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301 lines
16 KiB
R
301 lines
16 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) 2018-2021 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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# Run this file to update the package using:
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# source("data-raw/_internals.R")
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library(dplyr, warn.conflicts = FALSE)
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devtools::load_all(quiet = TRUE)
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old_globalenv <- ls(envir = globalenv())
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# Helper functions --------------------------------------------------------
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create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
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# Determination of which staphylococcal species are CoNS/CoPS according to:
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# - Becker et al. 2014, PMID 25278577
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# - Becker et al. 2019, PMID 30872103
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# - Becker et al. 2020, PMID 32056452
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# this function returns class <mo>
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MO_staph <- AMR::microorganisms
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MO_staph <- MO_staph[which(MO_staph$genus == "Staphylococcus"), , drop = FALSE]
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if (type == "CoNS") {
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MO_staph[which(MO_staph$species %in% c("coagulase-negative", "argensis", "arlettae",
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"auricularis", "caeli", "capitis", "caprae",
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"carnosus", "chromogenes", "cohnii", "condimenti",
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"debuckii", "devriesei", "edaphicus", "epidermidis",
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"equorum", "felis", "fleurettii", "gallinarum",
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"haemolyticus", "hominis", "jettensis", "kloosii",
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"lentus", "lugdunensis", "massiliensis", "microti",
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"muscae", "nepalensis", "pasteuri", "petrasii",
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"pettenkoferi", "piscifermentans", "pseudoxylosus",
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"pulvereri", "rostri", "saccharolyticus", "saprophyticus",
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"sciuri", "simulans", "stepanovicii", "succinus",
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"vitulinus", "vitulus", "warneri", "xylosus")
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| (MO_staph$species == "schleiferi" & MO_staph$subspecies %in% c("schleiferi", ""))),
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"mo", drop = TRUE]
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} else if (type == "CoPS") {
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MO_staph[which(MO_staph$species %in% c("coagulase-positive",
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"agnetis", "argenteus",
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"cornubiensis",
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"delphini", "lutrae",
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"hyicus", "intermedius",
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"pseudintermedius", "pseudointermedius",
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"schweitzeri", "simiae")
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| (MO_staph$species == "schleiferi" & MO_staph$subspecies == "coagulans")),
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"mo", drop = TRUE]
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}
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}
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create_AB_lookup <- function() {
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AB_lookup <- AMR::antibiotics
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AB_lookup$generalised_name <- generalise_antibiotic_name(AB_lookup$name)
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AB_lookup$generalised_synonyms <- lapply(AB_lookup$synonyms, generalise_antibiotic_name)
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AB_lookup$generalised_abbreviations <- lapply(AB_lookup$abbreviations, generalise_antibiotic_name)
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AB_lookup$generalised_loinc <- lapply(AB_lookup$loinc, generalise_antibiotic_name)
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AB_lookup$generalised_all <- unname(lapply(as.list(as.data.frame(t(AB_lookup[,
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c("ab", "atc", "cid", "name",
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colnames(AB_lookup)[colnames(AB_lookup) %like% "generalised"]),
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drop = FALSE]),
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stringsAsFactors = FALSE)),
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function(x) {
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x <- generalise_antibiotic_name(unname(unlist(x)))
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x[x != ""]
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}))
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AB_lookup
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}
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create_MO_lookup <- function() {
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MO_lookup <- AMR::microorganisms
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MO_lookup$kingdom_index <- NA_real_
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MO_lookup[which(MO_lookup$kingdom == "Bacteria" | MO_lookup$mo == "UNKNOWN"), "kingdom_index"] <- 1
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MO_lookup[which(MO_lookup$kingdom == "Fungi"), "kingdom_index"] <- 2
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MO_lookup[which(MO_lookup$kingdom == "Protozoa"), "kingdom_index"] <- 3
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MO_lookup[which(MO_lookup$kingdom == "Archaea"), "kingdom_index"] <- 4
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# all the rest
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MO_lookup[which(is.na(MO_lookup$kingdom_index)), "kingdom_index"] <- 5
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# use this paste instead of `fullname` to work with Viridans Group Streptococci, etc.
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MO_lookup$fullname_lower <- tolower(trimws(paste(MO_lookup$genus,
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MO_lookup$species,
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MO_lookup$subspecies)))
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ind <- MO_lookup$genus == "" | grepl("^[(]unknown ", MO_lookup$fullname)
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MO_lookup[ind, "fullname_lower"] <- tolower(MO_lookup[ind, "fullname"])
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MO_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", MO_lookup$fullname_lower, perl = TRUE))
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# add a column with only "e coli" like combinations
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MO_lookup$g_species <- gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO_lookup$fullname_lower, perl = TRUE)
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# so arrange data on prevalence first, then kingdom, then full name
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MO_lookup[order(MO_lookup$prevalence, MO_lookup$kingdom_index, MO_lookup$fullname_lower), ]
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}
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create_MO.old_lookup <- function() {
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MO.old_lookup <- AMR::microorganisms.old
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MO.old_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", tolower(trimws(MO.old_lookup$fullname))))
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# add a column with only "e coli"-like combinations
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MO.old_lookup$g_species <- trimws(gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO.old_lookup$fullname_lower))
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# so arrange data on prevalence first, then full name
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MO.old_lookup[order(MO.old_lookup$prevalence, MO.old_lookup$fullname_lower), ]
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}
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create_intr_resistance <- function() {
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# for mo_is_intrinsic_resistant() - saves a lot of time when executed on this vector
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paste(AMR::microorganisms[match(AMR::intrinsic_resistant$microorganism, AMR::microorganisms$fullname), "mo", drop = TRUE],
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AMR::antibiotics[match(AMR::intrinsic_resistant$antibiotic, AMR::antibiotics$name), "ab", drop = TRUE])
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}
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# Save internal data sets to R/sysdata.rda --------------------------------
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# See 'data-raw/eucast_rules.tsv' for the EUCAST reference file
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eucast_rules_file <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
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skip = 10,
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sep = "\t",
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stringsAsFactors = FALSE,
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header = TRUE,
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strip.white = TRUE,
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na = c(NA, "", NULL)) %>%
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# take the order of the reference.rule_group column in the original data file
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mutate(reference.rule_group = factor(reference.rule_group,
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levels = unique(reference.rule_group),
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ordered = TRUE),
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sorting_rule = ifelse(grepl("^Table", reference.rule, ignore.case = TRUE), 1, 2)) %>%
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arrange(reference.rule_group,
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reference.version,
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sorting_rule,
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reference.rule) %>%
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mutate(reference.rule_group = as.character(reference.rule_group)) %>%
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select(-sorting_rule)
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# Translations
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translations_file <- utils::read.delim(file = "data-raw/translations.tsv",
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sep = "\t",
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stringsAsFactors = FALSE,
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header = TRUE,
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blank.lines.skip = TRUE,
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fill = TRUE,
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strip.white = TRUE,
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encoding = "UTF-8",
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fileEncoding = "UTF-8",
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na.strings = c(NA, "", NULL),
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allowEscapes = TRUE, # else "\\1" will be imported as "\\\\1"
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quote = "")
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# Old microorganism codes
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microorganisms.translation <- readRDS("data-raw/microorganisms.translation.rds")
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# for mo_is_intrinsic_resistant() - saves a lot of time when executed on this vector
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INTRINSIC_R <- create_intr_resistance()
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# for checking input in `language` argument in e.g. mo_*() and ab_*() functions
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LANGUAGES_SUPPORTED <- sort(c("en", unique(translations_file$lang)))
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# vectors of CoNS and CoPS, improves speed in as.mo()
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MO_CONS <- create_species_cons_cops("CoNS")
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MO_COPS <- create_species_cons_cops("CoPS")
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# reference data - they have additional columns compared to `antibiotics` and `microorganisms` to improve speed
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AB_lookup <- create_AB_lookup()
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MO_lookup <- create_MO_lookup()
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MO.old_lookup <- create_MO.old_lookup()
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# Export to package as internal data ----
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usethis::use_data(eucast_rules_file,
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translations_file,
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microorganisms.translation,
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INTRINSIC_R,
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LANGUAGES_SUPPORTED,
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MO_CONS,
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MO_COPS,
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AB_lookup,
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MO_lookup,
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MO.old_lookup,
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internal = TRUE,
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overwrite = TRUE,
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version = 2,
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compress = "xz")
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# Export data sets to the repository in different formats -----------------
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write_md5 <- function(object) {
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conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
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writeLines(digest::digest(object, "md5"), conn)
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close(conn)
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}
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changed_md5 <- function(object) {
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tryCatch({
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conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
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compared <- digest::digest(object, "md5") != readLines(con = conn)
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close(conn)
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compared
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}, error = function(e) TRUE)
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}
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usethis::ui_done(paste0("Saving raw data to {usethis::ui_value('/data-raw/')}"))
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# give official names to ABs and MOs
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rsi <- dplyr::mutate(rsi_translation, ab = ab_name(ab), mo = mo_name(mo))
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if (changed_md5(rsi)) {
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write_md5(rsi)
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try(saveRDS(rsi, "data-raw/rsi_translation.rds", version = 2, compress = "xz"), silent = TRUE)
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try(write.table(rsi, "data-raw/rsi_translation.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
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try(haven::write_sas(rsi, "data-raw/rsi_translation.sas"), silent = TRUE)
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try(haven::write_sav(rsi, "data-raw/rsi_translation.sav"), silent = TRUE)
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try(haven::write_dta(rsi, "data-raw/rsi_translation.dta"), silent = TRUE)
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try(openxlsx::write.xlsx(rsi, "data-raw/rsi_translation.xlsx"), silent = TRUE)
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}
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mo <- dplyr::mutate_if(microorganisms, ~!is.numeric(.), as.character)
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if (changed_md5(mo)) {
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write_md5(mo)
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try(saveRDS(mo, "data-raw/microorganisms.rds", version = 2, compress = "xz"), silent = TRUE)
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try(write.table(mo, "data-raw/microorganisms.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
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try(haven::write_sas(mo, "data-raw/microorganisms.sas"), silent = TRUE)
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try(haven::write_sav(mo, "data-raw/microorganisms.sav"), silent = TRUE)
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try(haven::write_dta(mo, "data-raw/microorganisms.dta"), silent = TRUE)
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try(openxlsx::write.xlsx(mo, "data-raw/microorganisms.xlsx"), silent = TRUE)
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}
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if (changed_md5(microorganisms.old)) {
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write_md5(microorganisms.old)
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try(saveRDS(microorganisms.old, "data-raw/microorganisms.old.rds", version = 2, compress = "xz"), silent = TRUE)
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try(write.table(microorganisms.old, "data-raw/microorganisms.old.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
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try(haven::write_sas(microorganisms.old, "data-raw/microorganisms.old.sas"), silent = TRUE)
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try(haven::write_sav(microorganisms.old, "data-raw/microorganisms.old.sav"), silent = TRUE)
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try(haven::write_dta(microorganisms.old, "data-raw/microorganisms.old.dta"), silent = TRUE)
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try(openxlsx::write.xlsx(microorganisms.old, "data-raw/microorganisms.old.xlsx"), silent = TRUE)
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}
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ab <- dplyr::mutate_if(antibiotics, ~!is.numeric(.), as.character)
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if (changed_md5(ab)) {
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write_md5(ab)
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try(saveRDS(ab, "data-raw/antibiotics.rds", version = 2, compress = "xz"), silent = TRUE)
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try(write.table(ab, "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
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try(haven::write_sas(ab, "data-raw/antibiotics.sas"), silent = TRUE)
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try(haven::write_sav(ab, "data-raw/antibiotics.sav"), silent = TRUE)
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try(haven::write_dta(ab, "data-raw/antibiotics.dta"), silent = TRUE)
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try(openxlsx::write.xlsx(ab, "data-raw/antibiotics.xlsx"), silent = TRUE)
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}
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av <- dplyr::mutate_if(antivirals, ~!is.numeric(.), as.character)
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if (changed_md5(av)) {
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write_md5(av)
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try(saveRDS(av, "data-raw/antivirals.rds", version = 2, compress = "xz"), silent = TRUE)
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try(write.table(av, "data-raw/antivirals.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
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try(haven::write_sas(av, "data-raw/antivirals.sas"), silent = TRUE)
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try(haven::write_sav(av, "data-raw/antivirals.sav"), silent = TRUE)
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try(haven::write_dta(av, "data-raw/antivirals.dta"), silent = TRUE)
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try(openxlsx::write.xlsx(av, "data-raw/antivirals.xlsx"), silent = TRUE)
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}
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if (changed_md5(intrinsic_resistant)) {
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write_md5(intrinsic_resistant)
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try(saveRDS(intrinsic_resistant, "data-raw/intrinsic_resistant.rds", version = 2, compress = "xz"), silent = TRUE)
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try(write.table(intrinsic_resistant, "data-raw/intrinsic_resistant.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
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try(haven::write_sas(intrinsic_resistant, "data-raw/intrinsic_resistant.sas"), silent = TRUE)
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try(haven::write_sav(intrinsic_resistant, "data-raw/intrinsic_resistant.sav"), silent = TRUE)
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try(haven::write_dta(intrinsic_resistant, "data-raw/intrinsic_resistant.dta"), silent = TRUE)
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try(openxlsx::write.xlsx(intrinsic_resistant, "data-raw/intrinsic_resistant.xlsx"), silent = TRUE)
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}
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if (changed_md5(dosage)) {
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write_md5(dosage)
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try(saveRDS(dosage, "data-raw/dosage.rds", version = 2, compress = "xz"), silent = TRUE)
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try(write.table(dosage, "data-raw/dosage.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
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try(haven::write_sas(dosage, "data-raw/dosage.sas"), silent = TRUE)
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try(haven::write_sav(dosage, "data-raw/dosage.sav"), silent = TRUE)
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try(haven::write_dta(dosage, "data-raw/dosage.dta"), silent = TRUE)
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try(openxlsx::write.xlsx(dosage, "data-raw/dosage.xlsx"), silent = TRUE)
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}
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# remove leftovers from global env
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current_globalenv <- ls(envir = globalenv())
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rm(list = current_globalenv[!current_globalenv %in% old_globalenv])
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rm(current_globalenv)
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