AMR/R/zzz.R

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R
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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2020 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 analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
.onLoad <- function(libname, pkgname) {
assign(x = "AB_lookup",
value = create_AB_lookup(),
envir = asNamespace("AMR"))
assign(x = "MO_lookup",
value = create_MO_lookup(),
envir = asNamespace("AMR"))
assign(x = "MO.old_lookup",
value = create_MO.old_lookup(),
envir = asNamespace("AMR"))
assign(x = "LANGUAGES_SUPPORTED",
value = sort(c("en", unique(translations_file$lang))),
envir = asNamespace("AMR"))
assign(x = "MO_CONS",
value = create_species_cons_cops("CoNS"),
envir = asNamespace("AMR"))
assign(x = "MO_COPS",
value = create_species_cons_cops("CoPS"),
envir = asNamespace("AMR"))
# Support for tibble headers (type_sum) and tibble columns content (pillar_shaft)
# without the need to depend on other packages. This was suggested by the
# developers of the vctrs package:
# https://github.com/r-lib/vctrs/blob/05968ce8e669f73213e3e894b5f4424af4f46316/R/register-s3.R
s3_register("pillar::pillar_shaft", "ab")
s3_register("pillar::pillar_shaft", "mo")
s3_register("pillar::pillar_shaft", "rsi")
s3_register("pillar::pillar_shaft", "mic")
s3_register("pillar::pillar_shaft", "disk")
s3_register("tibble::type_sum", "ab")
s3_register("tibble::type_sum", "mo")
s3_register("tibble::type_sum", "rsi")
s3_register("tibble::type_sum", "mic")
s3_register("tibble::type_sum", "disk")
# Support for frequency tables from the cleaner package
s3_register("cleaner::freq", "mo")
s3_register("cleaner::freq", "rsi")
# Support from skim() from the skimr package
s3_register("skimr::get_skimmers", "mo")
s3_register("skimr::get_skimmers", "rsi")
s3_register("skimr::get_skimmers", "mic")
s3_register("skimr::get_skimmers", "disk")
}
.onAttach <- function(...) {
# show notice in 10% of cases in interactive session
if (!interactive() || stats::runif(1) > 0.1 || isTRUE(as.logical(getOption("AMR_silentstart", FALSE)))) {
return()
}
packageStartupMessage("Thank you for using the AMR package! ",
"If you have a minute, please anonymously fill in this short questionnaire to improve the package and its functionalities:",
"\nhttps://msberends.github.io/AMR/survey.html",
"\n[ prevent his notice with suppressPackageStartupMessages(library(AMR)) or use options(AMR_silentstart = TRUE) ]")
}
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$species %in% c("coagulase-negative", "argensis", "arlettae",
"auricularis", "caeli", "capitis", "caprae",
"carnosus", "chromogenes", "cohnii", "condimenti",
"debuckii", "devriesei", "edaphicus", "epidermidis",
"equorum", "felis", "fleurettii", "gallinarum",
"haemolyticus", "hominis", "jettensis", "kloosii",
"lentus", "lugdunensis", "massiliensis", "microti",
"muscae", "nepalensis", "pasteuri", "petrasii",
"pettenkoferi", "piscifermentans", "pseudoxylosus",
"rostri", "saccharolyticus", "saprophyticus",
"sciuri", "simulans", "stepanovicii", "succinus",
"vitulinus", "warneri", "xylosus")
| (MO_staph$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",
"simiae", "agnetis",
"delphini", "lutrae",
"hyicus", "intermedius",
"pseudintermedius", "pseudointermedius",
"schweitzeri", "argenteus")
| (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
}
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), ]
}