# ==================================================================== # # TITLE # # AMR: An R Package for Working with Antimicrobial Resistance Data # # # # SOURCE # # https://github.com/msberends/AMR # # # # CITE AS # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # (2022). AMR: An R Package for Working with Antimicrobial Resistance # # Data. Journal of Statistical Software, 104(3), 1-31. # # doi:10.18637/jss.v104.i03 # # # # Developed at the University of Groningen, the Netherlands, in # # collaboration with non-profit organisations Certe Medical # # Diagnostics & Advice, and University Medical Center Groningen. # # # # This R package is free software; you can freely use and distribute # # it for both personal and commercial purposes under the terms of the # # GNU General Public License version 2.0 (GNU GPL-2), as published by # # the Free Software Foundation. # # We created this package for both routine data analysis and academic # # research and it was publicly released in the hope that it will be # # useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # # # # Visit our website for the full manual and a complete tutorial about # # how to conduct AMR data analysis: https://msberends.github.io/AMR/ # # ==================================================================== # # THIS SCRIPT REQUIRES AT LEAST 16 GB RAM # (at least 10 GB will be used by the R session for the size of the files) # 1. Go to https://doi.org/10.15468/39omei and find the download link for the # latest GBIF backbone taxonony under "Endpoints" and unpack Taxon.tsv from it (~2.2 GB) # ALSO BE SURE to get the date of release and update R/aa_globals.R later! # 2. Go to https://lpsn.dsmz.de/downloads (register first) and download the latest # CSV file (~12,5 MB) as "taxonomy.csv". Their API unfortunately does # not include the full taxonomy and is currently (2022) pretty worthless. # 3. For data about human pathogens, we use Bartlett et al. (2022), # https://doi.org/10.1099/mic.0.001269. Their latest supplementary material # can be found here: https://github.com/padpadpadpad/bartlett_et_al_2022_human_pathogens. #. Download their latest xlsx file in the `data` folder and save it to our #. `data-raw` folder. # 4. Set this folder_location to the path where these two files are: folder_location <- "~/Downloads/backbone/" file_gbif <- paste0(folder_location, "Taxon.tsv") file_lpsn <- paste0(folder_location, "taxonomy.csv") file_bartlett <- "data-raw/bartlett_et_al_2022_human_pathogens.xlsx" # 4. Run the rest of this script line by line and check everything :) if (!file.exists(file_gbif)) stop("GBIF file not found") if (!file.exists(file_lpsn)) stop("LPSN file not found") if (!file.exists(file_bartlett)) stop("Bartlett et al. Excel file not found") library(dplyr) library(vroom) # to import files library(rvest) # to scape LPSN website library(progress) # to show progress bars library(readxl) # for reading the Bartlett Excel file devtools::load_all(".") # load AMR package # Helper functions -------------------------------------------------------- get_author_year <- function(ref) { # Only keep first author, e.g. transform 'Smith, Jones, 2011' to 'Smith et al., 2011' authors2 <- iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT") authors2 <- gsub(" ?\\(Approved Lists [0-9]+\\) ?", " () ", authors2) authors2 <- gsub(" [)(]+ $", "", authors2) # remove leading and trailing brackets authors2 <- trimws(gsub("^[(](.*)[)]$", "\\1", authors2)) # only take part after brackets if there's a name authors2 <- ifelse(grepl(".*[)] [a-zA-Z]+.*", authors2), gsub(".*[)] (.*)", "\\1", authors2), authors2 ) # replace parentheses with emend. to get the latest authors authors2 <- gsub("(", " emend. ", authors2, fixed = TRUE) authors2 <- gsub(")", "", authors2, fixed = TRUE) authors2 <- gsub(" +", " ", authors2) authors2 <- trimws(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) # not sure what this is authors <- gsub("(Saito)", "", authors, fixed = TRUE) authors <- gsub("(Oudem.)", "", authors, fixed = TRUE) # remove nonsense characters from names authors <- gsub("[^a-zA-Z,'&. -]", "", authors) # no initials, only surname authors <- gsub("[A-Z][.]", "", authors, ignore.case = FALSE) # remove trailing and leading spaces authors <- trimws(authors) # keep only the part after last 'emend.' to get the latest authors authors <- gsub(".*emend[.] ?", "", 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.?|corrig.?) ", "", authors, ignore.case = TRUE) # no initials, only surname authors <- trimws(authors) authors <- gsub("^([A-Z][.])+( & ?)?", "", authors, ignore.case = FALSE) authors <- gsub("^([A-Z]+ )+", "", authors, ignore.case = FALSE) # remove dots authors <- gsub(".", "", authors, fixed = TRUE) authors <- gsub("et al", "et al.", authors, fixed = TRUE) authors[nchar(authors) <= 3] <- "" # 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) ref <- gsub("^(emend|et al.,?)", "", ref) ref <- trimws(ref) ref <- gsub("'", "", ref) # a lot start with a lowercase character - fix that ref[!grepl("^d[A-Z]", ref)] <- gsub("^([a-z])", "\\U\\1", ref[!grepl("^d[A-Z]", ref)], perl = TRUE) # specific one for the French that are named dOrbigny ref[grepl("^d[A-Z]", ref)] <- gsub("^d", "d'", ref[grepl("^d[A-Z]", ref)]) ref <- gsub(" +", " ", ref) ref[ref == ""] <- NA_character_ ref } df_remove_nonASCII <- function(df) { # Remove non-ASCII characters (these are not allowed by CRAN) df %>% mutate_if(is.character, iconv, from = "UTF-8", to = "ASCII//TRANSLIT") %>% # also remove invalid characters mutate_if(is.character, ~ gsub("[\"'`]+", "", .)) %>% AMR:::dataset_UTF8_to_ASCII() } abbreviate_mo <- function(x, minlength = 5, prefix = "", hyphen_as_space = FALSE, ...) { if (hyphen_as_space == TRUE) { x <- gsub("-", " ", x, fixed = TRUE) } # keep a starting Latin ae suppressWarnings( gsub("^ae", "\u00E6\u00E6", x, ignore.case = TRUE) %>% abbreviate( minlength = minlength, use.classes = TRUE, method = "both.sides", ... ) %>% paste0(prefix, .) %>% toupper() %>% gsub("(\u00C6|\u00E6)+", "AE", .) ) } # to retrieve LPSN and authors from LPSN website get_lpsn_and_author <- function(rank, name) { url <- paste0("https://lpsn.dsmz.de/", tolower(rank), "/", tolower(name)) page_txt <- tryCatch(read_html(url), error = function(e) NULL) if (is.null(page_txt)) { warning("No LPSN found for ", tolower(rank), " '", name, "'") lpsn <- NA_character_ ref <- NA_character_ } else { page_txt <- page_txt %>% html_element("#detail-page") %>% html_text() lpsn <- gsub(".*Record number:[\r\n\t ]*([0-9]+).*", "\\1", page_txt, perl = FALSE) ref <- page_txt %>% gsub(".*?Name: (.*[0-9]{4}?).*", "\\1", ., perl = FALSE) %>% gsub(name, "", ., fixed = TRUE) %>% trimws() } c("lpsn" = lpsn, "ref" = ref) } # MB/ August 2022: useless, does not contain full taxonomy, e.g. LPSN::request(cred, category = "family") is empty. # get_from_lpsn <- function (user, pw) { # if (!"LPSN" %in% rownames(utils::installed.packages())) { # stop("Install the official LPSN package for R using: install.packages('LPSN', repos = 'https://r-forge.r-project.org')") # } # cred <- LPSN::open_lpsn(user, pw) # # lpsn_genus <- LPSN::request(cred, category = "genus") # message("Downloading genus data (n = ", lpsn_genus$count, ") from LPSN API...") # lpsn_genus <- as.data.frame(LPSN::retrieve(cred, category = "genus")) # # lpsn_species <- LPSN::request(cred, category = "species") # message("Downloading species data (n = ", lpsn_species$count, ") from LPSN API...") # lpsn_species <- as.data.frame(LPSN::retrieve(cred, category = "species")) # # lpsn_subspecies <- LPSN::request(cred, category = "subspecies") # message("Downloading subspecies data (n = ", lpsn_subspecies$count, ") from LPSN API...") # lpsn_subspecies <- as.data.frame(LPSN::retrieve(cred, category = "subspecies")) # # message("Binding rows...") # lpsn_total <- bind_rows(lpsn_genus, lpsn_species, lpsn_subspecies) # message("Done.") # lpsn_total # } # Read GBIF data ---------------------------------------------------------- taxonomy_gbif.bak <- vroom(file_gbif) include_fungal_orders <- c( "Eurotiales", "Microascales", "Mucorales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales", "Onygenales", "Pneumocystales" ) # get latest taxonomic names of these fungal orders include_fungal_orders_ids <- taxonomy_gbif.bak %>% filter(order %in% include_fungal_orders) include_fungal_orders <- taxonomy_gbif.bak %>% filter(taxonID %in% c(include_fungal_orders_ids$taxonID, include_fungal_orders_ids$acceptedNameUsageID)) %>% distinct(order) %>% pull(order) # check some columns to validate below filters sort(table(taxonomy_gbif.bak$taxonomicStatus)) sort(table(taxonomy_gbif.bak$taxonRank)) taxonomy_gbif <- taxonomy_gbif.bak %>% # immediately filter rows we really never want filter( # never doubtful status, only accepted and all synonyms, and only ranked items taxonomicStatus != "doubtful", taxonRank != "unranked", # include these kingdoms (no Chromista) kingdom %in% c("Archaea", "Bacteria", "Protozoa") | # include all of these fungal orders order %in% c( "Eurotiales", "Microascales", "Mucorales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales", "Onygenales", "Pneumocystales" ) | # and all of these important genera (see "data-raw/_pre_commit_hook.R") # (they also contain bacteria and protozoa, but these will get prevalence = 2 later on) genus %in% AMR:::MO_PREVALENT_GENERA ) %>% select( kingdom, phylum, class, order, family, genus, species = specificEpithet, subspecies = infraspecificEpithet, rank = taxonRank, status = taxonomicStatus, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID, gbif_renamed_to = acceptedNameUsageID ) %>% mutate( # do this mutate after the original selection/filtering, as it decreases computing time tremendously status = ifelse(status == "accepted", "accepted", "synonym"), # checked taxonRank - the "form" and "variety" always have a subspecies, so: rank = ifelse(rank %in% c("form", "variety"), "subspecies", rank), source = "GBIF" ) %>% filter( # their data is messy - keep only these: rank == "kingdom" & !is.na(kingdom) | rank == "phylum" & !is.na(phylum) | rank == "class" & !is.na(class) | rank == "order" & !is.na(order) | rank == "family" & !is.na(family) | rank == "genus" & !is.na(genus) | rank == "species" & !is.na(species) | rank == "subspecies" & !is.na(subspecies) ) %>% # some items end with _A or _B... why?? mutate_all(~ gsub("_[A-Z]$", "", .x, perl = TRUE)) %>% # now we have duplicates, remove these, but prioritise "accepted" status and highest taxon ID arrange(status, gbif) %>% distinct(kingdom, phylum, class, order, family, genus, species, subspecies, .keep_all = TRUE) %>% filter( kingdom %unlike% "[0-9]", phylum %unlike% "[0-9]", class %unlike% "[0-9]", order %unlike% "[0-9]", family %unlike% "[0-9]", genus %unlike% "[0-9]" ) # integrity tests sort(table(taxonomy_gbif$rank)) sort(table(taxonomy_gbif$status)) taxonomy_gbif # Read LPSN data ---------------------------------------------------------- taxonomy_lpsn.bak <- vroom(file_lpsn) # check some columns to validate below filters sort(table(is.na(taxonomy_lpsn.bak$record_lnk))) # accepted = TRUE taxonomy_lpsn <- taxonomy_lpsn.bak %>% transmute( genus = genus_name, species = sp_epithet, subspecies = subsp_epithet, rank = case_when( !is.na(subsp_epithet) ~ "subspecies", !is.na(sp_epithet) ~ "species", TRUE ~ "genus" ), status = ifelse(is.na(record_lnk), "accepted", "synonym"), ref = authors, lpsn = as.character(record_no), lpsn_parent = NA_character_, lpsn_renamed_to = as.character(record_lnk) ) %>% mutate(source = "LPSN") taxonomy_lpsn # download additional taxonomy to the domain/kingdom level (their API is not sufficient...) taxonomy_lpsn_missing <- tibble( kingdom = character(0), phylum = character(0), class = character(0), order = character(0), family = character(0), genus = character(0) ) for (page in LETTERS) { # this will not alter `taxonomy_lpsn` yet message("Downloading page ", page, "...", appendLF = FALSE) url <- paste0("https://lpsn.dsmz.de/genus?page=", page) x <- read_html(url) %>% # class "main-list" is the main table html_element(".main-list") %>% # get every list element with a set attribute html_elements("li[id]") for (i in seq_len(length(x))) { if (i %% 25 == 0) { message(".", appendLF = FALSE) } elements <- x[[i]] %>% html_elements("a") hrefs <- elements %>% html_attr("href") ranks <- hrefs %>% gsub(".*/(.*?)/.*", "\\1", .) names <- elements %>% html_text() %>% gsub('"', "", ., fixed = TRUE) # no species, this must be until genus level hrefs <- hrefs[ranks != "species"] names <- names[ranks != "species"] ranks <- ranks[ranks != "species"] ranks[ranks == "domain"] <- "kingdom" df <- names %>% tibble() %>% t() %>% as_tibble(.name_repair = "unique") %>% setNames(ranks) %>% # no candidates please filter(genus %unlike% "^(Candidatus|\\[)") taxonomy_lpsn_missing <- taxonomy_lpsn_missing %>% bind_rows(df) } message(length(x), " entries incl. candidates (cleaned total: ", nrow(taxonomy_lpsn_missing), ")") } taxonomy_lpsn_missing taxonomy_lpsn <- taxonomy_lpsn %>% left_join(taxonomy_lpsn_missing, by = "genus") %>% select(kingdom:family, everything()) %>% # remove entries like "[Bacteria, no family]" and "[Bacteria, no class]" mutate_all(function(x) ifelse(x %like_case% " no ", NA_character_, x)) taxonomy_lpsn.bak2 <- taxonomy_lpsn # download family directly from LPSN website using scraping pb <- progress_bar$new(total = length(unique(taxonomy_lpsn$family))) for (f in unique(taxonomy_lpsn$family)) { pb$tick() if (is.na(f)) next tax_info <- get_lpsn_and_author("Family", f) taxonomy_lpsn <- taxonomy_lpsn %>% bind_rows(tibble( kingdom = taxonomy_lpsn$kingdom[which(taxonomy_lpsn$family == f)[1]], phylum = taxonomy_lpsn$phylum[which(taxonomy_lpsn$family == f)[1]], class = taxonomy_lpsn$class[which(taxonomy_lpsn$family == f)[1]], order = taxonomy_lpsn$order[which(taxonomy_lpsn$family == f)[1]], family = f, rank = "family", status = "accepted", source = "LPSN", lpsn = unname(tax_info["lpsn"]), ref = unname(tax_info["ref"]) )) } # download order directly from LPSN website using scraping pb <- progress_bar$new(total = length(unique(taxonomy_lpsn$order))) for (o in unique(taxonomy_lpsn$order)) { pb$tick() if (is.na(o)) next tax_info <- get_lpsn_and_author("Order", o) taxonomy_lpsn <- taxonomy_lpsn %>% bind_rows(tibble( kingdom = taxonomy_lpsn$kingdom[which(taxonomy_lpsn$order == o)[1]], phylum = taxonomy_lpsn$phylum[which(taxonomy_lpsn$order == o)[1]], class = taxonomy_lpsn$class[which(taxonomy_lpsn$order == o)[1]], order = o, rank = "order", status = "accepted", source = "LPSN", lpsn = unname(tax_info["lpsn"]), ref = unname(tax_info["ref"]) )) } # download class directly from LPSN website using scraping pb <- progress_bar$new(total = length(unique(taxonomy_lpsn$class))) for (cc in unique(taxonomy_lpsn$class)) { pb$tick() if (is.na(cc)) next tax_info <- get_lpsn_and_author("Class", cc) taxonomy_lpsn <- taxonomy_lpsn %>% bind_rows(tibble( kingdom = taxonomy_lpsn$kingdom[which(taxonomy_lpsn$class == cc)[1]], phylum = taxonomy_lpsn$phylum[which(taxonomy_lpsn$class == cc)[1]], class = cc, rank = "class", status = "accepted", source = "LPSN", lpsn = unname(tax_info["lpsn"]), ref = unname(tax_info["ref"]) )) } # download phylum directly from LPSN website using scraping pb <- progress_bar$new(total = length(unique(taxonomy_lpsn$phylum))) for (p in unique(taxonomy_lpsn$phylum)) { pb$tick() if (is.na(p)) next tax_info <- get_lpsn_and_author("Phylum", p) taxonomy_lpsn <- taxonomy_lpsn %>% bind_rows(tibble( kingdom = taxonomy_lpsn$kingdom[which(taxonomy_lpsn$phylum == p)[1]], phylum = p, rank = "phylum", status = "accepted", source = "LPSN", lpsn = unname(tax_info["lpsn"]), ref = unname(tax_info["ref"]) )) } # download kingdom directly from LPSN website using scraping pb <- progress_bar$new(total = length(unique(taxonomy_lpsn$kingdom))) for (k in unique(taxonomy_lpsn$kingdom)) { pb$tick() if (is.na(k)) next tax_info <- get_lpsn_and_author("Domain", k) taxonomy_lpsn <- taxonomy_lpsn %>% bind_rows(tibble( kingdom = k, rank = "kingdom", status = "accepted", source = "LPSN", lpsn = unname(tax_info["lpsn"]), ref = unname(tax_info["ref"]) )) } # integrity tests sort(table(taxonomy_lpsn$rank)) sort(table(taxonomy_lpsn$status)) # Save intermediate results ----------------------------------------------- saveRDS(taxonomy_gbif, "data-raw/taxonomy_gbif.rds", version = 2) saveRDS(taxonomy_lpsn, "data-raw/taxonomy_lpsn.rds", version = 2) # this allows to always get back to this point by simply loading the files from data-raw/. # Add full names ---------------------------------------------------------- taxonomy_gbif <- taxonomy_gbif %>% # clean NAs and add fullname mutate(across(kingdom:subspecies, function(x) ifelse(is.na(x), "", x)), fullname = trimws(case_when( rank == "family" ~ family, rank == "order" ~ order, rank == "class" ~ class, rank == "phylum" ~ phylum, rank == "kingdom" ~ kingdom, TRUE ~ paste(genus, species, subspecies) )), .before = 1 ) %>% # keep only one GBIF taxon ID per full name arrange(fullname, gbif) %>% distinct(kingdom, rank, fullname, .keep_all = TRUE) taxonomy_lpsn <- taxonomy_lpsn %>% # clean NAs and add fullname mutate(across(kingdom:subspecies, function(x) ifelse(is.na(x), "", x)), fullname = trimws(case_when( rank == "family" ~ family, rank == "order" ~ order, rank == "class" ~ class, rank == "phylum" ~ phylum, rank == "kingdom" ~ kingdom, TRUE ~ paste(genus, species, subspecies) )), .before = 1 ) %>% # keep only one LPSN record ID per full name arrange(fullname, lpsn) %>% distinct(kingdom, rank, fullname, .keep_all = TRUE) # set parent LPSN IDs, requires full name taxonomy_lpsn$lpsn_parent[taxonomy_lpsn$rank == "phylum"] <- taxonomy_lpsn$lpsn[match(taxonomy_lpsn$kingdom[taxonomy_lpsn$rank == "phylum"], taxonomy_lpsn$fullname)] taxonomy_lpsn$lpsn_parent[taxonomy_lpsn$rank == "class"] <- taxonomy_lpsn$lpsn[match(taxonomy_lpsn$phylum[taxonomy_lpsn$rank == "class"], taxonomy_lpsn$fullname)] taxonomy_lpsn$lpsn_parent[taxonomy_lpsn$rank == "order"] <- taxonomy_lpsn$lpsn[match(taxonomy_lpsn$class[taxonomy_lpsn$rank == "order"], taxonomy_lpsn$fullname)] taxonomy_lpsn$lpsn_parent[taxonomy_lpsn$rank == "family"] <- taxonomy_lpsn$lpsn[match(taxonomy_lpsn$order[taxonomy_lpsn$rank == "family"], taxonomy_lpsn$fullname)] taxonomy_lpsn$lpsn_parent[taxonomy_lpsn$rank == "genus"] <- taxonomy_lpsn$lpsn[match(taxonomy_lpsn$family[taxonomy_lpsn$rank == "genus"], taxonomy_lpsn$fullname)] taxonomy_lpsn$lpsn_parent[taxonomy_lpsn$rank == "species"] <- taxonomy_lpsn$lpsn[match(taxonomy_lpsn$genus[taxonomy_lpsn$rank == "species"], taxonomy_lpsn$fullname)] taxonomy_lpsn$lpsn_parent[taxonomy_lpsn$rank == "subspecies"] <- taxonomy_lpsn$lpsn[match(paste(taxonomy_lpsn$genus[taxonomy_lpsn$rank == "subspecies"], taxonomy_lpsn$species[taxonomy_lpsn$rank == "subspecies"]), taxonomy_lpsn$fullname)] # Combine the datasets ---------------------------------------------------- # basis must be LPSN as it's most recent taxonomy <- taxonomy_lpsn %>% # join GBIF identifiers to them left_join(taxonomy_gbif %>% select(kingdom, fullname, starts_with("gbif")), by = c("kingdom", "fullname") ) # for everything else, add the GBIF data taxonomy <- taxonomy %>% bind_rows(taxonomy_gbif %>% filter(!paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname))) %>% arrange(fullname) %>% filter(fullname != "") # get missing entries from existing microorganisms data set taxonomy <- taxonomy %>% bind_rows(AMR::microorganisms %>% select(all_of(colnames(taxonomy))) %>% filter(!paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname), # these will be added later: source != "manually added")) %>% arrange(fullname) %>% filter(fullname != "") # fix rank table(taxonomy$rank, useNA = "always") taxonomy <- taxonomy %>% mutate(rank = case_when( subspecies != "" ~ "subspecies", species != "" ~ "species", genus != "" ~ "genus", family != "" ~ "family", order != "" ~ "order", class != "" ~ "class", phylum != "" ~ "phylum", kingdom != "" ~ "kingdom", TRUE ~ NA_character_ )) table(taxonomy$rank, useNA = "always") # Save intermediate results (0) ------------------------------------------- saveRDS(taxonomy, "data-raw/taxonomy0.rds") # Add missing and fix old taxonomic entries ------------------------------- # this part will make sure that the whole taxonomy of every included species exists, so no missing genera, classes, etc. current_gbif <- taxonomy_gbif.bak %>% filter(is.na(acceptedNameUsageID)) %>% mutate( taxonID = as.character(taxonID), parentNameUsageID = as.character(parentNameUsageID) ) # add missing kingdoms taxonomy <- taxonomy %>% bind_rows( taxonomy %>% filter(kingdom != "") %>% distinct(kingdom) %>% mutate( fullname = kingdom, rank = "kingdom", status = "accepted", source = "manually added" ) %>% filter(!paste(kingdom, rank) %in% paste(taxonomy$kingdom, taxonomy$rank)) %>% left_join(current_gbif %>% select(kingdom, rank = taxonRank, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID), by = c("kingdom", "rank") ) %>% mutate(source = ifelse(!is.na(gbif), "GBIF", source)) ) # 2 = phylum ... 6 = genus taxonomy_all_missing <- NULL for (i in 2:6) { i_name <- colnames(taxonomy)[i + 1] message("Adding missing: ", i_name, "... ", appendLF = FALSE) to_add <- taxonomy %>% filter(.[[i + 1]] != "") %>% distinct(kingdom, .[[i + 1]], .keep_all = TRUE) %>% select(kingdom:(i + 1)) %>% mutate( fullname = .[[ncol(.)]], rank = i_name, status = "accepted", source = "manually added" ) %>% filter(!paste(kingdom, .[[ncol(.) - 4]], rank) %in% paste(taxonomy$kingdom, taxonomy[[i + 1]], taxonomy$rank)) %>% # get GBIF identifier where available left_join(current_gbif %>% select(kingdom, all_of(i_name), rank = taxonRank, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID), by = c("kingdom", "rank", i_name) ) %>% mutate(source = ifelse(!is.na(gbif), "GBIF", source)) message("n = ", nrow(to_add)) if (is.null(taxonomy_all_missing)) { taxonomy_all_missing <- to_add } else { taxonomy_all_missing <- taxonomy_all_missing %>% bind_rows(to_add) } } taxonomy_all_missing %>% View() taxonomy <- taxonomy %>% bind_rows(taxonomy_all_missing) # fix for duplicate fullnames within a kingdom (such as Nitrospira which is the name of the genus AND its class) taxonomy <- taxonomy %>% mutate(rank_index = case_when(rank == "subspecies" ~ 1, rank == "species" ~ 2, rank == "genus" ~ 3, rank == "family" ~ 4, rank == "order" ~ 5, rank == "class" ~ 6, TRUE ~ 7), fullname_rank = paste0(fullname, " {", rank, "}")) %>% arrange(kingdom, fullname, rank_index) %>% group_by(kingdom, fullname) %>% mutate(fullname = if_else(row_number() > 1, fullname_rank, fullname)) %>% ungroup() %>% select(-fullname_rank, -rank_index) %>% arrange(fullname) # now also add missing species (requires combination with genus) taxonomy <- taxonomy %>% bind_rows( taxonomy %>% filter(species != "") %>% distinct(kingdom, genus, species, .keep_all = TRUE) %>% select(kingdom:species) %>% mutate( fullname = paste(genus, species), rank = "species", status = "accepted", source = "manually added" ) %>% filter(!paste(kingdom, genus, species, rank) %in% paste(taxonomy$kingdom, taxonomy$genus, taxonomy$species, taxonomy$rank)) %>% # get GBIF identifier where available left_join(current_gbif %>% select(kingdom, genus, species = specificEpithet, rank = taxonRank, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID), by = c("kingdom", "rank", "genus", "species") ) %>% mutate(source = ifelse(!is.na(gbif), "GBIF", source)) ) # remove NAs from taxonomy again, and keep unique full names taxonomy <- taxonomy %>% mutate(across(kingdom:subspecies, function(x) ifelse(is.na(x), "", x))) %>% distinct(kingdom, fullname, .keep_all = TRUE) %>% filter(kingdom != "") # Save intermediate results (1) ------------------------------------------- saveRDS(taxonomy, "data-raw/taxonomy1.rds") # Get previously manually added entries ----------------------------------- manually_added <- AMR::microorganisms %>% filter(source == "manually added", !paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname)) %>% select(fullname:subspecies, ref, source, rank) manually_added <- manually_added %>% bind_rows(salmonellae) # get latest taxonomy for those entries for (g in unique(manually_added$genus[manually_added$genus != "" & manually_added$genus %in% taxonomy$genus])) { manually_added$family[which(manually_added$genus == g)] <- taxonomy$family[which(taxonomy$genus == g & is.na(taxonomy$lpsn))][1] } for (f in unique(manually_added$family[manually_added$family != "" & manually_added$family %in% taxonomy$family])) { manually_added$order[which(manually_added$family == f)] <- taxonomy$order[which(taxonomy$family == f & is.na(taxonomy$lpsn))][1] } for (o in unique(manually_added$order[manually_added$order != "" & manually_added$order %in% taxonomy$order])) { manually_added$class[which(manually_added$order == o)] <- taxonomy$class[which(taxonomy$order == o & is.na(taxonomy$lpsn))][1] } for (cc in unique(manually_added$class[manually_added$class != "" & manually_added$class %in% taxonomy$class])) { manually_added$phylum[which(manually_added$class == cc)] <- taxonomy$phylum[which(taxonomy$class == cc & is.na(taxonomy$lpsn))][1] } for (p in unique(manually_added$phylum[manually_added$phylum != "" & manually_added$phylum %in% taxonomy$phylum])) { manually_added$kingdom[which(manually_added$phylum == p)] <- taxonomy$kingdom[which(taxonomy$phylum == p & is.na(taxonomy$lpsn))][1] } manually_added <- manually_added %>% mutate( status = "accepted", rank = ifelse(fullname %like% "unknown", "(unknown rank)", rank) ) manually_added taxonomy <- taxonomy %>% # here also the 'unknowns' are added, such as "(unknown fungus)" bind_rows(manually_added) %>% arrange(fullname) table(taxonomy$rank, useNA = "always") # Clean scientific reference ---------------------------------------------- taxonomy <- taxonomy %>% mutate(ref = get_author_year(ref)) # Get the latest upper taxonomy from LPSN for non-LPSN data --------------- # (e.g., phylum above class "Bacilli" was still "Firmicutes", should be "Bacillota" in 2022) for (k in unique(taxonomy$kingdom[taxonomy$kingdom != ""])) { message("Fixing GBIF taxonomy for kingdom ", k, ".", appendLF = FALSE) i <- 0 for (g in unique(taxonomy$genus[taxonomy$genus != "" & taxonomy$kingdom == k & taxonomy$source == "LPSN"])) { i <- i + 1 if (i %% 50 == 0) message(".", appendLF = FALSE) taxonomy$family[which(taxonomy$genus == g & taxonomy$kingdom == k)] <- taxonomy$family[which(taxonomy$genus == g & taxonomy$kingdom == k & taxonomy$source == "LPSN")][1] } for (f in unique(taxonomy$family[taxonomy$family != "" & taxonomy$kingdom == k & taxonomy$source == "LPSN"])) { i <- i + 1 if (i %% 50 == 0) message(".", appendLF = FALSE) taxonomy$order[which(taxonomy$family == f & taxonomy$kingdom == k)] <- taxonomy$order[which(taxonomy$family == f & taxonomy$kingdom == k & taxonomy$source == "LPSN")][1] } for (o in unique(taxonomy$order[taxonomy$order != "" & taxonomy$kingdom == k & taxonomy$source == "LPSN"])) { i <- i + 1 if (i %% 50 == 0) message(".", appendLF = FALSE) taxonomy$class[which(taxonomy$order == o & taxonomy$kingdom == k)] <- taxonomy$class[which(taxonomy$order == o & taxonomy$kingdom == k & taxonomy$source == "LPSN")][1] } for (cc in unique(taxonomy$class[taxonomy$class != "" & taxonomy$kingdom == k & taxonomy$source == "LPSN"])) { i <- i + 1 if (i %% 50 == 0) message(".", appendLF = FALSE) taxonomy$phylum[which(taxonomy$class == cc & taxonomy$kingdom == k)] <- taxonomy$phylum[which(taxonomy$class == cc & taxonomy$kingdom == k & taxonomy$source == "LPSN")][1] } message("OK.") } # we need to fix parent GBIF identifiers taxonomy$gbif_parent[taxonomy$rank == "phylum" & !is.na(taxonomy$gbif)] <- taxonomy$gbif[match(taxonomy$kingdom[taxonomy$rank == "phylum" & !is.na(taxonomy$gbif)], taxonomy$fullname)] taxonomy$gbif_parent[taxonomy$rank == "class" & !is.na(taxonomy$gbif)] <- taxonomy$gbif[match(taxonomy$phylum[taxonomy$rank == "class" & !is.na(taxonomy$gbif)], taxonomy$fullname)] taxonomy$gbif_parent[taxonomy$rank == "order" & !is.na(taxonomy$gbif)] <- taxonomy$gbif[match(taxonomy$class[taxonomy$rank == "order" & !is.na(taxonomy$gbif)], taxonomy$fullname)] taxonomy$gbif_parent[taxonomy$rank == "family" & !is.na(taxonomy$gbif)] <- taxonomy$gbif[match(taxonomy$order[taxonomy$rank == "family" & !is.na(taxonomy$gbif)], taxonomy$fullname)] taxonomy$gbif_parent[taxonomy$rank == "genus" & !is.na(taxonomy$gbif)] <- taxonomy$gbif[match(taxonomy$family[taxonomy$rank == "genus" & !is.na(taxonomy$gbif)], taxonomy$fullname)] taxonomy$gbif_parent[taxonomy$rank == "species" & !is.na(taxonomy$gbif)] <- taxonomy$gbif[match(taxonomy$genus[taxonomy$rank == "species" & !is.na(taxonomy$gbif)], taxonomy$fullname)] taxonomy$gbif_parent[taxonomy$rank == "subspecies" & !is.na(taxonomy$gbif)] <- taxonomy$gbif[match(paste(taxonomy$genus[taxonomy$rank == "subspecies" & !is.na(taxonomy$gbif)], taxonomy$species[taxonomy$rank == "subspecies" & !is.na(taxonomy$gbif)]), taxonomy$fullname)] # these still have no record in our data set: all(taxonomy$lpsn_parent %in% taxonomy$lpsn) all(taxonomy$gbif_parent %in% taxonomy$gbif) # fix rank taxonomy <- taxonomy %>% mutate(rank = case_when( subspecies != "" ~ "subspecies", species != "" ~ "species", genus != "" ~ "genus", family != "" ~ "family", order != "" ~ "order", class != "" ~ "class", phylum != "" ~ "phylum", kingdom != "" ~ "kingdom", TRUE ~ NA_character_ )) # Add prevalence ---------------------------------------------------------- pathogens <- read_excel(file_bartlett, sheet = "Tab 6 Full List") # get all established, both old and current taxonomic names established <- pathogens %>% filter(status == "established") %>% mutate(fullname = paste(genus, species)) %>% pull(fullname) %>% c(unlist(mo_current(.)), unlist(mo_synonyms(., keep_synonyms = FALSE))) %>% strsplit(" ", fixed = TRUE) %>% sapply(function(x) ifelse(length(x) == 1, x, paste(x[1], x[2]))) %>% sort() %>% unique() # get all putative, both old and current taxonomic names putative <- pathogens %>% filter(status == "putative") %>% mutate(fullname = paste(genus, species)) %>% pull(fullname) %>% c(unlist(mo_current(.)), unlist(mo_synonyms(., keep_synonyms = FALSE))) %>% strsplit(" ", fixed = TRUE) %>% sapply(function(x) ifelse(length(x) == 1, x, paste(x[1], x[2]))) %>% sort() %>% unique() established <- established[established %unlike% "unknown"] putative <- putative[putative %unlike% "unknown"] other_bacterial_genera <- c(established, putative) %>% strsplit(" ", fixed = TRUE) %>% sapply(function(x) x[1]) %>% sort() %>% unique() other_genera <- AMR:::MO_PREVALENT_GENERA %>% c(unlist(mo_current(.)), unlist(mo_synonyms(., keep_synonyms = FALSE))) %>% strsplit(" ", fixed = TRUE) %>% sapply(function(x) x[1]) %>% sort() %>% unique() other_genera <- other_genera[other_genera %unlike% "unknown"] # update prevalence based on taxonomy (following the recent and thorough work of Bartlett et al., 2022) # see https://doi.org/10.1099/mic.0.001269 taxonomy <- taxonomy %>% mutate(prevalence = case_when( # 'established' gets a 1 and means 'have infected at least three persons in three or more references' paste(genus, species) %in% established & rank %in% c("genus", "species", "subspecies") ~ 1.0, # 'putative' gets a 2 and means 'fewer than three known cases' paste(genus, species) %in% putative & rank %in% c("genus", "species", "subspecies") ~ 2.0, # other species from a genus in either group get a 2.5 genus %in% other_bacterial_genera & rank %in% c("genus", "species", "subspecies") ~ 2.5, # we keep track of prevalent genera too of non-bacterial species genus %in% AMR:::MO_PREVALENT_GENERA & kingdom != "Bacteria" & rank %in% c("genus", "species", "subspecies") ~ 2.5, # all others get a 3 TRUE ~ 3.0)) table(taxonomy$prevalence, useNA = "always") # (a lot will be removed further below) # Save intermediate results (2) ------------------------------------------- saveRDS(taxonomy, "data-raw/taxonomy2.rds") # Add microbial IDs ------------------------------------------------------- # MO codes in the AMR package have the form KINGDOM_GENUS_SPECIES_SUBSPECIES where all are abbreviated. # Kingdom is abbreviated with 1 character, with exceptions for Animalia and Plantae mo_kingdom <- taxonomy %>% filter(rank == "kingdom") %>% select(kingdom) %>% mutate(mo_kingdom = case_when( kingdom == "Animalia" ~ "AN", kingdom == "Archaea" ~ "A", kingdom == "Bacteria" ~ "B", kingdom == "Chromista" ~ "C", kingdom == "Fungi" ~ "F", kingdom == "Plantae" ~ "PL", kingdom == "Protozoa" ~ "P", TRUE ~ "" )) # phylum until family are abbreviated with 8 characters and prefixed with their rank # Phylum - keep old and fill up for new ones mo_phylum <- taxonomy %>% filter(rank == "phylum") %>% distinct(kingdom, phylum) %>% left_join(AMR::microorganisms %>% filter(rank == "phylum") %>% transmute(kingdom, phylum = fullname, mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo)) ), by = c("kingdom", "phylum") ) %>% group_by(kingdom) %>% mutate( mo_phylum8 = abbreviate_mo(phylum, minlength = 8, prefix = "[PHL]_"), mo_phylum9 = abbreviate_mo(phylum, minlength = 9, prefix = "[PHL]_"), mo_phylum = ifelse(!is.na(mo_old), mo_old, mo_phylum8), mo_duplicated = duplicated(mo_phylum), mo_phylum = ifelse(mo_duplicated, mo_phylum9, mo_phylum), mo_duplicated = duplicated(mo_phylum) ) %>% ungroup() if (any(mo_phylum$mo_duplicated, na.rm = TRUE)) stop("Duplicate MO codes for phylum!") mo_phylum <- mo_phylum %>% select(kingdom, phylum, mo_phylum) # Class - keep old and fill up for new ones mo_class <- taxonomy %>% filter(rank == "class") %>% distinct(kingdom, class) %>% left_join(AMR::microorganisms %>% filter(rank == "class") %>% transmute(kingdom, class = fullname, mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo)) ), by = c("kingdom", "class") ) %>% group_by(kingdom) %>% mutate( mo_class8 = abbreviate_mo(class, minlength = 8, prefix = "[CLS]_"), mo_class9 = abbreviate_mo(class, minlength = 9, prefix = "[CLS]_"), mo_class = ifelse(!is.na(mo_old), mo_old, mo_class8), mo_duplicated = duplicated(mo_class), mo_class = ifelse(mo_duplicated, mo_class9, mo_class), mo_duplicated = duplicated(mo_class) ) %>% ungroup() if (any(mo_class$mo_duplicated, na.rm = TRUE)) stop("Duplicate MO codes for class!") mo_class <- mo_class %>% select(kingdom, class, mo_class) # Order - keep old and fill up for new ones mo_order <- taxonomy %>% filter(rank == "order") %>% distinct(kingdom, order) %>% left_join(AMR::microorganisms %>% filter(rank == "order") %>% transmute(kingdom, order = fullname, mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo)) ), by = c("kingdom", "order") ) %>% group_by(kingdom) %>% mutate( mo_order8 = abbreviate_mo(order, minlength = 8, prefix = "[ORD]_"), mo_order9 = abbreviate_mo(order, minlength = 9, prefix = "[ORD]_"), mo_order = ifelse(!is.na(mo_old), mo_old, mo_order8), mo_duplicated = duplicated(mo_order), mo_order = ifelse(mo_duplicated, mo_order9, mo_order), mo_duplicated = duplicated(mo_order) ) %>% ungroup() if (any(mo_order$mo_duplicated, na.rm = TRUE)) stop("Duplicate MO codes for order!") mo_order <- mo_order %>% select(kingdom, order, mo_order) # Family - keep old and fill up for new ones mo_family <- taxonomy %>% filter(rank == "family") %>% distinct(kingdom, family) %>% left_join(AMR::microorganisms %>% filter(rank == "family") %>% transmute(kingdom, family = fullname, mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo)) ), by = c("kingdom", "family") ) %>% group_by(kingdom) %>% mutate( mo_family8 = abbreviate_mo(family, minlength = 8, prefix = "[FAM]_"), mo_family9 = abbreviate_mo(family, minlength = 9, prefix = "[FAM]_"), mo_family = ifelse(!is.na(mo_old), mo_old, mo_family8), mo_duplicated = duplicated(mo_family), mo_family = ifelse(mo_duplicated, mo_family9, mo_family), mo_duplicated = duplicated(mo_family) ) %>% ungroup() if (any(mo_family$mo_duplicated, na.rm = TRUE)) stop("Duplicate MO codes for family!") mo_family <- mo_family %>% select(kingdom, family, mo_family) # construct code part for genus - keep old code where available and generate new ones where needed mo_genus <- taxonomy %>% filter(rank == "genus") %>% distinct(kingdom, genus) %>% # get available old MO codes left_join(AMR::microorganisms %>% filter(rank == "genus") %>% transmute(mo_genus_old = gsub("^[A-Z]+_", "", as.character(mo)), kingdom, genus) %>% distinct(kingdom, genus, .keep_all = TRUE), by = c("kingdom", "genus") ) %>% distinct(kingdom, genus, .keep_all = TRUE) %>% # since kingdom is part of the code, genus abbreviations may be duplicated between kingdoms group_by(kingdom) %>% # generate new MO codes for genus and set the right one mutate( mo_genus_new5 = abbreviate_mo(genus, 5), mo_genus_new5b = paste0(abbreviate_mo(genus, 5), 1), mo_genus_new6 = abbreviate_mo(genus, 6), mo_genus_new7 = abbreviate_mo(genus, 7), mo_genus_new8 = abbreviate_mo(genus, 8), mo_genus_new = case_when( !is.na(mo_genus_old) ~ mo_genus_old, !mo_genus_new5 %in% mo_genus_old ~ mo_genus_new5, !mo_genus_new6 %in% mo_genus_old ~ mo_genus_new6, !mo_genus_new7 %in% mo_genus_old ~ mo_genus_new7, !mo_genus_new8 %in% mo_genus_old ~ mo_genus_new8, !mo_genus_new5b %in% mo_genus_old ~ mo_genus_new5b, TRUE ~ mo_genus_old ), mo_duplicated = duplicated(mo_genus_new), mo_genus_new = case_when( !mo_duplicated ~ mo_genus_new, mo_duplicated & mo_genus_new == mo_genus_new5 ~ mo_genus_new6, mo_duplicated & mo_genus_new == mo_genus_new6 ~ mo_genus_new7, mo_duplicated & mo_genus_new == mo_genus_new7 ~ mo_genus_new8, mo_duplicated & mo_genus_new == mo_genus_new8 ~ mo_genus_new5b, TRUE ~ NA_character_ ), mo_duplicated = duplicated(mo_genus_new) ) %>% ungroup() if (any(mo_genus$mo_duplicated, na.rm = TRUE) | anyNA(mo_genus$mo_genus_new)) stop("Duplicate MO codes for genus!") # no duplicates *within kingdoms*, so keep the right columns for left joining later mo_genus <- mo_genus %>% select(kingdom, genus, mo_genus = mo_genus_new) # same for species - keep old where available and create new per kingdom-genus where needed: mo_species <- taxonomy %>% filter(rank == "species") %>% distinct(kingdom, genus, species) %>% left_join(AMR::microorganisms %>% filter(rank == "species") %>% transmute(mo_species_old = gsub("^[A-Z]+_[A-Z]+_", "", as.character(mo)), kingdom, genus, species) %>% filter(mo_species_old %unlike% "-") %>% distinct(kingdom, genus, species, .keep_all = TRUE), by = c("kingdom", "genus", "species") ) %>% distinct(kingdom, genus, species, .keep_all = TRUE) %>% group_by(kingdom, genus) %>% mutate( mo_species_new4 = abbreviate_mo(species, 4, hyphen_as_space = TRUE), mo_species_new5 = abbreviate_mo(species, 5, hyphen_as_space = TRUE), mo_species_new5b = paste0(abbreviate_mo(species, 5, hyphen_as_space = TRUE), 1), mo_species_new6 = abbreviate_mo(species, 6, hyphen_as_space = TRUE), mo_species_new7 = abbreviate_mo(species, 7, hyphen_as_space = TRUE), mo_species_new8 = abbreviate_mo(species, 8, hyphen_as_space = TRUE), mo_species_new = case_when( !is.na(mo_species_old) ~ mo_species_old, !mo_species_new4 %in% mo_species_old ~ mo_species_new4, !mo_species_new5 %in% mo_species_old ~ mo_species_new5, !mo_species_new6 %in% mo_species_old ~ mo_species_new6, !mo_species_new7 %in% mo_species_old ~ mo_species_new7, !mo_species_new8 %in% mo_species_old ~ mo_species_new8, !mo_species_new5b %in% mo_species_old ~ mo_species_new5b, TRUE ~ mo_species_old ), mo_duplicated = duplicated(mo_species_new), mo_species_new = case_when( !mo_duplicated ~ mo_species_new, mo_duplicated & mo_species_new == mo_species_new4 ~ mo_species_new5, mo_duplicated & mo_species_new == mo_species_new5 ~ mo_species_new6, mo_duplicated & mo_species_new == mo_species_new6 ~ mo_species_new7, mo_duplicated & mo_species_new == mo_species_new7 ~ mo_species_new8, mo_duplicated & mo_species_new == mo_species_new8 ~ mo_species_new5b, TRUE ~ NA_character_ ), mo_duplicated = duplicated(mo_species_new) ) %>% ungroup() if (any(mo_species$mo_duplicated, na.rm = TRUE) | anyNA(mo_species$mo_species_new)) stop("Duplicate MO codes for species!") # no duplicates *within kingdoms*, so keep the right columns for left joining later mo_species <- mo_species %>% select(kingdom, genus, species, mo_species = mo_species_new) # same for subspecies - keep old where available and create new per kingdom-genus-species where needed: mo_subspecies <- taxonomy %>% filter(rank == "subspecies") %>% distinct(kingdom, genus, species, subspecies) %>% left_join(AMR::microorganisms %>% filter(rank %in% c("subspecies", "subsp.", "infraspecies")) %>% transmute(mo_subspecies_old = gsub("^[A-Z]+_[A-Z]+_[A-Z]+_", "", as.character(mo)), kingdom, genus, species, subspecies) %>% filter(mo_subspecies_old %unlike% "-") %>% distinct(kingdom, genus, species, subspecies, .keep_all = TRUE), by = c("kingdom", "genus", "species", "subspecies") ) %>% distinct(kingdom, genus, species, subspecies, .keep_all = TRUE) %>% group_by(kingdom, genus, species) %>% mutate( mo_subspecies_new4 = abbreviate_mo(subspecies, 4, hyphen_as_space = TRUE), mo_subspecies_new5 = abbreviate_mo(subspecies, 5, hyphen_as_space = TRUE), mo_subspecies_new5b = paste0(abbreviate_mo(subspecies, 5, hyphen_as_space = TRUE), 1), mo_subspecies_new6 = abbreviate_mo(subspecies, 6, hyphen_as_space = TRUE), mo_subspecies_new7 = abbreviate_mo(subspecies, 7, hyphen_as_space = TRUE), mo_subspecies_new8 = abbreviate_mo(subspecies, 8, hyphen_as_space = TRUE), mo_subspecies_new = case_when( !is.na(mo_subspecies_old) ~ mo_subspecies_old, !mo_subspecies_new4 %in% mo_subspecies_old ~ mo_subspecies_new4, !mo_subspecies_new5 %in% mo_subspecies_old ~ mo_subspecies_new5, !mo_subspecies_new6 %in% mo_subspecies_old ~ mo_subspecies_new6, !mo_subspecies_new7 %in% mo_subspecies_old ~ mo_subspecies_new7, !mo_subspecies_new8 %in% mo_subspecies_old ~ mo_subspecies_new8, !mo_subspecies_new5b %in% mo_subspecies_old ~ mo_subspecies_new5b, TRUE ~ mo_subspecies_old ), mo_duplicated = duplicated(mo_subspecies_new), mo_subspecies_new = case_when( !mo_duplicated ~ mo_subspecies_new, mo_duplicated & mo_subspecies_new == mo_subspecies_new4 ~ mo_subspecies_new5, mo_duplicated & mo_subspecies_new == mo_subspecies_new5 ~ mo_subspecies_new6, mo_duplicated & mo_subspecies_new == mo_subspecies_new6 ~ mo_subspecies_new7, mo_duplicated & mo_subspecies_new == mo_subspecies_new7 ~ mo_subspecies_new8, mo_duplicated & mo_subspecies_new == mo_subspecies_new8 ~ mo_subspecies_new5b, TRUE ~ NA_character_ ), mo_duplicated = duplicated(mo_subspecies_new) ) %>% ungroup() if (any(mo_subspecies$mo_duplicated, na.rm = TRUE) | anyNA(mo_subspecies$mo_subspecies_new)) stop("Duplicate MO codes for subspecies!") # no duplicates *within kingdoms*, so keep the right columns for left joining later mo_subspecies <- mo_subspecies %>% select(kingdom, genus, species, subspecies, mo_subspecies = mo_subspecies_new) # unknowns - manually added mo_unknown <- AMR::microorganisms %>% filter(fullname %like% "unknown") %>% transmute(fullname, mo_unknown = as.character(mo)) # apply the new codes! taxonomy <- taxonomy %>% left_join(mo_kingdom, by = "kingdom") %>% left_join(mo_phylum, by = c("kingdom", "phylum")) %>% left_join(mo_class, by = c("kingdom", "class")) %>% left_join(mo_order, by = c("kingdom", "order")) %>% left_join(mo_family, by = c("kingdom", "family")) %>% left_join(mo_genus, by = c("kingdom", "genus")) %>% left_join(mo_species, by = c("kingdom", "genus", "species")) %>% left_join(mo_subspecies, by = c("kingdom", "genus", "species", "subspecies")) %>% left_join(mo_unknown, by = "fullname") %>% mutate(across(starts_with("mo_"), function(x) ifelse(is.na(x), "", x))) %>% mutate( mo = case_when( fullname %like% "unknown" ~ mo_unknown, # add special cases for taxons higher than genus rank == "kingdom" ~ paste(mo_kingdom, "[KNG]", toupper(kingdom), sep = "_"), rank == "phylum" ~ paste(mo_kingdom, mo_phylum, sep = "_"), rank == "class" ~ paste(mo_kingdom, mo_class, sep = "_"), rank == "order" ~ paste(mo_kingdom, mo_order, sep = "_"), rank == "family" ~ paste(mo_kingdom, mo_family, sep = "_"), TRUE ~ paste(mo_kingdom, mo_genus, mo_species, mo_subspecies, sep = "_") ), mo = trimws(gsub("_+$", "", mo)), .before = 1 ) %>% select(!starts_with("mo_")) %>% arrange(fullname) # now check these - e.g. Nitrospira is the name of a genus AND its class taxonomy %>% filter(fullname %in% .[duplicated(fullname), "fullname", drop = TRUE]) %>% View() taxonomy <- taxonomy %>% mutate(rank_index = case_when(kingdom == "Bacteria" ~ 1, kingdom == "Fungi" ~ 2, kingdom == "Protozoa" ~ 3, kingdom == "Archaea" ~ 4, TRUE ~ 5)) %>% arrange(fullname, rank_index) %>% distinct(fullname, .keep_all = TRUE) %>% select(-rank_index) %>% filter(mo != "") # this must not exist: taxonomy %>% filter(mo %like% "__") %>% View() taxonomy <- taxonomy %>% filter(mo %unlike% "__") # Some integrity checks --------------------------------------------------- # are mo codes unique? taxonomy %>% filter(mo %in% .[duplicated(mo), "mo", drop = TRUE]) taxonomy <- taxonomy %>% distinct(mo, .keep_all = TRUE) # are fullnames unique? taxonomy %>% filter(fullname %in% .[duplicated(fullname), "fullname", drop = TRUE]) # are all GBIFs available? taxonomy %>% filter(!gbif_parent %in% gbif) %>% count(rank) # try to find the right gbif IDs taxonomy$gbif_parent[which(!taxonomy$gbif_parent %in% taxonomy$gbif & taxonomy$rank == "species")] <- taxonomy$gbif[match(taxonomy$genus[which(!taxonomy$gbif_parent %in% taxonomy$gbif & taxonomy$rank == "species")], taxonomy$genus)] taxonomy$gbif_parent[which(!taxonomy$gbif_parent %in% taxonomy$gbif & taxonomy$rank == "class")] <- taxonomy$gbif[match(taxonomy$phylum[which(!taxonomy$gbif_parent %in% taxonomy$gbif & taxonomy$rank == "class")], taxonomy$phylum)] taxonomy %>% filter(!gbif_parent %in% gbif) %>% count(rank) # are all LPSNs available? taxonomy %>% filter(!lpsn_parent %in% lpsn) %>% count(rank) # make GBIF refer to newest renaming according to LPSN taxonomy$gbif_renamed_to[which(!is.na(taxonomy$gbif_renamed_to) & !is.na(taxonomy$lpsn_renamed_to))] <- taxonomy$gbif[match(taxonomy$lpsn_renamed_to[which(!is.na(taxonomy$gbif_renamed_to) & !is.na(taxonomy$lpsn_renamed_to))], taxonomy$lpsn)] # Save intermediate results (3) ------------------------------------------- saveRDS(taxonomy, "data-raw/taxonomy3.rds") # Remove unwanted taxonomic entries from Protoza/Fungi -------------------- # this must be done after the microbial ID generation, since it will otherwise generate a lot of different IDs taxonomy <- taxonomy %>% filter( # Protozoa: !(phylum %in% c("Choanozoa", "Mycetozoa") & prevalence == 3), # Fungi: !(phylum %in% c("Ascomycota", "Zygomycota", "Basidiomycota") & prevalence == 3), !(genus %in% c("Phoma", "Leptosphaeria", "Physarum") & rank %in% c("species", "subspecies")), # only genus of this rare fungus, with resp. 1300 and 800 species # (leave Alternaria in there, part of human mycobiome and opportunistic pathogen) # Animalia: !genus %in% c("Lucilia", "Lumbricus"), !(class == "Insecta" & rank %in% c("species", "subspecies")), # keep only genus of insects !(genus == "Amoeba" & kingdom == "Animalia"), !(genus %in% c("Aedes", "Anopheles") & rank %in% c("species", "subspecies")), # only genus of the many hundreds of mosquitoes species kingdom != "Plantae" ) # this kingdom only contained Curvularia and Hymenolepis, which have coincidental twin names with Fungi # no ghost families, orders classes, phyla taxonomy <- taxonomy %>% group_by(kingdom, family) %>% filter(n() > 1 | fullname %like% "unknown" | rank == "kingdom") %>% group_by(kingdom, order) %>% filter(n() > 1 | fullname %like% "unknown" | rank == "kingdom") %>% group_by(kingdom, class) %>% filter(n() > 1 | fullname %like% "unknown" | rank == "kingdom") %>% group_by(kingdom, phylum) %>% filter(n() > 1 | fullname %like% "unknown" | rank == "kingdom") %>% ungroup() message("\nCongratulations! The new taxonomic table will contain ", format(nrow(taxonomy), big.mark = ","), " rows.\n", "This was ", format(nrow(AMR::microorganisms), big.mark = ","), " rows.\n") # these are the new ones: taxonomy %>% filter(!paste(kingdom, fullname) %in% paste(AMR::microorganisms$kingdom, AMR::microorganisms$fullname)) %>% View() # these were removed: AMR::microorganisms %>% filter(!paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname)) %>% View() AMR::microorganisms %>% filter(!fullname %in% taxonomy$fullname) %>% View() # Add SNOMED CT ----------------------------------------------------------- # we will use Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS) # as a source, which copies directly from the latest US SNOMED CT version # - go to https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009 # - check that current online version is higher than TAXONOMY_VERSION$SNOMED # - if so, click on 'Download Value Set', choose 'TXT' snomed <- vroom("data-raw/SNOMED_PHVS_Microorganism_CDC_V12.txt", skip = 3) %>% select(1:2) %>% setNames(c("snomed", "mo")) %>% mutate(snomed = as.character(snomed)) # try to get name of MO snomed <- snomed %>% mutate(mo = gsub("ss. ", "", mo, fixed = TRUE)) %>% mutate(fullname = case_when( mo %like_case% "[A-Z][a-z]+ [a-z]+ [a-z]{4,} " ~ gsub("(^|.*)([A-Z][a-z]+ [a-z]+ [a-z]{4,}) .*", "\\2", mo), mo %like_case% "[A-Z][a-z]+ [a-z]{4,} " ~ gsub("(^|.*)([A-Z][a-z]+ [a-z]{4,}) .*", "\\2", mo), mo %like_case% "[A-Z][a-z]+" ~ gsub("(^|.*)([A-Z][a-z]+) .*", "\\2", mo), TRUE ~ NA_character_ )) %>% filter(fullname %in% taxonomy$fullname) message(nrow(snomed), " SNOMED codes will be added to ", n_distinct(snomed$fullname), " microorganisms") snomed <- snomed %>% group_by(fullname) %>% summarise(snomed = list(snomed)) taxonomy <- taxonomy %>% left_join(snomed, by = "fullname") # Clean data set ---------------------------------------------------------- # format to tibble and check again for invalid characters taxonomy <- taxonomy %>% select(mo, fullname, status, kingdom:subspecies, rank, ref, source, starts_with("lpsn"), starts_with("gbif"), prevalence, snomed) %>% df_remove_nonASCII() # set class class(taxonomy$mo) <- c("mo", "character") ### this was previously needed?? Since 2022 M. catarrhalis seems to be "accepted" again # # Moraxella catarrhalis was named Branhamella catarrhalis (Catlin, 1970), but this is unaccepted in clinical microbiology # # we keep them both # taxonomy$status[which(taxonomy$fullname == "Moraxella catarrhalis")] # taxonomy$lpsn_renamed_to[which(taxonomy$fullname == "Moraxella catarrhalis")] # taxonomy$status[which(taxonomy$fullname == "Moraxella catarrhalis")] <- "accepted" # taxonomy$lpsn_renamed_to[which(taxonomy$fullname == "Moraxella catarrhalis")] <- NA_character_ # Save to package --------------------------------------------------------- microorganisms <- taxonomy usethis::use_data(microorganisms, overwrite = TRUE, version = 2, compress = "xz") rm(microorganisms) # DON'T FORGET TO UPDATE R/_globals.R! # Test updates ------------------------------------------------------------ # and check: these codes should not be missing (will otherwise throw a unit test error): AMR::microorganisms.codes %>% filter(!mo %in% taxonomy$mo) AMR::rsi_translation %>% filter(!mo %in% taxonomy$mo) AMR::example_isolates %>% filter(!mo %in% taxonomy$mo) AMR::intrinsic_resistant %>% filter(!mo %in% taxonomy$mo) # load new data sets devtools::load_all(".") # reset previously changed mo codes if (!identical(rsi_translation$mo, as.mo(rsi_translation$mo, language = NULL))) { rsi_translation$mo <- as.mo(rsi_translation$mo, language = NULL) usethis::use_data(rsi_translation, overwrite = TRUE, version = 2, compress = "xz") rm(rsi_translation) } if (!identical(microorganisms.codes$mo, as.mo(microorganisms.codes$mo, language = NULL))) { microorganisms.codes <- microorganisms.codes %>% filter(mo %in% microorganisms$mo) microorganisms.codes$mo <- as.mo(microorganisms.codes$mo, language = NULL) usethis::use_data(microorganisms.codes, overwrite = TRUE, version = 2, compress = "xz") rm(microorganisms.codes) } if (!identical(example_isolates$mo, as.mo(example_isolates$mo, language = NULL))) { example_isolates$mo <- as.mo(example_isolates$mo, language = NULL) usethis::use_data(example_isolates, overwrite = TRUE, version = 2) rm(example_isolates) } # load new data sets again devtools::load_all(".") source("data-raw/_pre_commit_hook.R") devtools::load_all(".") if (!identical(intrinsic_resistant$mo, as.mo(intrinsic_resistant$mo, language = NULL))) { stop("Run data-raw/reproduction_of_intrinsic_resistant.R again") } # run the unit tests Sys.setenv(NOT_CRAN = "true") testthat::test_file("tests/testthat/test-data.R") testthat::test_file("tests/testthat/test-mo.R") testthat::test_file("tests/testthat/test-mo_property.R")