(v0.7.1.9009) note for WHOCC

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 0.7.1.9008
+Version: 0.7.1.9009
-Date: 2019-07-04
+Date: 2019-07-09
 Title: Antimicrobial Resistance Analysis
 Authors@R: c(
     person(

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 0.7.1.9008
+# AMR 0.7.1.9009
 
 ### New
 * Additional way to calculate co-resistance, i.e. when using multiple antibiotics as input for `portion_*` functions or `count_*` functions. This can be used to determine the empiric susceptibily of a combination therapy. A new parameter `only_all_tested` (**which defaults to `FALSE`**) replaces the old `also_single_tested` 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 `portion` and `count` help pages), where the %SI is being determined:

R/mdro.R

@@ -496,8 +496,8 @@ mdro <- function(x,
 
 #' @rdname mdro
 #' @export
-brmo <- function(..., guideline = "BRMO") {
+brmo <- function(x, guideline = "BRMO", ...) {
-  mdro(..., guideline = "BRMO")
+  mdro(x, guideline = "BRMO", ...)
 }
 
 #' @rdname mdro

R/mo.R

@@ -483,7 +483,7 @@ exec_as.mo <- function(x,
     x <- gsub("(alpha|beta|gamma).?ha?emoly", "\\1-haemoly", x)
     # remove genus as first word
     x <- gsub("^Genus ", "", x)
-    # allow characters that resemble others
+    # allow characters that resemble others, but not on first try
     if (initial_search == FALSE) {
       x <- tolower(x)
       x <- gsub("[iy]+", "[iy]+", x)

R/mo_property.R

@@ -157,7 +157,7 @@ mo_shortname <- function(x, language = get_locale(), ...) {
   # exceptions for Staphylococci
   shortnames[shortnames == "S. coagulase-negative" ] <- "CoNS"
   shortnames[shortnames == "S. coagulase-positive" ] <- "CoPS"
-  # exceptions for Streptococci
+  # exceptions for Streptococci: Streptococcus Group A -> GAS
   shortnames[shortnames %like% "S. group [ABCDFGHK]"] <- paste0("G", gsub("S. group ([ABCDFGHK])", "\\1", shortnames[shortnames %like% "S. group [ABCDFGHK]"]), "S")
 
   load_mo_failures_uncertainties_renamed(metadata)

R/whocc.R

@@ -24,7 +24,7 @@
 #' All antimicrobial drugs and their official names, ATC codes, ATC groups and defined daily dose (DDD) are included in this package, using the WHO Collaborating Centre for Drug Statistics Methodology.
 #' @section WHOCC:
 #' \if{html}{\figure{logo_who.png}{options: height=60px style=margin-bottom:5px} \cr}
-#' This package contains \strong{all ~450 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}).
+#' This package contains \strong{all ~450 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}). \strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See \url{https://www.whocc.no/copyright_disclaimer/}.}
 #'
 #' These have become the gold standard for international drug utilisation monitoring and research.
 #'

data-raw/reproduction_of_microorganisms_new.R

@@ -0,0 +1,657 @@
+# ---------------------------------------------------------------------------------
+# Reproduction of the `microorganisms` data set
+# ---------------------------------------------------------------------------------
+# Data retrieved from:
+#
+# [1] Catalogue of Life (CoL) through the Encyclopaedia of Life
+#     https://opendata.eol.org/dataset/catalogue-of-life/
+#      * Download the resource file with a name like "Catalogue of Life yyyy-mm-dd"
+#      * Extract "taxon.tab"
+#
+# [2] Global Biodiversity Information Facility (GBIF)
+#     https://doi.org/10.15468/39omei
+#     * Extract "Taxon.tsv"
+#
+# [3] Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ)
+#     https://www.dsmz.de/support/bacterial-nomenclature-up-to-date-downloads.html
+#     * Download the latest "Complete List" as xlsx file (DSMZ_bactnames.xlsx)
+# ---------------------------------------------------------------------------------
+
+library(dplyr)
+library(AMR)
+
+data_col <- data.table::fread("Documents/taxon.tab")
+data_gbif <- data.table::fread("Documents/Taxon.tsv")
+
+# read the xlsx file from DSMZ (only around 2.5 MB):
+data_dsmz <- readxl::read_xlsx("Downloads/DSMZ_bactnames.xlsx")
+
+# the CoL data is over 3.7M rows:
+data_col %>% freq(kingdom)
+#      Item             Count   Percent   Cum. Count   Cum. Percent
+# ---  ----------  ----------  --------  -----------  -------------
+# 1    Animalia     2,225,627     59.1%    2,225,627          59.1%
+# 2    Plantae      1,177,412     31.3%    3,403,039          90.4%
+# 3    Fungi          290,145      7.7%    3,693,184          98.1%
+# 4    Chromista       47,126      1.3%    3,740,310          99.3%
+# 5    Bacteria        14,478      0.4%    3,754,788          99.7%
+# 6    Protozoa         6,060      0.2%    3,760,848          99.9%
+# 7    Viruses          3,827      0.1%    3,764,675         100.0%
+# 8    Archaea            610      0.0%    3,765,285         100.0%
+
+# the GBIF data is over 5.8M rows:
+data_gbif %>% freq(kingdom)
+#      Item                  Count   Percent   Cum. Count   Cum. Percent
+# ---  ---------------  ----------  --------  -----------  -------------
+# 1    Animalia          3,264,138     55.7%    3,264,138          55.7%
+# 2    Plantae           1,814,962     31.0%    5,079,100          86.7%
+# 3    Fungi               538,086      9.2%    5,617,186          95.9%
+# 4    Chromista           181,374      3.1%    5,798,560          99.0%
+# 5    Bacteria             24,048      0.4%    5,822,608          99.4%
+# 6    Protozoa             15,138      0.3%    5,837,746          99.7%
+# 7    incertae sedis        9,995      0.2%    5,847,741          99.8%
+# 8    Viruses               9,630      0.2%    5,857,371         100.0%
+# 9    Archaea                 771      0.0%    5,858,142         100.0%
+
+
+# Clean up helper function ------------------------------------------------
+clean_new <- function(new) {
+  new %>%
+    # only the ones that have no new ID to refer to a newer name
+    filter(is.na(col_id_new)) %>%
+    filter(
+      (
+        # we only want all MICROorganisms and no viruses
+        !kingdom %in% c("Animalia", "Chromista", "Plantae", "Viruses")
+        # and not all fungi: Aspergillus, Candida, Trichphyton and Pneumocystis are the most important,
+        # so only keep these orders from the fungi:
+        & !(kingdom == "Fungi"
+            & !order %in% c("Eurotiales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales", "Onygenales", "Pneumocystales"))
+      )
+      # or the family has to contain a genus we found in our hospitals last decades (Northern Netherlands, 2002-2018)
+      | genus %in% c("Absidia", "Acremonium", "Actinotignum", "Alternaria", "Anaerosalibacter", "Ancylostoma", "Anisakis", "Apophysomyces",
+                     "Arachnia", "Ascaris", "Aureobacterium", "Aureobasidium", "Balantidum", "Bilophilia", "Branhamella", "Brochontrix",
+                     "Brugia", "Calymmatobacterium", "Catabacter", "Chilomastix", "Chryseomonas", "Cladophialophora", "Cladosporium",
+                     "Clonorchis", "Cordylobia", "Curvularia", "Demodex", "Dermatobia", "Diphyllobothrium", "Dracunculus", "Echinococcus",
+                     "Enterobius", "Euascomycetes", "Exophiala", "Fasciola", "Fusarium", "Hendersonula", "Hymenolepis", "Kloeckera",
+                     "Koserella", "Larva", "Leishmania", "Lelliottia", "Loa", "Lumbricus", "Malassezia", "Metagonimus", "Molonomonas",
+                     "Mucor", "Nattrassia", "Necator", "Novospingobium", "Onchocerca", "Opistorchis", "Paragonimus", "Paramyxovirus",
+                     "Pediculus", "Phoma", "Phthirus", "Pityrosporum", "Pseudallescheria", "Pulex", "Rhizomucor", "Rhizopus", "Rhodotorula",
+                     "Salinococcus", "Sanguibacteroides", "Schistosoma", "Scopulariopsis", "Scytalidium", "Sporobolomyces", "Stomatococcus",
+                     "Strongyloides", "Syncephalastraceae", "Taenia", "Torulopsis", "Trichinella", "Trichobilharzia", "Trichomonas",
+                     "Trichosporon", "Trichuris", "Trypanosoma", "Wuchereria")) %>%
+    mutate(
+      authors2 = iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT"),
+      # remove leading and trailing brackets
+      authors2 = gsub("^[(](.*)[)]$", "\\1", authors2),
+      # only take part after brackets if there's a name
+      authors2 = ifelse(grepl(".*[)] [a-zA-Z]+.*", authors2),
+                        gsub(".*[)] (.*)", "\\1", authors2),
+                        authors2),
+      # get year from last 4 digits
+      lastyear = as.integer(gsub(".*([0-9]{4})$", "\\1", authors2)),
+      # can never be later than now
+      lastyear = ifelse(lastyear > as.integer(format(Sys.Date(), "%Y")),
+                        NA,
+                        lastyear),
+      # get authors without last year
+      authors = gsub("(.*)[0-9]{4}$", "\\1", authors2),
+      # remove nonsense characters from names
+      authors = gsub("[^a-zA-Z,'& -]", "", authors),
+      # remove trailing and leading spaces
+      authors = trimws(authors),
+      # only keep first author and replace all others by 'et al'
+      authors = gsub("(,| and| et| &| ex| emend\\.?) .*", " et al.", authors),
+      # et al. always with ending dot
+      authors = gsub(" et al\\.?", " et al.", authors),
+      authors = gsub(" ?,$", "", authors),
+      # don't start with 'sensu' or 'ehrenb'
+      authors = gsub("^(sensu|Ehrenb.?) ", "", authors, ignore.case = TRUE),
+      # no initials, only surname
+      authors = gsub("^([A-Z]+ )+", "", authors, ignore.case = FALSE),
+      # combine author and year if year is available
+      ref = ifelse(!is.na(lastyear),
+                   paste0(authors, ", ", lastyear),
+                   authors),
+      # fix beginning and ending
+      ref = gsub(", $", "", ref),
+      ref = gsub("^, ", "", ref)) %>%
+    # remove text if it contains 'Not assigned' like phylum in viruses
+    mutate_all(~gsub("Not assigned", "", .)) %>%
+    # Remove non-ASCII characters (these are not allowed by CRAN)
+    lapply(iconv, from = "UTF-8", to = "ASCII//TRANSLIT") %>%
+    as_tibble(stringsAsFactors = FALSE) %>%
+    mutate(fullname = trimws(case_when(rank == "family" ~ family,
+                                       rank == "order" ~ order,
+                                       rank == "class" ~ class,
+                                       rank == "phylum" ~ phylum,
+                                       rank == "kingdom" ~ kingdom,
+                                       TRUE ~ paste(genus, species, subspecies))))
+}
+clean_old <- function(old, new) {
+  old %>%
+    # only the ones that exist in the new data set
+    filter(col_id_new %in% new$col_id) %>%
+    mutate(
+      authors2 = iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT"),
+      # remove leading and trailing brackets
+      authors2 = gsub("^[(](.*)[)]$", "\\1", authors2),
+      # only take part after brackets if there's a name
+      authors2 = ifelse(grepl(".*[)] [a-zA-Z]+.*", authors2),
+                        gsub(".*[)] (.*)", "\\1", authors2),
+                        authors2),
+      # get year from last 4 digits
+      lastyear = as.integer(gsub(".*([0-9]{4})$", "\\1", authors2)),
+      # can never be later than now
+      lastyear = ifelse(lastyear > as.integer(format(Sys.Date(), "%Y")),
+                        NA,
+                        lastyear),
+      # get authors without last year
+      authors = gsub("(.*)[0-9]{4}$", "\\1", authors2),
+      # remove nonsense characters from names
+      authors = gsub("[^a-zA-Z,'& -]", "", authors),
+      # remove trailing and leading spaces
+      authors = trimws(authors),
+      # only keep first author and replace all others by 'et al'
+      authors = gsub("(,| and| et| &| ex| emend\\.?) .*", " et al.", authors),
+      # et al. always with ending dot
+      authors = gsub(" et al\\.?", " et al.", authors),
+      authors = gsub(" ?,$", "", authors),
+      # don't start with 'sensu' or 'ehrenb'
+      authors = gsub("^(sensu|Ehrenb.?) ", "", authors, ignore.case = TRUE),
+      # no initials, only surname
+      authors = gsub("^([A-Z]+ )+", "", authors, ignore.case = FALSE),
+      # combine author and year if year is available
+      ref = ifelse(!is.na(lastyear),
+                   paste0(authors, ", ", lastyear),
+                   authors),
+      # fix beginning and ending
+      ref = gsub(", $", "", ref),
+      ref = gsub("^, ", "", ref)) %>%
+    # remove text if it contains 'Not assigned' like phylum in viruses
+    mutate_all(~gsub("Not assigned", "", .)) %>%
+    # Remove non-ASCII characters (these are not allowed by CRAN)
+    lapply(iconv, from = "UTF-8", to = "ASCII//TRANSLIT") %>%
+    as_tibble(stringsAsFactors = FALSE) %>%
+    select(col_id_new, fullname, ref, authors2) %>%
+    left_join(new %>% select(col_id, fullname_new = fullname), by = c(col_id_new = "col_id")) %>%
+    mutate(fullname = trimws(
+      gsub("(.*)[(].*", "\\1",
+           stringr::str_replace(
+             string = fullname,
+             pattern = stringr::fixed(authors2),
+             replacement = "")) %>%
+        gsub(" (var|f|subsp)[.]", "", .))) %>%
+    select(-c("col_id_new", "authors2")) %>%
+    filter(!is.na(fullname), !is.na(fullname_new)) %>%
+    filter(fullname != fullname_new, !fullname %like% "^[?]")
+}
+
+# clean CoL and GBIF ----
+# clean data_col
+data_col <- data_col %>%
+  as_tibble() %>%
+  select(col_id = taxonID,
+         col_id_new = acceptedNameUsageID,
+         fullname = scientificName,
+         kingdom,
+         phylum,
+         class,
+         order,
+         family,
+         genus,
+         species = specificEpithet,
+         subspecies = infraspecificEpithet,
+         rank = taxonRank,
+         ref = scientificNameAuthorship,
+         species_id = furtherInformationURL) %>%
+  mutate(source = "CoL")
+# split into old and new
+data_col.new <- data_col %>% clean_new()
+data_col.old <- data_col %>% clean_old(new = data_col.new)
+rm(data_col)
+
+# clean data_gbif
+data_gbif <- data_gbif %>%
+  as_tibble() %>%
+  filter(
+    # no uncertain taxonomic placements
+    taxonRemarks != "doubtful",
+    kingdom != "incertae sedis",
+    taxonRank != "unranked") %>%
+  transmute(col_id = taxonID,
+            col_id_new = acceptedNameUsageID,
+            fullname = scientificName,
+            kingdom,
+            phylum,
+            class,
+            order,
+            family,
+            genus,
+            species = specificEpithet,
+            subspecies = infraspecificEpithet,
+            rank = taxonRank,
+            ref = scientificNameAuthorship,
+            species_id = as.character(parentNameUsageID)) %>%
+  mutate(source = "GBIF")
+# split into old and new
+data_gbif.new <- data_gbif %>% clean_new()
+data_gbif.old <- data_gbif %>% clean_old(new = data_gbif.new)
+rm(data_gbif)
+
+# put CoL and GBIF together ----
+MOs.new <- bind_rows(data_col.new,
+                     data_gbif.new) %>%
+  mutate(taxonomic_tree_length = nchar(trimws(paste(kingdom, phylum, class, order, family, genus, species, subspecies)))) %>%
+  arrange(desc(taxonomic_tree_length)) %>%
+  distinct(fullname, .keep_all = TRUE) %>%
+  select(-c("col_id_new", "authors2", "authors", "lastyear", "taxonomic_tree_length")) %>%
+  arrange(fullname)
+MOs.old <- bind_rows(data_col.old,
+                     data_gbif.old) %>%
+  distinct(fullname, .keep_all = TRUE) %>%
+  arrange(fullname)
+
+# clean up DSMZ ---
+data_dsmz <- data_dsmz %>%
+  as_tibble() %>%
+  transmute(col_id = NA_integer_,
+            col_id_new = NA_integer_,
+            fullname = "",
+            # kingdom = "",
+            # phylum = "",
+            # class = "",
+            # order = "",
+            # family = "",
+            genus = ifelse(is.na(GENUS), "", GENUS),
+            species = ifelse(is.na(SPECIES), "", SPECIES),
+            subspecies = ifelse(is.na(SUBSPECIES), "", SUBSPECIES),
+            rank = ifelse(species == "", "genus", "species"),
+            ref = AUTHORS,
+            species_id = as.character(RECORD_NO),
+            source = "DSMZ")
+
+# DSMZ only contains genus/(sub)species, try to find taxonomic properties based on genus and data_col
+ref_taxonomy <- MOs.new %>%
+  distinct(genus, .keep_all = TRUE) %>%
+  filter(family != "") %>%
+  filter(genus %in% data_dsmz$genus) %>%
+  distinct(genus, .keep_all = TRUE) %>%
+  select(kingdom, phylum, class, order, family, genus)
+
+data_dsmz <- data_dsmz %>%
+  left_join(ref_taxonomy, by = "genus") %>%
+  mutate(kingdom = "Bacteria")
+
+data_dsmz.new <- data_dsmz %>%
+  clean_new() %>%
+  distinct(fullname, .keep_all = TRUE) %>%
+  select(colnames(MOs.new)) %>%
+  arrange(fullname)
+
+# combine everything ----
+MOs <- bind_rows(MOs.new,
+                 data_dsmz.new) %>%
+  distinct(fullname, .keep_all = TRUE) %>%
+  # not the ones that are old
+  filter(!fullname %in% MOs.old$fullname) %>%
+  arrange(fullname) %>%
+  mutate(col_id = ifelse(source != "CoL", NA_integer_, col_id)) %>%
+  filter(fullname != "")
+
+rm(data_col.new)
+rm(data_col.old)
+rm(data_gbif.new)
+rm(data_gbif.old)
+rm(data_dsmz)
+rm(data_dsmz.new)
+rm(ref_taxonomy)
+rm(MOs.new)
+
+MOs.bak <- MOs
+
+# Trichomonas trick ----
+# for species in Trypanosoma and Trichomonas we observe al lot of taxonomic info missing
+MOs %>% filter(genus %in% c("Trypanosoma", "Trichomonas")) %>% View()
+MOs[which(MOs$genus == "Trypanosoma"), "kingdom"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$kingdom
+MOs[which(MOs$genus == "Trypanosoma"), "phylum"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$phylum
+MOs[which(MOs$genus == "Trypanosoma"), "class"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$class
+MOs[which(MOs$genus == "Trypanosoma"), "order"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$order
+MOs[which(MOs$genus == "Trypanosoma"), "family"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$family
+MOs[which(MOs$genus == "Trichomonas"), "kingdom"] <- MOs[which(MOs$fullname == "Trichomonas"),]$kingdom
+MOs[which(MOs$genus == "Trichomonas"), "phylum"] <- MOs[which(MOs$fullname == "Trichomonas"),]$phylum
+MOs[which(MOs$genus == "Trichomonas"), "class"] <- MOs[which(MOs$fullname == "Trichomonas"),]$class
+MOs[which(MOs$genus == "Trichomonas"), "order"] <- MOs[which(MOs$fullname == "Trichomonas"),]$order
+MOs[which(MOs$genus == "Trichomonas"), "family"] <- MOs[which(MOs$fullname == "Trichomonas"),]$family
+
+# fill taxonomic properties that are missing
+MOs <- MOs %>%
+  mutate(phylum = ifelse(phylum %in% c(NA, ""), "(unknown phylum)", phylum),
+         class = ifelse(class %in% c(NA, ""), "(unknown class)", class),
+         order = ifelse(order %in% c(NA, ""), "(unknown order)", order),
+         family = ifelse(family %in% c(NA, ""), "(unknown family)", family))
+
+# Abbreviations ----
+# Add abbreviations so we can easily know which ones are which ones.
+# These will become valid and unique microbial IDs for the AMR package.
+MOs <- MOs %>%
+  arrange(kingdom, fullname) %>%
+  group_by(kingdom) %>%
+  mutate(abbr_other = case_when(
+    rank == "family" ~ paste0("[FAM]_",
+                              abbreviate(family,
+                                         minlength = 8,
+                                         use.classes = TRUE,
+                                         method = "both.sides",
+                                         strict = FALSE)),
+    rank == "order" ~ paste0("[ORD]_",
+                             abbreviate(order,
+                                        minlength = 8,
+                                        use.classes = TRUE,
+                                        method = "both.sides",
+                                        strict = FALSE)),
+    rank == "class" ~ paste0("[CLS]_",
+                             abbreviate(class,
+                                        minlength = 8,
+                                        use.classes = TRUE,
+                                        method = "both.sides",
+                                        strict = FALSE)),
+    rank == "phylum" ~ paste0("[PHL]_",
+                              abbreviate(phylum,
+                                         minlength = 8,
+                                         use.classes = TRUE,
+                                         method = "both.sides",
+                                         strict = FALSE)),
+    rank == "kingdom" ~ paste0("[KNG]_", kingdom),
+    TRUE ~ NA_character_
+  )) %>%
+  # abbreviations determined per kingdom and family
+  # becuase they are part of the abbreviation
+  mutate(abbr_genus = abbreviate(genus,
+                                 minlength = 7,
+                                 use.classes = TRUE,
+                                 method = "both.sides",
+                                 strict = FALSE)) %>%
+  ungroup() %>%
+  group_by(genus) %>%
+  # species abbreviations may be the same between genera
+  # because the genus abbreviation is part of the abbreviation
+  mutate(abbr_species = abbreviate(stringr::str_to_title(species),
+                                   minlength = 3,
+                                   use.classes = FALSE,
+                                   method = "both.sides")) %>%
+  ungroup() %>%
+  group_by(genus, species) %>%
+  mutate(abbr_subspecies = abbreviate(stringr::str_to_title(subspecies),
+                                      minlength = 3,
+                                      use.classes = FALSE,
+                                      method = "both.sides")) %>%
+  ungroup() %>%
+  # remove trailing underscores
+  mutate(mo = gsub("_+$", "",
+                   toupper(paste(
+                     # first character: kingdom
+                     ifelse(kingdom %in% c("Animalia", "Plantae"),
+                            substr(kingdom, 1, 2),
+                            substr(kingdom, 1, 1)),
+                     # next: genus, species, subspecies
+                     ifelse(is.na(abbr_other),
+                            paste(abbr_genus,
+                                  abbr_species,
+                                  abbr_subspecies,
+                                  sep = "_"),
+                            abbr_other),
+                     sep = "_")))) %>%
+  mutate(mo = ifelse(duplicated(.$mo),
+                     # these one or two must be unique too
+                     paste0(mo, "1"),
+                     mo),
+         fullname = ifelse(fullname == "",
+                           trimws(paste(genus, species, subspecies)),
+                           fullname)) %>%
+  # put `mo` in front, followed by the rest
+  select(mo, everything(), -abbr_other, -abbr_genus, -abbr_species, -abbr_subspecies)
+
+# add non-taxonomic entries
+MOs <- MOs %>%
+  bind_rows(
+    # Unknowns
+    data.frame(mo = "UNKNOWN",
+               col_id = NA_integer_,
+               fullname = "(unknown name)",
+               kingdom = "(unknown kingdom)",
+               phylum = "(unknown phylum)",
+               class = "(unknown class)",
+               order = "(unknown order)",
+               family = "(unknown family)",
+               genus = "(unknown genus)",
+               species = "(unknown species)",
+               subspecies = "(unknown subspecies)",
+               rank = "(unknown rank)",
+               ref = NA_character_,
+               species_id = "",
+               source = "manually added",
+               stringsAsFactors = FALSE),
+    data.frame(mo = "B_GRAMN",
+               col_id = NA_integer_,
+               fullname = "(unknown Gram-negatives)",
+               kingdom = "Bacteria",
+               phylum = "(unknown phylum)",
+               class = "(unknown class)",
+               order = "(unknown order)",
+               family = "(unknown family)",
+               genus = "(unknown Gram-negatives)",
+               species = "(unknown species)",
+               subspecies = "(unknown subspecies)",
+               rank = "species",
+               ref = NA_character_,
+               species_id = "",
+               source = "manually added",
+               stringsAsFactors = FALSE),
+    data.frame(mo = "B_GRAMP",
+               col_id = NA_integer_,
+               fullname = "(unknown Gram-positives)",
+               kingdom = "Bacteria",
+               phylum = "(unknown phylum)",
+               class = "(unknown class)",
+               order = "(unknown order)",
+               family = "(unknown family)",
+               genus = "(unknown Gram-positives)",
+               species = "(unknown species)",
+               subspecies = "(unknown subspecies)",
+               rank = "species",
+               ref = NA_character_,
+               species_id = "",
+               source = "manually added",
+               stringsAsFactors = FALSE),
+    # CoNS
+    MOs %>%
+      filter(genus == "Staphylococcus", species == "") %>% .[1,] %>%
+      mutate(mo = paste(mo, "CNS", sep = "_"),
+             rank = "species",
+             col_id = NA_integer_,
+             species = "coagulase-negative",
+             fullname = "Coagulase-negative Staphylococcus (CoNS)",
+             ref = NA_character_,
+             species_id = "",
+             source = "manually added"),
+    # CoPS
+    MOs %>%
+      filter(genus == "Staphylococcus", species == "") %>% .[1,] %>%
+      mutate(mo = paste(mo, "CPS", sep = "_"),
+             rank = "species",
+             col_id = NA_integer_,
+             species = "coagulase-positive",
+             fullname = "Coagulase-positive Staphylococcus (CoPS)",
+             ref = NA_character_,
+             species_id = "",
+             source = "manually added"),
+    # Streptococci groups A, B, C, F, H, K
+    MOs %>%
+      filter(genus == "Streptococcus", species == "pyogenes") %>% .[1,] %>%
+      # we can keep all other details, since S. pyogenes is the only member of group A
+      mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRA", sep = "_"),
+             species = "group A" ,
+             fullname = "Streptococcus group A"),
+    MOs %>%
+      filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
+      # we can keep all other details, since S. agalactiae is the only member of group B
+      mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRB", sep = "_"),
+             species = "group B" ,
+             fullname = "Streptococcus group B"),
+    MOs %>%
+      filter(genus == "Streptococcus", species == "dysgalactiae") %>% .[1,] %>%
+      mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRC", sep = "_"),
+             col_id = NA_integer_,
+             species = "group C" ,
+             fullname = "Streptococcus group C",
+             ref = NA_character_,
+             species_id = "",
+             source = "manually added"),
+    MOs %>%
+      filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
+      mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRD", sep = "_"),
+             col_id = NA_integer_,
+             species = "group D" ,
+             fullname = "Streptococcus group D",
+             ref = NA_character_,
+             species_id = "",
+             source = "manually added"),
+    MOs %>%
+      filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
+      mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRF", sep = "_"),
+             col_id = NA_integer_,
+             species = "group F" ,
+             fullname = "Streptococcus group F",
+             ref = NA_character_,
+             species_id = "",
+             source = "manually added"),
+    MOs %>%
+      filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
+      mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRG", sep = "_"),
+             col_id = NA_integer_,
+             species = "group G" ,
+             fullname = "Streptococcus group G",
+             ref = NA_character_,
+             species_id = "",
+             source = "manually added"),
+    MOs %>%
+      filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
+      mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRH", sep = "_"),
+             col_id = NA_integer_,
+             species = "group H" ,
+             fullname = "Streptococcus group H",
+             ref = NA_character_,
+             species_id = "",
+             source = "manually added"),
+    MOs %>%
+      filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
+      mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRK", sep = "_"),
+             col_id = NA_integer_,
+             species = "group K" ,
+             fullname = "Streptococcus group K",
+             ref = NA_character_,
+             species_id = "",
+             source = "manually added"),
+    # Beta-haemolytic Streptococci
+    MOs %>%
+      filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
+      mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "HAE", sep = "_"),
+             col_id = NA_integer_,
+             species = "beta-haemolytic" ,
+             fullname = "Beta-haemolytic Streptococcus",
+             ref = NA_character_,
+             species_id = "",
+             source = "manually added")
+  )
+
+
+# everything distinct?
+sum(duplicated(MOs$mo))
+colnames(MOs)
+
+# set prevalence per species
+MOs <- MOs %>%
+  mutate(prevalence = case_when(
+    class == "Gammaproteobacteria"
+    | genus %in% c("Enterococcus", "Staphylococcus", "Streptococcus")
+    | mo %in% c("UNKNOWN", "B_GRAMN", "B_GRAMP")
+    ~ 1,
+    phylum %in% c("Proteobacteria",
+                  "Firmicutes",
+                  "Actinobacteria",
+                  "Sarcomastigophora")
+    | genus %in% c("Aspergillus",
+                   "Bacteroides",
+                   "Candida",
+                   "Capnocytophaga",
+                   "Chryseobacterium",
+                   "Cryptococcus",
+                   "Elisabethkingia",
+                   "Flavobacterium",
+                   "Fusobacterium",
+                   "Giardia",
+                   "Leptotrichia",
+                   "Mycoplasma",
+                   "Prevotella",
+                   "Rhodotorula",
+                   "Treponema",
+                   "Trichophyton",
+                   "Trichomonas",
+                   "Ureaplasma")
+    | rank %in% c("kingdom", "phylum", "class", "order", "family")
+    ~ 2,
+    TRUE ~ 3
+  ))
+
+# arrange
+MOs <- MOs %>% arrange(fullname)
+
+# transform
+MOs <- as.data.frame(MOs, stringsAsFactors = FALSE)
+MOs.old <- as.data.frame(MOs.old, stringsAsFactors = FALSE)
+class(MOs$mo) <- "mo"
+MOs$col_id <- as.integer(MOs$col_id)
+
+# get differences in MO codes between this data and the package version
+MO_diff <- AMR::microorganisms %>%
+  mutate(pastedtext = paste(mo, fullname)) %>%
+  filter(!pastedtext %in% (MOs %>% mutate(pastedtext = paste(mo, fullname)) %>% pull(pastedtext))) %>%
+  select(mo_old = mo, fullname, pastedtext) %>%
+  left_join(MOs %>%
+              transmute(mo_new = mo, fullname_new = fullname, pastedtext = paste(mo, fullname)), "pastedtext") %>%
+  select(mo_old, mo_new, fullname_new)
+
+mo_diff2 <- AMR::microorganisms %>%
+  select(mo, fullname) %>%
+  left_join(MOs %>%
+              select(mo, fullname),
+            by = "fullname",
+            suffix = c("_old", "_new")) %>%
+  filter(mo_old != mo_new,
+         #!mo_new %in% mo_old,
+         !mo_old %like% "\\[")
+
+mo_diff3 <- tibble(previous_old = names(AMR:::make_trans_tbl()),
+                   previous_new = AMR:::make_trans_tbl()) %>%
+  left_join(AMR::microorganisms %>% select(mo, fullname), by = c(previous_new = "mo")) %>%
+  left_join(MOs %>% select(mo_new = mo, fullname), by = "fullname")
+
+# what did we win most?
+MOs %>% filter(!fullname %in% AMR::microorganisms$fullname) %>% freq(genus)
+# what did we lose most?
+AMR::microorganisms %>%
+  filter(kingdom !=  "Chromista" & !fullname %in% MOs$fullname & !fullname %in% MOs.old$fullname) %>%
+  freq(genus)
+
+
+# save
+saveRDS(MOs, "microorganisms.rds")
+saveRDS(MOs.old, "microorganisms.old.rds")
+
+# on the server, do:
+usethis::use_data(microorganisms, overwrite = TRUE, version = 2)
+usethis::use_data(microorganisms.old, overwrite = TRUE, version = 2)
+rm(microorganisms)
+rm(microorganisms.old)
+# and update the year in R/data.R

docs/LICENSE-text.html

@@ -78,7 +78,7 @@
       </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">0.7.1.9008</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/articles/index.html

@@ -78,7 +78,7 @@
       </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">0.7.1.9008</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/authors.html

@@ -78,7 +78,7 @@
       </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">0.7.1.9008</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/extra.css

@@ -187,8 +187,10 @@ table a:not(.btn):hover, .table a:not(.btn):hover {
 
 /* text below header in manual overview */
 .template-reference-index h2 ~ p {
-  font-size: 110%;
+  font-size: 16px;
-  /* font-weight: bold; */
+}
+.template-reference-topic h2 {
+  font-size: 24px;
 }
 
 /* logos on index page */

docs/extra.js

@@ -46,6 +46,9 @@ $( document ).ready(function() {
     window.location.replace(url_new);
   }
 
+  // Replace 'Value' in manual to 'Returned value'
+  $(".template-reference-topic h2#value").text("Returned value");
+
   // PR for 'R for Data Science' on How To pages
   if ($(".template-article").length > 0) {
     $('#sidebar').prepend(

docs/index.html

@@ -42,7 +42,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9008</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 
@@ -296,6 +296,7 @@
 <img src="reference/figures/logo_who.png" height="75px" class="logo_img"><p class="logo_txt">WHO Collaborating Centre for Drug Statistics Methodology</p>
 </div>
 <p>This package contains <strong>all ~450 antimicrobial drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD, oral and IV) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://www.whocc.no" class="uri">https://www.whocc.no</a>) and the <a href="http://ec.europa.eu/health/documents/community-register/html/atc.htm">Pharmaceuticals Community Register of the European Commission</a>.</p>
+<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See \url{<a href="https://www.whocc.no/copyright_disclaimer/" class="uri">https://www.whocc.no/copyright_disclaimer/</a>}.</strong></p>
 <p>Read more about the data from WHOCC <a href="./reference/WHOCC.html">in our manual</a>.</p>
 </div>
 <div id="whonet--ears-net" class="section level4">

docs/news/index.html

@@ -78,7 +78,7 @@
       </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">0.7.1.9008</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 
@@ -232,9 +232,9 @@
       
     </div>
 
-    <div id="amr-0719008" class="section level1">
+    <div id="amr-0719009" class="section level1">
 <h1 class="page-header">
-<a href="#amr-0719008" class="anchor"></a>AMR 0.7.1.9008<small> Unreleased </small>
+<a href="#amr-0719009" class="anchor"></a>AMR 0.7.1.9009<small> Unreleased </small>
 </h1>
 <div id="new" class="section level3">
 <h3 class="hasAnchor">
@@ -1196,7 +1196,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
     <div id="tocnav">
       <h2>Contents</h2>
       <ul class="nav nav-pills nav-stacked">
-        <li><a href="#amr-0719008">0.7.1.9008</a></li>
+        <li><a href="#amr-0719009">0.7.1.9009</a></li>
         <li><a href="#amr-071">0.7.1</a></li>
         <li><a href="#amr-070">0.7.0</a></li>
         <li><a href="#amr-061">0.6.1</a></li>

docs/reference/WHOCC.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9005</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 
@@ -246,7 +246,7 @@
 
     
     <p><img src='figures/logo_who.png' height=60px style=margin-bottom:5px /> <br />
-This package contains <strong>all ~450 antimicrobial drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href='https://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>).</p>
+This package contains <strong>all ~450 antimicrobial drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href='https://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>). <strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See <a href='https://www.whocc.no/copyright_disclaimer/'>https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
 <p>These have become the gold standard for international drug utilisation monitoring and research.</p>
 <p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
     

docs/reference/antibiotics.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9005</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 
@@ -276,7 +276,7 @@
 
     
     <p><img src='figures/logo_who.png' height=60px style=margin-bottom:5px /> <br />
-This package contains <strong>all ~450 antimicrobial drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href='https://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>).</p>
+This package contains <strong>all ~450 antimicrobial drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href='https://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>). <strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See <a href='https://www.whocc.no/copyright_disclaimer/'>https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
 <p>These have become the gold standard for international drug utilisation monitoring and research.</p>
 <p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
     

docs/reference/as.ab.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9005</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 
@@ -274,7 +274,7 @@
 
     
     <p><img src='figures/logo_who.png' height=60px style=margin-bottom:5px /> <br />
-This package contains <strong>all ~450 antimicrobial drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href='https://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>).</p>
+This package contains <strong>all ~450 antimicrobial drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href='https://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>). <strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See <a href='https://www.whocc.no/copyright_disclaimer/'>https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
 <p>These have become the gold standard for international drug utilisation monitoring and research.</p>
 <p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
     

docs/reference/as.mo.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/reference/catalogue_of_life.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9005</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/reference/catalogue_of_life_version.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9005</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/reference/freq.html

@@ -81,7 +81,7 @@ top_freq can be used to get the top/bottom n items of a frequency table, with co
       </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">0.7.1.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/reference/index.html

@@ -78,7 +78,7 @@
       </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">0.7.1.9008</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/reference/mdro.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 
@@ -244,7 +244,7 @@
     <pre class="usage"><span class='fu'>mdro</span>(<span class='no'>x</span>, <span class='kw'>guideline</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
   <span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='no'>...</span>)
 
-<span class='fu'>brmo</span>(<span class='no'>...</span>, <span class='kw'>guideline</span> <span class='kw'>=</span> <span class='st'>"BRMO"</span>)
+<span class='fu'>brmo</span>(<span class='no'>x</span>, <span class='kw'>guideline</span> <span class='kw'>=</span> <span class='st'>"BRMO"</span>, <span class='no'>...</span>)
 
 <span class='fu'>mrgn</span>(<span class='no'>x</span>, <span class='kw'>guideline</span> <span class='kw'>=</span> <span class='st'>"MRGN"</span>, <span class='no'>...</span>)
 

docs/reference/microorganisms.codes.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9005</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/reference/microorganisms.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9005</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/reference/microorganisms.old.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9005</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

docs/reference/mo_property.html

@@ -80,7 +80,7 @@
       </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">0.7.1.9007</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9009</span>
       </span>
     </div>
 

index.md

@@ -117,6 +117,8 @@ Read more about the data from the Catalogue of Life [in our manual](./reference/
 
 This package contains **all ~450 antimicrobial drugs** and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD, oral and IV) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, https://www.whocc.no) and the [Pharmaceuticals Community Register of the European Commission](http://ec.europa.eu/health/documents/community-register/html/atc.htm).
 
+**NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See \url{https://www.whocc.no/copyright_disclaimer/}.**
+
 Read more about the data from WHOCC [in our manual](./reference/WHOCC.html).
 
 #### WHONET / EARS-Net

man/WHOCC.Rd

@@ -9,7 +9,7 @@ All antimicrobial drugs and their official names, ATC codes, ATC groups and defi
 \section{WHOCC}{
 
 \if{html}{\figure{logo_who.png}{options: height=60px style=margin-bottom:5px} \cr}
-This package contains \strong{all ~450 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}).
+This package contains \strong{all ~450 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}). \strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See \url{https://www.whocc.no/copyright_disclaimer/}.}
 
 These have become the gold standard for international drug utilisation monitoring and research.
 

man/antibiotics.Rd

@@ -41,7 +41,7 @@ Synonyms (i.e. trade names) are derived from the Compound ID (\code{cid}) and co
 \section{WHOCC}{
 
 \if{html}{\figure{logo_who.png}{options: height=60px style=margin-bottom:5px} \cr}
-This package contains \strong{all ~450 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}).
+This package contains \strong{all ~450 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}). \strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See \url{https://www.whocc.no/copyright_disclaimer/}.}
 
 These have become the gold standard for international drug utilisation monitoring and research.
 

man/as.ab.Rd

@@ -35,7 +35,7 @@ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{htt
 \section{WHOCC}{
 
 \if{html}{\figure{logo_who.png}{options: height=60px style=margin-bottom:5px} \cr}
-This package contains \strong{all ~450 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}).
+This package contains \strong{all ~450 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}). \strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See \url{https://www.whocc.no/copyright_disclaimer/}.}
 
 These have become the gold standard for international drug utilisation monitoring and research.
 

man/mdro.Rd

@@ -18,7 +18,7 @@ Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Res
 mdro(x, guideline = NULL, col_mo = NULL, info = TRUE,
   verbose = FALSE, ...)
 
-brmo(..., guideline = "BRMO")
+brmo(x, guideline = "BRMO", ...)
 
 mrgn(x, guideline = "MRGN", ...)
 

pkgdown/extra.css

@@ -187,8 +187,10 @@ table a:not(.btn):hover, .table a:not(.btn):hover {
 
 /* text below header in manual overview */
 .template-reference-index h2 ~ p {
-  font-size: 110%;
+  font-size: 16px;
-  /* font-weight: bold; */
+}
+.template-reference-topic h2 {
+  font-size: 24px;
 }
 
 /* logos on index page */

pkgdown/extra.js

@@ -46,6 +46,9 @@ $( document ).ready(function() {
     window.location.replace(url_new);
   }
 
+  // Replace 'Value' in manual to 'Returned value'
+  $(".template-reference-topic h2#value").text("Returned value");
+
   // PR for 'R for Data Science' on How To pages
   if ($(".template-article").length > 0) {
     $('#sidebar').prepend(