mirror of https://github.com/msberends/AMR.git
161 lines
6.2 KiB
R
161 lines
6.2 KiB
R
# ==================================================================== #
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# TITLE: #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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# #
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# SOURCE CODE: #
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# https://github.com/msberends/AMR #
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# #
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# PLEASE CITE THIS SOFTWARE AS: #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
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# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
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# Data. Journal of Statistical Software, 104(3), 1-31. #
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# https://doi.org/10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen and the University Medical #
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# Center Groningen in The Netherlands, in collaboration with many #
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# colleagues from around the world, see our website. #
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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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library(dplyr)
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library(tidyr)
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library(rvest)
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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://atcddd.fhi.no/atc_ddd_index/?code=", atc_group, "&showdescription=no"))
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table_title <- downloaded %>%
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html_nodes(paste0('a[href^="./?code=', atc_group, '&"]')) %>%
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html_text()
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table_title <- table_title[tolower(table_title) != "show text from guidelines"][1]
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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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}
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# these are the relevant groups for input: https://atcddd.fhi.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", "J05AJ", "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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message(atc_groups[i], "...")
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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 %>%
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arrange(name) %>%
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as.data.frame(stringsAsFactors = FALSE)
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# add PubChem Compound ID (cid) and their trade names
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# see `data-raw/reproduction_of_antibiotics` for get_CID() and get_synonyms()
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CIDs <- get_CID(antivirals$name)
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# these could not be found:
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antivirals[is.na(CIDs), ] %>% View()
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# get brand names from PubChem
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synonyms <- get_synonyms(CIDs)
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synonyms <- lapply(
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synonyms,
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function(x) {
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if (length(x) == 0 | all(is.na(x))) {
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""
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} else {
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x
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}
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}
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)
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antivirals <- antivirals %>%
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transmute(atc,
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cid = as.double(CIDs),
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name,
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atc_group,
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synonyms = unname(synonyms),
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oral_ddd,
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oral_units,
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iv_ddd,
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iv_units
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) %>%
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AMR:::dataset_UTF8_to_ASCII()
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av_codes <- tibble(name = antivirals$name %>%
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strsplit("(, | and )") %>%
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unlist() %>%
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unique() %>%
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sort()) %>%
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mutate(av_1st = toupper(abbreviate(name, minlength = 3, use.classes = FALSE))) %>%
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filter(!name %in% c("acid", "dipivoxil", "disoproxil", "marboxil", "alafenamide"))
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replace_with_av_code <- function(name) {
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unname(av_codes$av_1st[match(name, av_codes$name)])
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}
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names_codes <- antivirals %>%
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separate(name,
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into = paste0("name", c(1:7)),
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sep = "(, | and )",
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remove = FALSE,
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fill = "right"
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) %>%
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# remove empty columns
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select(!where(function(x) all(is.na(x)))) %>%
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mutate_at(vars(matches("name[1-9]")), replace_with_av_code) %>%
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unite(av, matches("name[1-9]"), sep = "+", na.rm = TRUE) %>%
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mutate(name = gsub("(, | and )", "/", name))
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substr(names_codes$name, 1, 1) <- toupper(substr(names_codes$name, 1, 1))
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antivirals <- bind_cols(
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names_codes %>% select(av, name),
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antivirals %>% select(-name)
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)
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class(antivirals$av) <- c("av", "character")
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antivirals <- antivirals %>% AMR:::dataset_UTF8_to_ASCII()
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# ! add loinc, run 'data-raw/loinc.R' !
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# de-duplicate synonyms
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for (i in 1:nrow(antivirals)) {
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syn <- as.character(sort(unique(tolower(antivirals[i, "synonyms", drop = TRUE][[1]]))))
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syn <- syn[!syn %in% tolower(antivirals[i, "name", drop = TRUE])]
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antivirals[i, "synonyms"][[1]] <- ifelse(length(syn[!syn == ""]) == 0, list(""), list(syn))
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}
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antivirals <- antivirals %>% AMR:::dataset_UTF8_to_ASCII()
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# check it
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antivirals
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# save it
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usethis::use_data(antivirals, overwrite = TRUE, internal = FALSE, compress = "xz", version = 2)
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