2020-08-14 13:36:10 +02:00
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# ==================================================================== #
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# TITLE #
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2021-02-02 23:57:35 +01:00
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# Antimicrobial Resistance (AMR) Data Analysis for R #
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2020-08-14 13:36:10 +02:00
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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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2020-12-27 00:30:28 +01:00
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# (c) 2018-2021 Berends MS, Luz CF et al. #
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2020-10-08 11:16:03 +02:00
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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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2020-08-14 13:36:10 +02:00
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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 data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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library(AMR)
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2021-01-03 23:40:05 +01:00
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library(dplyr)
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2020-08-14 13:36:10 +02:00
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int_resis <- data.frame(microorganism = microorganisms$mo, stringsAsFactors = FALSE)
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for (i in seq_len(nrow(antibiotics))) {
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int_resis$new <- as.rsi("S")
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colnames(int_resis)[ncol(int_resis)] <- antibiotics$name[i]
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}
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int_resis <- eucast_rules(int_resis,
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2021-06-04 21:07:55 +02:00
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eucast_rules_df = subset(AMR:::EUCAST_RULES_DF,
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is.na(have_these_values) & reference.version == 3.3),
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2020-09-24 00:30:11 +02:00
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info = FALSE)
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2020-08-14 13:36:10 +02:00
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2020-09-24 00:30:11 +02:00
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int_resis2 <- int_resis[, sapply(int_resis, function(x) any(!is.rsi(x) | x == "R"))] %>%
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2020-08-14 13:36:10 +02:00
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tidyr::pivot_longer(-microorganism) %>%
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filter(value == "R") %>%
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select(microorganism, antibiotic = name)
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# remove lab drugs
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untreatable <- antibiotics[which(antibiotics$name %like% "-high|EDTA|polysorbate|macromethod|screening"), "name", drop = TRUE]
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int_resis2 <- int_resis2 %>%
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filter(!antibiotic %in% untreatable) %>%
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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)
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usethis::use_data(intrinsic_resistant, internal = FALSE, overwrite = TRUE, version = 2, compress = "xz")
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rm(intrinsic_resistant)
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# AFTER THIS:
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# DO NOT FORGET TO UPDATE THE VERSION NUMBER IN mo_is_intrinsic_resistant()
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