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