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94 lines
4.3 KiB
R
94 lines
4.3 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Data Analysis for R #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2022 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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# get all data from the WHOCC website
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get_atc_table <- function(atc_group) {
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# give as input J0XXX, like atc_group = "J05AB"
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downloaded <- read_html(paste0("https://www.whocc.no/atc_ddd_index/?code=", atc_group, "&showdescription=no"))
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table_title <- downloaded %>% html_nodes(paste0('a[href="./?code=', atc_group, '"]')) %>% html_text()
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table_content <- downloaded %>%
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html_nodes("table") %>%
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html_table(header = TRUE) %>%
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# returns list, so make data.frame out of it
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as.data.frame(stringsAsFactors = FALSE) %>%
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# select right columns
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select(atc = ATC.code, name = Name, ddd = DDD, unit = U, ddd_type = Adm.R) %>%
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# fill empty rows
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mutate(atc = ifelse(atc == "", lag(atc), atc), name = ifelse(name == "", lag(name), name)) %>%
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pivot_wider(names_from = ddd_type, values_from = c(ddd, unit)) %>%
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mutate(atc_group = table_title)
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if (!"ddd_O" %in% colnames(table_content)) {
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table_content <- table_content %>% mutate(ddd_O = NA_real_, unit_O = NA_character_)
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}
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if (!"ddd_P" %in% colnames(table_content)) {
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table_content <- table_content %>% mutate(ddd_P = NA_real_, unit_P = NA_character_)
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}
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table_content %>% select(atc, name, atc_group,
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oral_ddd = ddd_O, oral_units = unit_O,
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iv_ddd = ddd_P, iv_units = unit_P)
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}
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# these are the relevant groups for input: https://www.whocc.no/atc_ddd_index/?code=J05A (J05 only contains J05A)
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atc_groups <- c("J05AA", "J05AB", "J05AC", "J05AD", "J05AE", "J05AF", "J05AG", "J05AH", "J05AP", "J05AR", "J05AX")
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# get the first
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antivirals <- get_atc_table(atc_groups[1])
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# bind all others to it
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for (i in 2:length(atc_groups)) {
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antivirals <- rbind(antivirals, get_atc_table(atc_groups[i]))
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}
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# arrange on name, untibble it
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antivirals <- antivirals %>% arrange(name) %>% as.data.frame(stringsAsFactors = FALSE)
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# add PubChem Compound ID (cid) and their trade names - functions are in file to create `antibiotics` data set
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CIDs <- get_CID(antivirals$name)
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# these could not be found:
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antivirals[is.na(CIDs),] %>% View()
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# get brand names from PubChem
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synonyms <- get_synonyms(CIDs)
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synonyms <- lapply(synonyms,
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function(x) {
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if (length(x) == 0 | all(is.na(x))) {
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""
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} else {
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x
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}})
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antivirals <- antivirals %>%
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transmute(atc,
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cid = CIDs,
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name,
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atc_group,
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synonyms = unname(synonyms),
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oral_ddd,
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oral_units,
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iv_ddd,
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iv_units)
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# save it
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usethis::use_data(antivirals, overwrite = TRUE)
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