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AMR/data-raw/_internals.R

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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2021 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/ #
# ==================================================================== #
# Run this file to update the package using:
# source("data-raw/_internals.R")
library(dplyr, warn.conflicts = FALSE)
devtools::load_all(quiet = TRUE)
old_globalenv <- ls(envir = globalenv())
# Helper functions --------------------------------------------------------
create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
# Determination of which staphylococcal species are CoNS/CoPS according to:
# - Becker et al. 2014, PMID 25278577
# - Becker et al. 2019, PMID 30872103
# - Becker et al. 2020, PMID 32056452
# this function returns class <mo>
MO_staph <- AMR::microorganisms
MO_staph <- MO_staph[which(MO_staph$genus == "Staphylococcus"), , drop = FALSE]
if (type == "CoNS") {
MO_staph[which(MO_staph$species %in% c("coagulase-negative", "argensis", "arlettae",
"auricularis", "borealis", "caeli", "capitis", "caprae",
"carnosus", "casei", "chromogenes", "cohnii", "condimenti",
"croceilyticus",
"debuckii", "devriesei", "edaphicus", "epidermidis",
"equorum", "felis", "fleurettii", "gallinarum",
"haemolyticus", "hominis", "jettensis", "kloosii",
"lentus", "lugdunensis", "massiliensis", "microti",
"muscae", "nepalensis", "pasteuri", "petrasii",
"pettenkoferi", "piscifermentans", "pragensis", "pseudoxylosus",
"pulvereri", "rostri", "saccharolyticus", "saprophyticus",
"sciuri", "simulans", "stepanovicii", "succinus",
"ureilyticus",
"vitulinus", "vitulus", "warneri", "xylosus")
| (MO_staph$species == "schleiferi" & MO_staph$subspecies %in% c("schleiferi", ""))),
"mo", drop = TRUE]
} else if (type == "CoPS") {
MO_staph[which(MO_staph$species %in% c("coagulase-positive", "coagulans",
"agnetis", "argenteus",
"cornubiensis",
"delphini", "lutrae",
"hyicus", "intermedius",
"pseudintermedius", "pseudointermedius",
"schweitzeri", "simiae")
| (MO_staph$species == "schleiferi" & MO_staph$subspecies == "coagulans")),
"mo", drop = TRUE]
}
}
create_AB_lookup <- function() {
AB_lookup <- AMR::antibiotics
AB_lookup$generalised_name <- generalise_antibiotic_name(AB_lookup$name)
AB_lookup$generalised_synonyms <- lapply(AB_lookup$synonyms, generalise_antibiotic_name)
AB_lookup$generalised_abbreviations <- lapply(AB_lookup$abbreviations, generalise_antibiotic_name)
AB_lookup$generalised_loinc <- lapply(AB_lookup$loinc, generalise_antibiotic_name)
AB_lookup$generalised_all <- unname(lapply(as.list(as.data.frame(t(AB_lookup[,
c("ab", "atc", "cid", "name",
colnames(AB_lookup)[colnames(AB_lookup) %like% "generalised"]),
drop = FALSE]),
stringsAsFactors = FALSE)),
function(x) {
x <- generalise_antibiotic_name(unname(unlist(x)))
x[x != ""]
}))
AB_lookup
}
create_MO_lookup <- function() {
MO_lookup <- AMR::microorganisms
MO_lookup$kingdom_index <- NA_real_
MO_lookup[which(MO_lookup$kingdom == "Bacteria" | MO_lookup$mo == "UNKNOWN"), "kingdom_index"] <- 1
MO_lookup[which(MO_lookup$kingdom == "Fungi"), "kingdom_index"] <- 2
MO_lookup[which(MO_lookup$kingdom == "Protozoa"), "kingdom_index"] <- 3
MO_lookup[which(MO_lookup$kingdom == "Archaea"), "kingdom_index"] <- 4
# all the rest
MO_lookup[which(is.na(MO_lookup$kingdom_index)), "kingdom_index"] <- 5
# use this paste instead of `fullname` to work with Viridans Group Streptococci, etc.
MO_lookup$fullname_lower <- tolower(trimws(paste(MO_lookup$genus,
MO_lookup$species,
MO_lookup$subspecies)))
ind <- MO_lookup$genus == "" | grepl("^[(]unknown ", MO_lookup$fullname)
MO_lookup[ind, "fullname_lower"] <- tolower(MO_lookup[ind, "fullname"])
MO_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", MO_lookup$fullname_lower, perl = TRUE))
# add a column with only "e coli" like combinations
MO_lookup$g_species <- gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO_lookup$fullname_lower, perl = TRUE)
# so arrange data on prevalence first, then kingdom, then full name
MO_lookup[order(MO_lookup$prevalence, MO_lookup$kingdom_index, MO_lookup$fullname_lower), ]
}
create_MO.old_lookup <- function() {
MO.old_lookup <- AMR::microorganisms.old
MO.old_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", tolower(trimws(MO.old_lookup$fullname))))
# add a column with only "e coli"-like combinations
MO.old_lookup$g_species <- trimws(gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO.old_lookup$fullname_lower))
# so arrange data on prevalence first, then full name
MO.old_lookup[order(MO.old_lookup$prevalence, MO.old_lookup$fullname_lower), ]
}
create_intr_resistance <- function() {
# for mo_is_intrinsic_resistant() - saves a lot of time when executed on this vector
paste(AMR::microorganisms[match(AMR::intrinsic_resistant$microorganism, AMR::microorganisms$fullname), "mo", drop = TRUE],
AMR::antibiotics[match(AMR::intrinsic_resistant$antibiotic, AMR::antibiotics$name), "ab", drop = TRUE])
}
# Save internal data to R/sysdata.rda -------------------------------------
# See 'data-raw/eucast_rules.tsv' for the EUCAST reference file
eucast_rules_file <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
skip = 10,
sep = "\t",
stringsAsFactors = FALSE,
header = TRUE,
strip.white = TRUE,
na = c(NA, "", NULL)) %>%
# take the order of the reference.rule_group column in the original data file
mutate(reference.rule_group = factor(reference.rule_group,
levels = unique(reference.rule_group),
ordered = TRUE),
sorting_rule = ifelse(grepl("^Table", reference.rule, ignore.case = TRUE), 1, 2)) %>%
arrange(reference.rule_group,
reference.version,
sorting_rule,
reference.rule) %>%
mutate(reference.rule_group = as.character(reference.rule_group)) %>%
select(-sorting_rule)
# Translations
translations_file <- utils::read.delim(file = "data-raw/translations.tsv",
sep = "\t",
stringsAsFactors = FALSE,
header = TRUE,
blank.lines.skip = TRUE,
fill = TRUE,
strip.white = TRUE,
encoding = "UTF-8",
fileEncoding = "UTF-8",
na.strings = c(NA, "", NULL),
allowEscapes = TRUE, # else "\\1" will be imported as "\\\\1"
quote = "")
# Old microorganism codes
microorganisms.translation <- readRDS("data-raw/microorganisms.translation.rds")
# for mo_is_intrinsic_resistant() - saves a lot of time when executed on this vector
INTRINSIC_R <- create_intr_resistance()
# for checking input in `language` argument in e.g. mo_*() and ab_*() functions
LANGUAGES_SUPPORTED <- sort(c("en", colnames(translations_file)[nchar(colnames(translations_file)) == 2]))
# vectors of CoNS and CoPS, improves speed in as.mo()
MO_CONS <- create_species_cons_cops("CoNS")
MO_COPS <- create_species_cons_cops("CoPS")
# reference data - they have additional columns compared to `antibiotics` and `microorganisms` to improve speed
AB_lookup <- create_AB_lookup()
MO_lookup <- create_MO_lookup()
MO.old_lookup <- create_MO.old_lookup()
# antibiotic groups
# (these will also be used for eucast_rules() and understanding data-raw/eucast_rules.tsv)
globalenv_before_ab <- c(ls(envir = globalenv()), "globalenv_before_ab")
AMINOGLYCOSIDES <- antibiotics %>% filter(group %like% "aminoglycoside") %>% pull(ab)
AMINOPENICILLINS <- as.ab(c("AMP", "AMX"))
CARBAPENEMS <- antibiotics %>% filter(group %like% "carbapenem") %>% pull(ab)
CEPHALOSPORINS <- antibiotics %>% filter(group %like% "cephalosporin") %>% pull(ab)
CEPHALOSPORINS_1ST <- antibiotics %>% filter(group %like% "cephalosporin.*1") %>% pull(ab)
CEPHALOSPORINS_2ND <- antibiotics %>% filter(group %like% "cephalosporin.*2") %>% pull(ab)
CEPHALOSPORINS_3RD <- antibiotics %>% filter(group %like% "cephalosporin.*3") %>% pull(ab)
CEPHALOSPORINS_EXCEPT_CAZ <- CEPHALOSPORINS[CEPHALOSPORINS != "CAZ"]
FLUOROQUINOLONES <- antibiotics %>% filter(atc_group2 %like% "fluoroquinolone") %>% pull(ab)
LIPOGLYCOPEPTIDES <- as.ab(c("DAL", "ORI", "TLV")) # dalba/orita/tela
GLYCOPEPTIDES <- antibiotics %>% filter(group %like% "glycopeptide") %>% pull(ab)
GLYCOPEPTIDES_EXCEPT_LIPO <- GLYCOPEPTIDES[!GLYCOPEPTIDES %in% LIPOGLYCOPEPTIDES]
LINCOSAMIDES <- antibiotics %>% filter(atc_group2 %like% "lincosamide") %>% pull(ab) %>% c("PRL")
MACROLIDES <- antibiotics %>% filter(atc_group2 %like% "macrolide") %>% pull(ab)
OXAZOLIDINONES <- antibiotics %>% filter(group %like% "oxazolidinone") %>% pull(ab)
PENICILLINS <- antibiotics %>% filter(group %like% "penicillin") %>% pull(ab)
POLYMYXINS <- antibiotics %>% filter(group %like% "polymyxin") %>% pull(ab)
STREPTOGRAMINS <- antibiotics %>% filter(atc_group2 %like% "streptogramin") %>% pull(ab)
TETRACYCLINES <- antibiotics %>% filter(atc_group2 %like% "tetracycline") %>% pull(ab)
TETRACYCLINES_EXCEPT_TGC <- TETRACYCLINES[TETRACYCLINES != "TGC"]
UREIDOPENICILLINS <- as.ab(c("PIP", "TZP", "AZL", "MEZ"))
BETALACTAMS <- c(PENICILLINS, CEPHALOSPORINS, CARBAPENEMS)
DEFINED_AB_GROUPS <- ls(envir = globalenv())
DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab]
# Export to package as internal data ----
usethis::use_data(eucast_rules_file,
translations_file,
microorganisms.translation,
INTRINSIC_R,
LANGUAGES_SUPPORTED,
MO_CONS,
MO_COPS,
AB_lookup,
MO_lookup,
MO.old_lookup,
AMINOGLYCOSIDES,
AMINOPENICILLINS,
CARBAPENEMS,
CEPHALOSPORINS,
CEPHALOSPORINS_1ST,
CEPHALOSPORINS_2ND,
CEPHALOSPORINS_3RD,
CEPHALOSPORINS_EXCEPT_CAZ,
FLUOROQUINOLONES,
LIPOGLYCOPEPTIDES,
GLYCOPEPTIDES,
GLYCOPEPTIDES_EXCEPT_LIPO,
LINCOSAMIDES,
MACROLIDES,
OXAZOLIDINONES,
PENICILLINS,
POLYMYXINS,
STREPTOGRAMINS,
TETRACYCLINES,
TETRACYCLINES_EXCEPT_TGC,
UREIDOPENICILLINS,
BETALACTAMS,
DEFINED_AB_GROUPS,
internal = TRUE,
overwrite = TRUE,
version = 2,
compress = "xz")
# Export data sets to the repository in different formats -----------------
write_md5 <- function(object) {
conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
writeLines(digest::digest(object, "md5"), conn)
close(conn)
}
changed_md5 <- function(object) {
tryCatch({
conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
compared <- digest::digest(object, "md5") != readLines(con = conn)
close(conn)
compared
}, error = function(e) TRUE)
}
# give official names to ABs and MOs
rsi <- dplyr::mutate(rsi_translation, ab = ab_name(ab), mo = mo_name(mo))
if (changed_md5(rsi)) {
usethis::ui_info(paste0("Saving {usethis::ui_value('rsi_translation')} to {usethis::ui_value('/data-raw/')}"))
write_md5(rsi)
try(saveRDS(rsi, "data-raw/rsi_translation.rds", version = 2, compress = "xz"), silent = TRUE)
try(write.table(rsi, "data-raw/rsi_translation.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
try(haven::write_sas(rsi, "data-raw/rsi_translation.sas"), silent = TRUE)
try(haven::write_sav(rsi, "data-raw/rsi_translation.sav"), silent = TRUE)
try(haven::write_dta(rsi, "data-raw/rsi_translation.dta"), silent = TRUE)
try(openxlsx::write.xlsx(rsi, "data-raw/rsi_translation.xlsx"), silent = TRUE)
}
mo <- dplyr::mutate_if(microorganisms, ~!is.numeric(.), as.character)
if (changed_md5(mo)) {
usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms')} to {usethis::ui_value('/data-raw/')}"))
write_md5(mo)
try(saveRDS(mo, "data-raw/microorganisms.rds", version = 2, compress = "xz"), silent = TRUE)
try(write.table(mo, "data-raw/microorganisms.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
try(haven::write_sas(dplyr::select(mo, -snomed), "data-raw/microorganisms.sas"), silent = TRUE)
try(haven::write_sav(dplyr::select(mo, -snomed), "data-raw/microorganisms.sav"), silent = TRUE)
try(haven::write_dta(dplyr::select(mo, -snomed), "data-raw/microorganisms.dta"), silent = TRUE)
try(openxlsx::write.xlsx(mo, "data-raw/microorganisms.xlsx"), silent = TRUE)
}
if (changed_md5(microorganisms.old)) {
usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms.old')} to {usethis::ui_value('/data-raw/')}"))
write_md5(microorganisms.old)
try(saveRDS(microorganisms.old, "data-raw/microorganisms.old.rds", version = 2, compress = "xz"), silent = TRUE)
try(write.table(microorganisms.old, "data-raw/microorganisms.old.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
try(haven::write_sas(microorganisms.old, "data-raw/microorganisms.old.sas"), silent = TRUE)
try(haven::write_sav(microorganisms.old, "data-raw/microorganisms.old.sav"), silent = TRUE)
try(haven::write_dta(microorganisms.old, "data-raw/microorganisms.old.dta"), silent = TRUE)
try(openxlsx::write.xlsx(microorganisms.old, "data-raw/microorganisms.old.xlsx"), silent = TRUE)
}
ab <- dplyr::mutate_if(antibiotics, ~!is.numeric(.), as.character)
if (changed_md5(ab)) {
usethis::ui_info(paste0("Saving {usethis::ui_value('antibiotics')} to {usethis::ui_value('/data-raw/')}"))
write_md5(ab)
try(saveRDS(ab, "data-raw/antibiotics.rds", version = 2, compress = "xz"), silent = TRUE)
try(write.table(ab, "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
try(haven::write_sas(ab, "data-raw/antibiotics.sas"), silent = TRUE)
try(haven::write_sav(ab, "data-raw/antibiotics.sav"), silent = TRUE)
try(haven::write_dta(ab, "data-raw/antibiotics.dta"), silent = TRUE)
try(openxlsx::write.xlsx(ab, "data-raw/antibiotics.xlsx"), silent = TRUE)
}
av <- dplyr::mutate_if(antivirals, ~!is.numeric(.), as.character)
if (changed_md5(av)) {
usethis::ui_info(paste0("Saving {usethis::ui_value('antivirals')} to {usethis::ui_value('/data-raw/')}"))
write_md5(av)
try(saveRDS(av, "data-raw/antivirals.rds", version = 2, compress = "xz"), silent = TRUE)
try(write.table(av, "data-raw/antivirals.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
try(haven::write_sas(av, "data-raw/antivirals.sas"), silent = TRUE)
try(haven::write_sav(av, "data-raw/antivirals.sav"), silent = TRUE)
try(haven::write_dta(av, "data-raw/antivirals.dta"), silent = TRUE)
try(openxlsx::write.xlsx(av, "data-raw/antivirals.xlsx"), silent = TRUE)
}
if (changed_md5(intrinsic_resistant)) {
usethis::ui_info(paste0("Saving {usethis::ui_value('intrinsic_resistant')} to {usethis::ui_value('/data-raw/')}"))
write_md5(intrinsic_resistant)
try(saveRDS(intrinsic_resistant, "data-raw/intrinsic_resistant.rds", version = 2, compress = "xz"), silent = TRUE)
try(write.table(intrinsic_resistant, "data-raw/intrinsic_resistant.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
try(haven::write_sas(intrinsic_resistant, "data-raw/intrinsic_resistant.sas"), silent = TRUE)
try(haven::write_sav(intrinsic_resistant, "data-raw/intrinsic_resistant.sav"), silent = TRUE)
try(haven::write_dta(intrinsic_resistant, "data-raw/intrinsic_resistant.dta"), silent = TRUE)
try(openxlsx::write.xlsx(intrinsic_resistant, "data-raw/intrinsic_resistant.xlsx"), silent = TRUE)
}
if (changed_md5(dosage)) {
usethis::ui_info(paste0("Saving {usethis::ui_value('dosage')} to {usethis::ui_value('/data-raw/')}"))
write_md5(dosage)
try(saveRDS(dosage, "data-raw/dosage.rds", version = 2, compress = "xz"), silent = TRUE)
try(write.table(dosage, "data-raw/dosage.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
try(haven::write_sas(dosage, "data-raw/dosage.sas"), silent = TRUE)
try(haven::write_sav(dosage, "data-raw/dosage.sav"), silent = TRUE)
try(haven::write_dta(dosage, "data-raw/dosage.dta"), silent = TRUE)
try(openxlsx::write.xlsx(dosage, "data-raw/dosage.xlsx"), silent = TRUE)
}
# remove leftovers from global env
current_globalenv <- ls(envir = globalenv())
rm(list = current_globalenv[!current_globalenv %in% old_globalenv])
rm(current_globalenv)
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