From b15d59cf03601d4e0ba70a89768ec0bb125de3cd Mon Sep 17 00:00:00 2001 From: "Matthijs S. Berends" Date: Tue, 9 Jul 2019 11:22:46 +0200 Subject: [PATCH] (v0.7.1.9009) note for WHOCC --- DESCRIPTION | 4 +- NEWS.md | 2 +- R/mdro.R | 4 +- R/mo.R | 2 +- R/mo_property.R | 2 +- R/whocc.R | 2 +- data-raw/reproduction_of_microorganisms_new.R | 657 ++++++++++++++++++ docs/LICENSE-text.html | 2 +- docs/articles/index.html | 2 +- docs/authors.html | 2 +- docs/extra.css | 6 +- docs/extra.js | 3 + docs/index.html | 3 +- docs/news/index.html | 8 +- docs/reference/WHOCC.html | 4 +- docs/reference/antibiotics.html | 4 +- docs/reference/as.ab.html | 4 +- docs/reference/as.mo.html | 2 +- docs/reference/catalogue_of_life.html | 2 +- docs/reference/catalogue_of_life_version.html | 2 +- docs/reference/freq.html | 2 +- docs/reference/index.html | 2 +- docs/reference/mdro.html | 4 +- docs/reference/microorganisms.codes.html | 2 +- docs/reference/microorganisms.html | 2 +- docs/reference/microorganisms.old.html | 2 +- docs/reference/mo_property.html | 2 +- index.md | 2 + man/WHOCC.Rd | 2 +- man/antibiotics.Rd | 2 +- man/as.ab.Rd | 2 +- man/mdro.Rd | 2 +- pkgdown/extra.css | 6 +- pkgdown/extra.js | 3 + 34 files changed, 711 insertions(+), 41 deletions(-) create mode 100644 data-raw/reproduction_of_microorganisms_new.R diff --git a/DESCRIPTION b/DESCRIPTION index ee3d1f8a..e58e982b 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: AMR -Version: 0.7.1.9008 -Date: 2019-07-04 +Version: 0.7.1.9009 +Date: 2019-07-09 Title: Antimicrobial Resistance Analysis Authors@R: c( person( diff --git a/NEWS.md b/NEWS.md index 0bb14c24..335b1824 100755 --- a/NEWS.md +++ b/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: diff --git a/R/mdro.R b/R/mdro.R index e177fe30..8ce9d928 100755 --- a/R/mdro.R +++ b/R/mdro.R @@ -496,8 +496,8 @@ mdro <- function(x, #' @rdname mdro #' @export -brmo <- function(..., guideline = "BRMO") { - mdro(..., guideline = "BRMO") +brmo <- function(x, guideline = "BRMO", ...) { + mdro(x, guideline = "BRMO", ...) } #' @rdname mdro diff --git a/R/mo.R b/R/mo.R index dab25c05..da13af6f 100755 --- a/R/mo.R +++ b/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) diff --git a/R/mo_property.R b/R/mo_property.R index 8e72cabe..1e2829f9 100755 --- a/R/mo_property.R +++ b/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) diff --git a/R/whocc.R b/R/whocc.R index 6566a6ba..bd103a67 100755 --- a/R/whocc.R +++ b/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. #' diff --git a/data-raw/reproduction_of_microorganisms_new.R b/data-raw/reproduction_of_microorganisms_new.R new file mode 100644 index 00000000..6897dfd7 --- /dev/null +++ b/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 diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index cf0c354f..bb0f3760 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -78,7 +78,7 @@ AMR (for R) - 0.7.1.9008 + 0.7.1.9009 diff --git a/docs/articles/index.html b/docs/articles/index.html index a13d0919..1f465d3e 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -78,7 +78,7 @@ AMR (for R) - 0.7.1.9008 + 0.7.1.9009 diff --git a/docs/authors.html b/docs/authors.html index cf84b4a7..e0bb7f50 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -78,7 +78,7 @@ AMR (for R) - 0.7.1.9008 + 0.7.1.9009 diff --git a/docs/extra.css b/docs/extra.css index 1ab8e530..52765596 100644 --- a/docs/extra.css +++ b/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-weight: bold; */ + font-size: 16px; +} +.template-reference-topic h2 { + font-size: 24px; } /* logos on index page */ diff --git a/docs/extra.js b/docs/extra.js index d2ce07dc..69ef2e00 100644 --- a/docs/extra.js +++ b/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( diff --git a/docs/index.html b/docs/index.html index ebd8cd11..c8d3ae02 100644 --- a/docs/index.html +++ b/docs/index.html @@ -42,7 +42,7 @@ AMR (for R) - 0.7.1.9008 + 0.7.1.9009 @@ -296,6 +296,7 @@

WHO Collaborating Centre for Drug Statistics Methodology

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.

+

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.

diff --git a/docs/news/index.html b/docs/news/index.html index b2a19f2e..84b8ef9b 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -78,7 +78,7 @@ AMR (for R) - 0.7.1.9008 + 0.7.1.9009
@@ -232,9 +232,9 @@ -
+

-AMR 0.7.1.9008 Unreleased +AMR 0.7.1.9009 Unreleased

@@ -1196,7 +1196,7 @@ Using as.mo(..., allow_uncertain = 3)

Contents

    -
  • 0.7.1.9008
    • +
  • 0.7.1.9009
  • 0.7.1
  • 0.7.0
  • 0.6.1
    • diff --git a/docs/reference/WHOCC.html b/docs/reference/WHOCC.html index bcb3bbce..6e064615 100644 --- a/docs/reference/WHOCC.html +++ b/docs/reference/WHOCC.html @@ -80,7 +80,7 @@ AMR (for R) - 0.7.1.9005 + 0.7.1.9009

@@ -246,7 +246,7 @@


-This package contains 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, https://www.whocc.no) and the Pharmaceuticals Community Register of the European Commission (http://ec.europa.eu/health/documents/community-register/html/atc.htm).

+This package contains 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, 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 https://www.whocc.no/copyright_disclaimer/.

These have become the gold standard for international drug utilisation monitoring and research.

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.

diff --git a/docs/reference/antibiotics.html b/docs/reference/antibiotics.html index d396612f..ae1cf0e2 100644 --- a/docs/reference/antibiotics.html +++ b/docs/reference/antibiotics.html @@ -80,7 +80,7 @@ AMR (for R) - 0.7.1.9005 + 0.7.1.9009
@@ -276,7 +276,7 @@


-This package contains 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, https://www.whocc.no) and the Pharmaceuticals Community Register of the European Commission (http://ec.europa.eu/health/documents/community-register/html/atc.htm).

+This package contains 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, 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 https://www.whocc.no/copyright_disclaimer/.

These have become the gold standard for international drug utilisation monitoring and research.

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.

diff --git a/docs/reference/as.ab.html b/docs/reference/as.ab.html index b2fb70b5..33f9e61a 100644 --- a/docs/reference/as.ab.html +++ b/docs/reference/as.ab.html @@ -80,7 +80,7 @@ AMR (for R) - 0.7.1.9005 + 0.7.1.9009
@@ -274,7 +274,7 @@


-This package contains 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, https://www.whocc.no) and the Pharmaceuticals Community Register of the European Commission (http://ec.europa.eu/health/documents/community-register/html/atc.htm).

+This package contains 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, 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 https://www.whocc.no/copyright_disclaimer/.

These have become the gold standard for international drug utilisation monitoring and research.

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.

diff --git a/docs/reference/as.mo.html b/docs/reference/as.mo.html index 8af96b7f..22081145 100644 --- a/docs/reference/as.mo.html +++ b/docs/reference/as.mo.html @@ -80,7 +80,7 @@ AMR (for R) - 0.7.1.9007 + 0.7.1.9009 diff --git a/docs/reference/catalogue_of_life.html b/docs/reference/catalogue_of_life.html index ebbd8feb..76325f50 100644 --- a/docs/reference/catalogue_of_life.html +++ b/docs/reference/catalogue_of_life.html @@ -80,7 +80,7 @@ AMR (for R) - 0.7.1.9005 + 0.7.1.9009 diff --git a/docs/reference/catalogue_of_life_version.html b/docs/reference/catalogue_of_life_version.html index c02e7631..836a7fbf 100644 --- a/docs/reference/catalogue_of_life_version.html +++ b/docs/reference/catalogue_of_life_version.html @@ -80,7 +80,7 @@ AMR (for R) - 0.7.1.9005 + 0.7.1.9009 diff --git a/docs/reference/freq.html b/docs/reference/freq.html index e49000cc..cf70e637 100644 --- a/docs/reference/freq.html +++ b/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 AMR (for R) - 0.7.1.9007 + 0.7.1.9009 diff --git a/docs/reference/index.html b/docs/reference/index.html index b3aca75d..0176811b 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -78,7 +78,7 @@ AMR (for R) - 0.7.1.9008 + 0.7.1.9009 diff --git a/docs/reference/mdro.html b/docs/reference/mdro.html index a9caf473..7714b871 100644 --- a/docs/reference/mdro.html +++ b/docs/reference/mdro.html @@ -80,7 +80,7 @@ AMR (for R) - 0.7.1.9007 + 0.7.1.9009 @@ -244,7 +244,7 @@ 
mdro(x, guideline = NULL, col_mo = NULL, info = TRUE,
   verbose = FALSE, ...)
 
-brmo(..., guideline = "BRMO")
+brmo(x, guideline = "BRMO", ...)
 
 mrgn(x, guideline = "MRGN", ...)
 
diff --git a/docs/reference/microorganisms.codes.html b/docs/reference/microorganisms.codes.html
index 0bc2192b..0b4f0e17 100644
--- a/docs/reference/microorganisms.codes.html
+++ b/docs/reference/microorganisms.codes.html
@@ -80,7 +80,7 @@
       
       
         AMR (for R)
-        0.7.1.9005
+        0.7.1.9009
       
     
 
diff --git a/docs/reference/microorganisms.html b/docs/reference/microorganisms.html
index e86e90b7..fe0359ce 100644
--- a/docs/reference/microorganisms.html
+++ b/docs/reference/microorganisms.html
@@ -80,7 +80,7 @@
       
       
         AMR (for R)
-        0.7.1.9005
+        0.7.1.9009
       
     
 
diff --git a/docs/reference/microorganisms.old.html b/docs/reference/microorganisms.old.html
index 5024ae93..03147f1a 100644
--- a/docs/reference/microorganisms.old.html
+++ b/docs/reference/microorganisms.old.html
@@ -80,7 +80,7 @@
       
       
         AMR (for R)
-        0.7.1.9005
+        0.7.1.9009
       
     
 
diff --git a/docs/reference/mo_property.html b/docs/reference/mo_property.html
index 20178925..3c5a2819 100644
--- a/docs/reference/mo_property.html
+++ b/docs/reference/mo_property.html
@@ -80,7 +80,7 @@
       
       
         AMR (for R)
-        0.7.1.9007
+        0.7.1.9009
       
     
 
diff --git a/index.md b/index.md
index 4df05732..8957bd87 100644
--- a/index.md
+++ b/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
diff --git a/man/WHOCC.Rd b/man/WHOCC.Rd
index 90593dc2..5cc0b747 100644
--- a/man/WHOCC.Rd
+++ b/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.
 
diff --git a/man/antibiotics.Rd b/man/antibiotics.Rd
index 406a9298..83e1357b 100644
--- a/man/antibiotics.Rd
+++ b/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.
 
diff --git a/man/as.ab.Rd b/man/as.ab.Rd
index 9ff2dd9a..fe05a194 100644
--- a/man/as.ab.Rd
+++ b/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.
 
diff --git a/man/mdro.Rd b/man/mdro.Rd
index f1f76a05..a0d1b09e 100644
--- a/man/mdro.Rd
+++ b/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", ...)
 
diff --git a/pkgdown/extra.css b/pkgdown/extra.css
index 1ab8e530..52765596 100644
--- a/pkgdown/extra.css
+++ b/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-weight: bold; */
+  font-size: 16px;
+}
+.template-reference-topic h2 {
+  font-size: 24px;
 }
 
 /* logos on index page */
diff --git a/pkgdown/extra.js b/pkgdown/extra.js
index d2ce07dc..69ef2e00 100644
--- a/pkgdown/extra.js
+++ b/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(