mirror of https://github.com/msberends/AMR.git
104 lines
6.5 KiB
R
104 lines
6.5 KiB
R
# ==================================================================== #
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# TITLE #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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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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# CITE AS #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
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# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
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# Data. Journal of Statistical Software, 104(3), 1-31. #
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# https://doi.org/10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen and the University Medical #
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# Center Groningen in The Netherlands, in collaboration with many #
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# colleagues from around the world, see our website. #
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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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# antibiotic class selectors
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expect_equal(ncol(example_isolates[, ab_class("antimyco"), drop = FALSE]), 1, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, aminoglycosides(), drop = FALSE]), 4, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, aminopenicillins(), drop = FALSE]), 2, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, betalactams(), drop = FALSE]), 16, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, carbapenems(), drop = FALSE]), 2, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, cephalosporins(), drop = FALSE]), 7, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, cephalosporins_1st(), drop = FALSE]), 1, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, cephalosporins_2nd(), drop = FALSE]), 2, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, cephalosporins_3rd(), drop = FALSE]), 3, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, cephalosporins_4th(), drop = FALSE]), 1, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, cephalosporins_5th(), drop = FALSE]), 0, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, fluoroquinolones(), drop = FALSE]), 2, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, glycopeptides(), drop = FALSE]), 2, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, lincosamides(), drop = FALSE]), 1, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, lipoglycopeptides(), drop = FALSE]), 0, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, macrolides(), drop = FALSE]), 2, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, oxazolidinones(), drop = FALSE]), 1, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, penicillins(), drop = FALSE]), 7, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, polymyxins(), drop = FALSE]), 1, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, streptogramins(), drop = FALSE]), 0, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, quinolones(), drop = FALSE]), 2, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, tetracyclines(), drop = FALSE]), 3, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, trimethoprims(), drop = FALSE]), 2, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, ureidopenicillins(), drop = FALSE]), 1, tolerance = 0.5)
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# Examples:
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# select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
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expect_equal(ncol(example_isolates[, c("mo", aminoglycosides())]), 5, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, c(administrable_per_os() & penicillins())]), 5, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, c(administrable_iv() & penicillins())]), 7, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, c(administrable_iv() | penicillins())]), 37, tolerance = 0.5)
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# filter using any() or all()
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expect_equal(nrow(example_isolates[any(carbapenems() == "R"), ]), 55, tolerance = 0.5)
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expect_equal(nrow(subset(example_isolates, any(carbapenems() == "R"))), 55, tolerance = 0.5)
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# filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
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expect_equal(nrow(example_isolates[any(carbapenems()), ]), 962, tolerance = 0.5)
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expect_equal(nrow(example_isolates[all(carbapenems()), ]), 756, tolerance = 0.5)
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expect_equal(nrow(example_isolates[any(carbapenems() == "R"), ]), 55, tolerance = 0.5)
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expect_equal(nrow(example_isolates[any(carbapenems() != "R"), ]), 910, tolerance = 0.5)
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expect_equal(nrow(example_isolates[carbapenems() != "R", ]), 704, tolerance = 0.5)
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# filter with multiple antibiotic selectors using c()
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expect_equal(nrow(example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]), 26, tolerance = 0.5)
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# filter + select in one go: get penicillins in carbapenems-resistant strains
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expect_equal(nrow(example_isolates[any(carbapenems() == "R"), penicillins()]), 55, tolerance = 0.5)
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expect_equal(ncol(example_isolates[any(carbapenems() == "R"), penicillins()]), 7, tolerance = 0.5)
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x <- data.frame(
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x = 0,
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mo = 0,
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gen = "S",
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genta = "S",
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J01GB03 = "S",
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tobra = "S",
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Tobracin = "S"
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)
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# should have the first hits
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expect_identical(
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colnames(x[, aminoglycosides()]),
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c("gen", "tobra")
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)
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if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
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expect_equal(example_isolates %>% select(administrable_per_os() & penicillins()) %>% ncol(), 5, tolerance = 0.5)
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expect_equal(example_isolates %>% select(administrable_iv() & penicillins()) %>% ncol(), 7, tolerance = 0.5)
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expect_equal(example_isolates %>% select(administrable_iv() | penicillins()) %>% ncol(), 37, tolerance = 0.5)
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# expect_warning(example_isolates %>% select(GEH = GEN) %>% select(aminoglycosides(only_treatable = TRUE)))
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}
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