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