AMR/data-raw/reproduction_of_intrinsic_r...

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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# 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 #
# 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. #
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# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
library(AMR)
library(dplyr)
int_resis <- data.frame(microorganism = microorganisms$mo, stringsAsFactors = FALSE)
for (i in seq_len(nrow(antibiotics))) {
int_resis$new <- as.rsi("S")
colnames(int_resis)[ncol(int_resis)] <- antibiotics$name[i]
}
int_resis <- eucast_rules(int_resis,
eucast_rules_df = subset(AMR:::EUCAST_RULES_DF,
is.na(have_these_values) & reference.version == 3.3),
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info = FALSE)
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int_resis2 <- int_resis[, sapply(int_resis, function(x) any(!is.rsi(x) | x == "R"))] %>%
tidyr::pivot_longer(-microorganism) %>%
filter(value == "R") %>%
select(microorganism, antibiotic = name)
# remove lab drugs
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untreatable <- antibiotics[which(antibiotics$name %like% "-high|EDTA|polysorbate|macromethod|screening|/nacubactam"), "name", drop = TRUE]
int_resis2 <- int_resis2 %>%
filter(!antibiotic %in% untreatable) %>%
arrange(microorganism, antibiotic)
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int_resis2$microorganism <- mo_name(int_resis2$microorganism, language = NULL)
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intrinsic_resistant <- as.data.frame(int_resis2, stringsAsFactors = FALSE)
usethis::use_data(intrinsic_resistant, internal = FALSE, overwrite = TRUE, version = 2, compress = "xz")
rm(intrinsic_resistant)
# AFTER THIS:
# DO NOT FORGET TO UPDATE THE VERSION NUMBER IN mo_is_intrinsic_resistant()