AMR/data-raw/snomed.R

# ==================================================================== #
# TITLE                                                                #
# Antimicrobial Resistance (AMR) Analysis                              #
#                                                                      #
# SOURCE                                                               #
# https://gitlab.com/msberends/AMR                                     #
#                                                                      #
# LICENCE                                                              #
# (c) 2018-2020 Berends MS, Luz CF et al.                              #
#                                                                      #
# 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 more info: https://msberends.gitlab.io/AMR.    #
# ==================================================================== #

library(AMR)
library(tidyverse)

# go to https://www.nictiz.nl/standaardisatie/terminologiecentrum/referentielijsten/micro-organismen/ (Ctrl/Cmd + A in table)
# read the table from clipboard
snomed <- clipr::read_clip_tbl(skip = 2)
snomed <- snomed %>%
  dplyr::filter(gsub("(^genus |^familie |^stam |ss.? |subsp.? |subspecies )", "", 
              Omschrijving.,
              ignore.case = TRUE) %in% c(microorganisms$fullname, 
                                         microorganisms.old$fullname)) %>% 
  dplyr::transmute(fullname = mo_name(Omschrijving.),
            snomed = as.integer(Id)) %>% 
  dplyr::filter(!fullname %like% "unknown")
snomed_trans <- snomed %>%
  group_by(fullname) %>%
  mutate(snomed_list = list(snomed)) %>%
  ungroup() %>%
  select(fullname, snomed = snomed_list) %>%
  distinct(fullname, .keep_all = TRUE)

microorganisms <- AMR::microorganisms %>% 
  left_join(snomed_trans)
# remove the NULLs, set to NA
microorganisms$snomed <- lapply(microorganisms$snomed, function(x) if (length(x) == 0)  NA else x)

microorganisms <- dataset_UTF8_to_ASCII(microorganisms)

usethis::use_data(microorganisms, overwrite = TRUE)
rm(microorganisms)

# OLD ---------------------------------------------------------------------

# baseUrl <- 'https://browser.ihtsdotools.org/snowstorm/snomed-ct'
# edition <- 'MAIN'
# version <- '2019-07-31'
# 
# microorganisms.snomed <- data.frame(conceptid = character(0),
#                                     mo = character(0),
#                                     stringsAsFactors = FALSE)
# microorganisms$snomed <- ""
# 
# # for (i in 1:50) {
# for (i in 1:1000) {
#   
#   if (i %% 10 == 0) {
#     cat(paste0(i, " - ", cleaner::percentage(i / nrow(microorganisms)), "\n"))
#   }
#   
#   mo_data <- microorganisms %>% 
#     filter(mo == microorganisms$mo[i]) %>% 
#     as.list()
#   
#   if (!mo_data$rank %in% c("genus", "species")) {
#     next
#   }
#   
#   searchTerm <- paste0(
#     ifelse(mo_data$rank == "genus", "Genus ", ""),
#     mo_data$fullname, 
#     " (organism)")
#   
#   url <- paste0(baseUrl, '/browser/',
#                 edition, '/', 
#                 version, 
#                 '/descriptions?term=', curl::curl_escape(searchTerm),
#                 '&mode=fullText&activeFilter=true&limit=', 250)
#   results <- url %>% 
#     httr::GET() %>%
#     httr::content(type = "text", encoding = "UTF-8") %>% 
#     jsonlite::fromJSON(flatten = TRUE) %>% 
#     .$items
#   if (NROW(results) == 0) {
#     next
#   } else {
#     message("Adding ", crayon::italic(mo_data$fullname))
#   }
#   
#   tryCatch(
#     microorganisms$snomed[i] <- results %>% filter(term == searchTerm) %>% pull(concept.conceptId),
#     error = function(e) invisible()
#   )
#   
#   if (nrow(results) > 1) {
#       microorganisms.snomed <- microorganisms.snomed %>% 
#         bind_rows(tibble(conceptid = results %>% filter(term != searchTerm) %>% pull(concept.conceptId) %>% unique(),
#                          mo = as.character(mo_data$mo)))
#   }
# }