mirror of https://github.com/msberends/AMR.git
207 lines
8.9 KiB
R
207 lines
8.9 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.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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# #
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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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# #
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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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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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library(openxlsx)
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library(dplyr)
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library(cleaner)
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library(AMR)
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read_EUCAST <- function(sheet, file = "data-raw/v_10.0_Breakpoint_Tables.xlsx") {
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message("Getting sheet ", sheet)
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sheet.bak <- sheet
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raw_data <- read.xlsx(xlsxFile = file,
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sheet = sheet,
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colNames = FALSE,
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skipEmptyRows = FALSE,
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skipEmptyCols = FALSE,
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fillMergedCells = TRUE,
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na.strings = c("", "-", "NA", "IE", "IP"))
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# in the info header in the Excel file, EUCAST mentions which genera are targeted
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if (sheet %like% "anaerob.*Gram.*posi") {
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sheet <- paste0(c("Actinomyces", "Bifidobacterium", "Clostridioides",
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"Clostridium", "Cutibacterium", "Eggerthella",
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"Eubacterium", "Lactobacillus", "Propionibacterium",
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"Staphylococcus saccharolyticus"),
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collapse = "_")
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} else if (sheet %like% "anaerob.*Gram.*nega") {
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sheet <- paste0(c("Bacteroides",
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"Bilophila",
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"Fusobacterium",
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"Mobiluncus",
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"Parabacteroides",
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"Porphyromonas",
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"Prevotella"),
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collapse = "_")
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} else if (sheet == "Streptococcus A,B,C,G") {
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sheet <- paste0(microorganisms %>%
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filter(genus == "Streptococcus") %>%
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mutate(lancefield = mo_name(mo, Lancefield = TRUE)) %>%
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filter(lancefield %like% "^Streptococcus group") %>%
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pull(fullname),
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collapse = "_")
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} else if (sheet %like% "PK.*PD") {
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sheet <- "UNKNOWN"
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}
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mo_sheet <- paste0(as.mo(unlist(strsplit(sheet, "_"))), collapse = "|")
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set_columns_names <- function(x, cols) {
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colnames(x) <- cols[1:length(colnames(x))]
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x
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}
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get_mo <- function(x) {
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for (i in seq_len(length(x))) {
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y <- trimws(unlist(strsplit(x[i], "(,|and)")))
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y <- trimws(gsub("[(].*[)]", "", y))
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y <- suppressWarnings(as.mo(y, allow_uncertain = FALSE))
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y <- y[!is.na(y) & y != "UNKNOWN"]
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x[i] <- paste(y, collapse = "|")
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}
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x
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}
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MICs_with_trailing_superscript <- c(0.0011:0.0019, 11:19, 21:29, 0.51:0.59, 41:49,
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81:89, 0.031:0.039, 0.061:0.069, 0.251:0.259,
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0.1251:0.1259, 161:169, 321:329)
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has_zone_diameters <- rep(any(unlist(raw_data) %like% "zone diameter"), nrow(raw_data))
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cleaned <- raw_data %>%
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as_tibble() %>%
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set_columns_names(LETTERS) %>%
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transmute(drug = A,
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MIC_S = B,
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MIC_R = C,
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disk_dose = ifelse(has_zone_diameters, E, NA_character_),
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disk_S = ifelse(has_zone_diameters, `F`, NA_character_),
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disk_R = ifelse(has_zone_diameters, G, NA_character_)) %>%
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filter(!is.na(drug),
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!(is.na(MIC_S) & is.na(MIC_R) & is.na(disk_S) & is.na(disk_R)),
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!MIC_S %like% "(MIC|S ≤|note)",
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drug != MIC_S) %>%
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mutate(administration = case_when(drug %like% "[( ]oral" ~ "oral",
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drug %like% "[( ]iv" ~ "iv",
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TRUE ~ NA_character_),
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uti = ifelse(drug %like% "(UTI|urinary|urine)", TRUE, FALSE),
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systemic = ifelse(drug %like% "(systemic|septic)", TRUE, FALSE),
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mo = ifelse(drug %like% "([.]|spp)", get_mo(drug), mo_sheet)) %>%
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# clean disk doses
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mutate(disk_dose = clean_character(disk_dose, remove = "[^0-9.-]")) %>%
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# clean MIC and disk values
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mutate(MIC_S = gsub(".,.", "", MIC_S), # remove superscript notes with comma, like 0.5^2,3
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MIC_R = gsub(".,.", "", MIC_R),
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disk_S = gsub(".,.", "", disk_S),
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disk_R = gsub(".,.", "", disk_R),
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MIC_S = clean_double(MIC_S), # make them valid numeric values
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MIC_R = clean_double(MIC_R),
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disk_S = clean_integer(disk_S),
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disk_R = clean_integer(disk_R),
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# invalid MIC values have a superscript text, delete those
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MIC_S = ifelse(MIC_S %in% MICs_with_trailing_superscript,
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substr(MIC_S, 1, nchar(MIC_S) - 1),
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MIC_S),
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MIC_R = ifelse(MIC_R %in% MICs_with_trailing_superscript,
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substr(MIC_R, 1, nchar(MIC_R) - 1),
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MIC_R)
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) %>%
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# clean drug names
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mutate(drug = gsub(" ?[(, ].*$", "", drug),
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drug = gsub("[1-9]+$", "", drug),
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ab = as.ab(drug)) %>%
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select(ab, mo, everything(), -drug)
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# new row for every different MO mentioned
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for (i in 1:nrow(cleaned)) {
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mo <- cleaned[i, "mo", drop = TRUE]
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if (grepl(pattern = "|", mo, fixed = TRUE)) {
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mo_vect <- unlist(strsplit(mo, "|", fixed = TRUE))
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cleaned[i, "mo"] <- mo_vect[1]
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for (j in seq_len(length(mo_vect))) {
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cleaned <- bind_rows(cleaned, cleaned[i ,])
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cleaned[nrow(cleaned), "mo"] <- mo_vect[j]
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}
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}
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}
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cleaned <- cleaned %>%
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distinct(ab, mo, administration, uti, systemic, .keep_all = TRUE) %>%
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arrange(ab, mo) %>%
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mutate_at(c("MIC_S", "MIC_R", "disk_S", "disk_R"), as.double) %>%
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pivot_longer(c("MIC_S", "MIC_R", "disk_S", "disk_R"), "type") %>%
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mutate(method = ifelse(type %like% "MIC", "MIC", "DISK"),
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type = gsub("^.*_", "breakpoint_", type)) %>%
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pivot_wider(names_from = type, values_from = value) %>%
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mutate(guideline = "EUCAST 2020",
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disk_dose = ifelse(method == "DISK", disk_dose, NA_character_),
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mo = ifelse(mo == "", mo_sheet, mo)) %>%
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filter(!(is.na(breakpoint_S) & is.na(breakpoint_R))) %>%
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# comply with rsi_translation for now
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transmute(guideline,
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method,
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site = case_when(uti ~ "UTI",
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systemic ~ "Systemic",
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TRUE ~ administration),
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mo, ab,
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ref_tbl = sheet.bak,
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disk_dose = ifelse(!is.na(disk_dose), paste0(disk_dose, "ug"), NA_character_),
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breakpoint_S,
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breakpoint_R)
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cleaned
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}
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sheets_to_analyse <- c("Enterobacterales",
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"Pseudomonas",
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"S.maltophilia",
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"Acinetobacter",
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"Staphylococcus",
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"Enterococcus",
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"Streptococcus A,B,C,G",
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"S.pneumoniae",
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"Viridans group streptococci",
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"H.influenzae",
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"M.catarrhalis",
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"N.gonorrhoeae",
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"N.meningitidis",
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"Anaerobes, Grampositive",
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"C.difficile",
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"Anaerobes, Gramnegative",
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"H.pylori",
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"L.monocytogenes",
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"P.multocida",
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"C.jejuni_C.coli",
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"Corynebacterium",
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"A.sanguinicola_A.urinae",
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"K.kingae",
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"Aeromonas",
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"B.pseudomallei",
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"M.tuberculosis",
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"PK PD breakpoints")
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new_EUCAST <- read_EUCAST(sheets_to_analyse[1]) # takes the longest time
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for (i in 2:length(sheets_to_analyse)) {
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new_EUCAST <<- new_EUCAST %>% bind_rows(read_EUCAST(sheets_to_analyse[i]))
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}
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