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299 lines
17 KiB
R
299 lines
17 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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# Save internal data 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_DF <- 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 <- 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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# for checking input in `language` argument in e.g. mo_*() and ab_*() functions
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LANGUAGES_SUPPORTED <- sort(c("en", colnames(TRANSLATIONS)[nchar(colnames(TRANSLATIONS)) == 2]))
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# EXAMPLE_ISOLATES <- readRDS("data-raw/example_isolates.rds")
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# vectors of CoNS and CoPS, improves speed in as.mo()
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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", "borealis", "caeli", "capitis", "caprae",
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"carnosus", "casei", "chromogenes", "cohnii", "condimenti",
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"croceilyticus",
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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", "pragensis", "pseudoxylosus",
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"pulvereri", "rostri", "saccharolyticus", "saprophyticus",
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"sciuri", "simulans", "stepanovicii", "succinus",
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"ureilyticus",
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"vitulinus", "vitulus", "warneri", "xylosus",
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"caledonicus", "canis",
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"durrellii", "lloydii")
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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$species %in% c("coagulase-positive", "coagulans",
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"agnetis", "argenteus",
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"cornubiensis",
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"delphini", "lutrae",
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"hyicus", "intermedius",
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"pseudintermedius", "pseudointermedius",
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"schweitzeri", "simiae",
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"roterodami")
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| (MO_staph$species == "schleiferi" & MO_staph$subspecies == "coagulans")),
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"mo", drop = TRUE]
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}
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}
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MO_CONS <- create_species_cons_cops("CoNS")
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MO_COPS <- create_species_cons_cops("CoPS")
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MO_STREP_ABCG <- as.mo(MO_lookup[which(MO_lookup$genus == "Streptococcus"), "mo", drop = TRUE], Lancefield = TRUE) %in% c("B_STRPT_GRPA", "B_STRPT_GRPB", "B_STRPT_GRPC", "B_STRPT_GRPG")
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# antibiotic groups
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# (these will also be used for eucast_rules() and understanding data-raw/eucast_rules.tsv)
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globalenv_before_ab <- c(ls(envir = globalenv()), "globalenv_before_ab")
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AB_AMINOGLYCOSIDES <- antibiotics %>% filter(group %like% "aminoglycoside") %>% pull(ab)
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AB_AMINOPENICILLINS <- as.ab(c("AMP", "AMX"))
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AB_ANTIFUNGALS <- AB_lookup %>% filter(group %like% "antifungal") %>% pull(ab)
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AB_ANTIMYCOBACTERIALS <- AB_lookup %>% filter(group %like% "antimycobacterial") %>% pull(ab)
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AB_CARBAPENEMS <- antibiotics %>% filter(group %like% "carbapenem") %>% pull(ab)
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AB_CEPHALOSPORINS <- antibiotics %>% filter(group %like% "cephalosporin") %>% pull(ab)
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AB_CEPHALOSPORINS_1ST <- antibiotics %>% filter(group %like% "cephalosporin.*1") %>% pull(ab)
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AB_CEPHALOSPORINS_2ND <- antibiotics %>% filter(group %like% "cephalosporin.*2") %>% pull(ab)
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AB_CEPHALOSPORINS_3RD <- antibiotics %>% filter(group %like% "cephalosporin.*3") %>% pull(ab)
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AB_CEPHALOSPORINS_4TH <- antibiotics %>% filter(group %like% "cephalosporin.*4") %>% pull(ab)
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AB_CEPHALOSPORINS_5TH <- antibiotics %>% filter(group %like% "cephalosporin.*5") %>% pull(ab)
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AB_CEPHALOSPORINS_EXCEPT_CAZ <- AB_CEPHALOSPORINS[AB_CEPHALOSPORINS != "CAZ"]
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AB_FLUOROQUINOLONES <- antibiotics %>% filter(atc_group2 %like% "fluoroquinolone" | (group %like% "quinolone" & is.na(atc_group2))) %>% pull(ab)
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AB_GLYCOPEPTIDES <- antibiotics %>% filter(group %like% "glycopeptide") %>% pull(ab)
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AB_LIPOGLYCOPEPTIDES <- as.ab(c("DAL", "ORI", "TLV")) # dalba/orita/tela
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AB_GLYCOPEPTIDES_EXCEPT_LIPO <- AB_GLYCOPEPTIDES[!AB_GLYCOPEPTIDES %in% AB_LIPOGLYCOPEPTIDES]
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AB_LINCOSAMIDES <- antibiotics %>% filter(atc_group2 %like% "lincosamide" | (group %like% "lincosamide" & is.na(atc_group2))) %>% pull(ab)
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AB_MACROLIDES <- antibiotics %>% filter(atc_group2 %like% "macrolide" | (group %like% "macrolide" & is.na(atc_group2))) %>% pull(ab)
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AB_OXAZOLIDINONES <- antibiotics %>% filter(group %like% "oxazolidinone") %>% pull(ab)
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AB_PENICILLINS <- antibiotics %>% filter(group %like% "penicillin") %>% pull(ab)
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AB_POLYMYXINS <- antibiotics %>% filter(group %like% "polymyxin") %>% pull(ab)
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AB_QUINOLONES <- antibiotics %>% filter(group %like% "quinolone") %>% pull(ab)
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AB_STREPTOGRAMINS <- antibiotics %>% filter(atc_group2 %like% "streptogramin") %>% pull(ab)
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AB_TETRACYCLINES <- antibiotics %>% filter(group %like% "tetracycline") %>% pull(ab)
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AB_TETRACYCLINES_EXCEPT_TGC <- AB_TETRACYCLINES[AB_TETRACYCLINES != "TGC"]
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AB_TRIMETHOPRIMS <- antibiotics %>% filter(group %like% "trimethoprim") %>% pull(ab)
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AB_UREIDOPENICILLINS <- as.ab(c("PIP", "TZP", "AZL", "MEZ"))
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AB_BETALACTAMS <- c(AB_PENICILLINS, AB_CEPHALOSPORINS, AB_CARBAPENEMS)
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# this will be used for documentation:
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DEFINED_AB_GROUPS <- ls(envir = globalenv())
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DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab]
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# Export to package as internal data ----
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usethis::use_data(EUCAST_RULES_DF,
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TRANSLATIONS,
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LANGUAGES_SUPPORTED,
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# EXAMPLE_ISOLATES,
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MO_CONS,
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MO_COPS,
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MO_STREP_ABCG,
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AB_AMINOGLYCOSIDES,
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AB_AMINOPENICILLINS,
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AB_ANTIFUNGALS,
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AB_ANTIMYCOBACTERIALS,
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AB_CARBAPENEMS,
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AB_CEPHALOSPORINS,
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AB_CEPHALOSPORINS_1ST,
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AB_CEPHALOSPORINS_2ND,
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AB_CEPHALOSPORINS_3RD,
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AB_CEPHALOSPORINS_4TH,
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AB_CEPHALOSPORINS_5TH,
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AB_CEPHALOSPORINS_EXCEPT_CAZ,
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AB_FLUOROQUINOLONES,
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AB_LIPOGLYCOPEPTIDES,
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AB_GLYCOPEPTIDES,
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AB_GLYCOPEPTIDES_EXCEPT_LIPO,
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AB_LINCOSAMIDES,
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AB_MACROLIDES,
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AB_OXAZOLIDINONES,
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AB_PENICILLINS,
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AB_POLYMYXINS,
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AB_QUINOLONES,
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AB_STREPTOGRAMINS,
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AB_TETRACYCLINES,
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AB_TETRACYCLINES_EXCEPT_TGC,
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AB_TRIMETHOPRIMS,
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AB_UREIDOPENICILLINS,
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AB_BETALACTAMS,
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DEFINED_AB_GROUPS,
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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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# 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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usethis::ui_info(paste0("Saving {usethis::ui_value('rsi_translation')} to {usethis::ui_value('/data-raw/')}"))
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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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usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms')} to {usethis::ui_value('/data-raw/')}"))
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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(dplyr::select(mo, -snomed), "data-raw/microorganisms.sas"), silent = TRUE)
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try(haven::write_sav(dplyr::select(mo, -snomed), "data-raw/microorganisms.sav"), silent = TRUE)
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try(haven::write_dta(dplyr::select(mo, -snomed), "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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usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms.old')} to {usethis::ui_value('/data-raw/')}"))
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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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usethis::ui_info(paste0("Saving {usethis::ui_value('antibiotics')} to {usethis::ui_value('/data-raw/')}"))
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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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usethis::ui_info(paste0("Saving {usethis::ui_value('antivirals')} to {usethis::ui_value('/data-raw/')}"))
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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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usethis::ui_info(paste0("Saving {usethis::ui_value('intrinsic_resistant')} to {usethis::ui_value('/data-raw/')}"))
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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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usethis::ui_info(paste0("Saving {usethis::ui_value('dosage')} to {usethis::ui_value('/data-raw/')}"))
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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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