+
+This data set contains all EARS-Net and ATC codes gathered from WHO and WHONET, and all compound IDs from PubChem. It also contains all brand names (synonyms) as found on PubChem and Defined Daily Doses (DDDs) for oral and parenteral administration.
+
+* [ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology](https://www.whocc.no/atc_ddd_index/) (note: this may not be used for commercial purposes, but is frelly available from the WHO CC website for personal use)
+* [PubChem by the US National Library of Medicine](https://pubchem.ncbi.nlm.nih.gov)
+* [WHONET software 2019](https://whonet.org)
+
+#### Structure
+
+`r structure_txt(antibiotics)`
+
+#### Download
+
+`r download_txt("antibiotics")`
+
+#### Example
+
+Example rows:
+
+```{r, echo = FALSE}
+antibiotics %>%
+  filter(ab %in% colnames(example_isolates)) %>% 
+  print_df()
+```
+
+
+## Antiviral agents
+
+This data set is in R available as `antivirals`, after you load the `AMR` package.
+
+#### Source
+
+This data set contains all ATC codes gathered from WHO and all compound IDs from PubChem. It also contains all brand names (synonyms) as found on PubChem and Defined Daily Doses (DDDs) for oral and parenteral administration.
+
+* [ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology](https://www.whocc.no/atc_ddd_index/) (note: this may not be used for commercial purposes, but is frelly available from the WHO CC website for personal use)
+* [PubChem by the US National Library of Medicine](https://pubchem.ncbi.nlm.nih.gov)
+
+#### Structure
+
+`r structure_txt(antivirals)`
+
+#### Download
+
+`r download_txt("antivirals")`
+
+#### Example
+
+Example rows:
+
+```{r, echo = FALSE}
+antivirals %>%
+  print_df()
+```
+
+
+## Intrinsic bacterial resistance
+
+This data set is in R available as `intrinsic_resistant`, after you load the `AMR` package.
+
+#### Source
+
+This data set contains all defined intrinsic resistance by EUCAST of all bug-drug combinations. 
+
+The data set is based on 'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes', version `r AMR:::EUCAST_VERSION_EXPERT_RULES`.
+
+#### Structure
+
+`r structure_txt(intrinsic_resistant)`
+
+#### Download
+
+`r download_txt("intrinsic_resistant")`
+
+#### Example
+
+Example rows:
+
+```{r, echo = FALSE}
+intrinsic_resistant %>%
+  filter(microorganism %like% "^Klebsiella") %>% 
+  print_df()
+```
+
+
+## Interpretation from MIC values / disk diameters to R/SI
+
+This data set is in R available as `rsi_translation`, after you load the `AMR` package.
+
+#### Source
+
+This data set contains interpretation rules for MIC values and disk diffusion diameters. Included guidelines are CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`) and EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`).
+
+#### Structure
+
+`r structure_txt(rsi_translation)`
+
+#### Download
+
+`r download_txt("rsi_translation")`
+
+#### Example
+
+Example rows:
+
+```{r, echo = FALSE}
+rsi_translation %>% 
+  mutate(ab = ab_name(ab), mo = mo_name(mo)) %>% 
+  print_df()
+```