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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2022 Berends MS, Luz CF et al. #
# 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/ #
# ==================================================================== #
# get all data from the WHOCC website
get_atc_table <- function(atc_group) {
# give as input J0XXX, like atc_group = "J05AB"
downloaded <- read_html(paste0("https://www.whocc.no/atc_ddd_index/?code=", atc_group, "&showdescription=no"))
table_title <- downloaded %>% html_nodes(paste0('a[href="./?code=', atc_group, '"]')) %>% html_text()
table_content <- downloaded %>%
html_nodes("table") %>%
html_table(header = TRUE) %>%
# returns list, so make data.frame out of it
as.data.frame(stringsAsFactors = FALSE) %>%
# select right columns
select(atc = ATC.code, name = Name, ddd = DDD, unit = U, ddd_type = Adm.R) %>%
# fill empty rows
mutate(atc = ifelse(atc == "", lag(atc), atc), name = ifelse(name == "", lag(name), name)) %>%
pivot_wider(names_from = ddd_type, values_from = c(ddd, unit)) %>%
mutate(atc_group = table_title)
if (!"ddd_O" %in% colnames(table_content)) {
table_content <- table_content %>% mutate(ddd_O = NA_real_, unit_O = NA_character_)
}
if (!"ddd_P" %in% colnames(table_content)) {
table_content <- table_content %>% mutate(ddd_P = NA_real_, unit_P = NA_character_)
}
table_content %>% select(atc, name, atc_group,
oral_ddd = ddd_O, oral_units = unit_O,
iv_ddd = ddd_P, iv_units = unit_P)
}
# these are the relevant groups for input: https://www.whocc.no/atc_ddd_index/?code=J05A (J05 only contains J05A)
atc_groups <- c("J05AA", "J05AB", "J05AC", "J05AD", "J05AE", "J05AF", "J05AG", "J05AH", "J05AP", "J05AR", "J05AX")
# get the first
antivirals <- get_atc_table(atc_groups[1])
# bind all others to it
for (i in 2:length(atc_groups)) {
antivirals <- rbind(antivirals, get_atc_table(atc_groups[i]))
}
# arrange on name, untibble it
antivirals <- antivirals %>% arrange(name) %>% as.data.frame(stringsAsFactors = FALSE)
# add PubChem Compound ID (cid) and their trade names - functions are in file to create `antibiotics` data set
CIDs <- get_CID(antivirals$name)
# these could not be found:
antivirals[is.na(CIDs),] %>% View()
# get brand names from PubChem
synonyms <- get_synonyms(CIDs)
synonyms <- lapply(synonyms,
function(x) {
if (length(x) == 0 | all(is.na(x))) {
""
} else {
x
}})
antivirals <- antivirals %>%
transmute(atc,
cid = CIDs,
name,
atc_group,
synonyms = unname(synonyms),
oral_ddd,
oral_units,
iv_ddd,
iv_units)
# save it
usethis::use_data(antivirals, overwrite = TRUE)