# ==================================================================== # # TITLE # # Antimicrobial Resistance (AMR) Analysis # # # # SOURCE # # https://gitlab.com/msberends/AMR # # # # LICENCE # # (c) 2018-2020 Berends MS, Luz CF et al. # # # # 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 more info: https://msberends.gitlab.io/AMR. # # ==================================================================== # context("mdro.R") test_that("mdro works", { skip_on_cran() expect_error(suppressWarnings(mdro(example_isolates, country = "invalid", col_mo = "mo", info = TRUE))) expect_error(suppressWarnings(mdro(example_isolates, country = "fr", info = TRUE))) expect_error(mdro(example_isolates, guideline = c("BRMO", "MRGN"), info = TRUE)) expect_error(mdro(example_isolates, col_mo = "invalid", info = TRUE)) outcome <- suppressWarnings(mdro(example_isolates)) outcome <- eucast_exceptional_phenotypes(example_isolates, info = TRUE) # check class expect_equal(outcome %>% class(), c("ordered", "factor")) outcome <- mdro(example_isolates, "nl", info = TRUE) # check class expect_equal(outcome %>% class(), c("ordered", "factor")) # example_isolates should have these finding using Dutch guidelines expect_equal(outcome %>% cleaner::freq() %>% pull(count), c(1969, 25, 6)) # 1969 neg, 25 unconfirmed, 6 pos expect_equal(brmo(example_isolates, info = FALSE), mdro(example_isolates, guideline = "BRMO", info = FALSE)) # test Dutch P. aeruginosa MDRO expect_equal( as.character(mdro(data.frame(mo = as.mo("P. aeruginosa"), cfta = "S", cipr = "S", mero = "S", imip = "S", gent = "S", tobr = "S", pita = "S"), guideline = "BRMO", col_mo = "mo", info = FALSE)), "Negative") expect_equal( as.character(mdro(data.frame(mo = as.mo("P. aeruginosa"), cefta = "R", cipr = "R", mero = "R", imip = "R", gent = "R", tobr = "R", pita = "R"), guideline = "BRMO", col_mo = "mo", info = FALSE)), "Positive") # German 3MRGN and 4MRGN expect_equal(as.character(mrgn( data.frame(mo = c("E. coli", "E. coli", "K. pneumoniae", "E. coli", "A. baumannii", "A. baumannii", "A. baumannii", "P. aeruginosa", "P. aeruginosa", "P. aeruginosa"), PIP = c("S", "R", "R", "S", "S", "R", "R", "S", "R", "R"), CTX = c("S", "R", "R", "S", "R", "R", "R", "R", "R", "R"), IPM = c("S", "R", "S", "R", "R", "R", "S", "S", "R", "R"), CIP = c("S", "R", "R", "S", "R", "R", "R", "R", "S", "R"), stringsAsFactors = FALSE))), c("Negative", "4MRGN", "3MRGN", "4MRGN", "4MRGN", "4MRGN", "3MRGN", "Negative", "3MRGN", "4MRGN")) # MDR TB expect_equal( # select only rifampicine, mo will be determined automatically (as M. tuberculosis), # number of mono-resistant strains should be equal to number of rifampicine-resistant strains cleaner::freq(mdr_tb(example_isolates[, "RIF", drop = FALSE]))$count[2], count_R(example_isolates$RIF)) sample_rsi <- function() { sample(c("S", "I", "R"), size = 5000, prob = c(0.5, 0.1, 0.4), replace = TRUE) } x <- data.frame(rifampicin = sample_rsi(), inh = sample_rsi(), gatifloxacin = sample_rsi(), eth = sample_rsi(), pza = sample_rsi(), MFX = sample_rsi(), KAN = sample_rsi()) expect_gt(n_distinct(mdr_tb(x)), 2) # check the guideline by Magiorakos et al. (2012), the default guideline stau <- data.frame(mo = c("S. aureus", "S. aureus", "S. aureus", "S. aureus"), GEN = c("R", "R", "S", "R"), RIF = c("S", "R", "S", "R"), CPT = c("S", "R", "R", "R"), OXA = c("S", "R", "R", "R"), CIP = c("S", "S", "R", "R"), MFX = c("S", "S", "R", "R"), SXT = c("S", "S", "R", "R"), FUS = c("S", "S", "R", "R"), VAN = c("S", "S", "R", "R"), TEC = c("S", "S", "R", "R"), TLV = c("S", "S", "R", "R"), TGC = c("S", "S", "R", "R"), CLI = c("S", "S", "R", "R"), DAP = c("S", "S", "R", "R"), ERY = c("S", "S", "R", "R"), LNZ = c("S", "S", "R", "R"), CHL = c("S", "S", "R", "R"), FOS = c("S", "S", "R", "R"), QDA = c("S", "S", "R", "R"), TCY = c("S", "S", "R", "R"), DOX = c("S", "S", "R", "R"), MNO = c("S", "S", "R", "R"), stringsAsFactors = FALSE) expect_equal(as.integer(mdro(stau)), c(1:4)) expect_s3_class(mdro(stau, verbose = TRUE), "data.frame") ente <- data.frame(mo = c("Enterococcus", "Enterococcus", "Enterococcus", "Enterococcus"), GEH = c("R", "R", "S", "R"), STH = c("S", "R", "S", "R"), IPM = c("S", "R", "R", "R"), MEM = c("S", "R", "R", "R"), DOR = c("S", "S", "R", "R"), CIP = c("S", "S", "R", "R"), LVX = c("S", "S", "R", "R"), MFX = c("S", "S", "R", "R"), VAN = c("S", "S", "R", "R"), TEC = c("S", "S", "R", "R"), TGC = c("S", "S", "R", "R"), DAP = c("S", "S", "R", "R"), LNZ = c("S", "S", "R", "R"), AMP = c("S", "S", "R", "R"), QDA = c("S", "S", "R", "R"), DOX = c("S", "S", "R", "R"), MNO = c("S", "S", "R", "R"), stringsAsFactors = FALSE) expect_equal(as.integer(mdro(ente)), c(1:4)) expect_s3_class(mdro(ente, verbose = TRUE), "data.frame") entero <- data.frame(mo = c("E. coli", "E. coli", "E. coli", "E. coli"), GEN = c("R", "R", "S", "R"), TOB = c("S", "R", "S", "R"), AMK = c("S", "R", "R", "R"), NET = c("S", "R", "R", "R"), CPT = c("S", "R", "R", "R"), TCC = c("S", "R", "R", "R"), TZP = c("S", "S", "R", "R"), ETP = c("S", "S", "R", "R"), IPM = c("S", "S", "R", "R"), MEM = c("S", "S", "R", "R"), DOR = c("S", "S", "R", "R"), CZO = c("S", "S", "R", "R"), CXM = c("S", "S", "R", "R"), CTX = c("S", "S", "R", "R"), CAZ = c("S", "S", "R", "R"), FEP = c("S", "S", "R", "R"), FOX = c("S", "S", "R", "R"), CTT = c("S", "S", "R", "R"), CIP = c("S", "S", "R", "R"), SXT = c("S", "S", "R", "R"), TGC = c("S", "S", "R", "R"), ATM = c("S", "S", "R", "R"), AMP = c("S", "S", "R", "R"), AMC = c("S", "S", "R", "R"), SAM = c("S", "S", "R", "R"), CHL = c("S", "S", "R", "R"), FOS = c("S", "S", "R", "R"), COL = c("S", "S", "R", "R"), TCY = c("S", "S", "R", "R"), DOX = c("S", "S", "R", "R"), MNO = c("S", "S", "R", "R"), stringsAsFactors = FALSE) expect_equal(as.integer(mdro(entero)), c(1:4)) expect_s3_class(mdro(entero, verbose = TRUE), "data.frame") pseud <- data.frame(mo = c("P. aeruginosa", "P. aeruginosa", "P. aeruginosa", "P. aeruginosa"), GEN = c("R", "R", "S", "R"), TOB = c("S", "S", "S", "R"), AMK = c("S", "S", "R", "R"), NET = c("S", "S", "R", "R"), IPM = c("S", "R", "R", "R"), MEM = c("S", "S", "R", "R"), DOR = c("S", "S", "R", "R"), CAZ = c("S", "S", "R", "R"), FEP = c("S", "R", "R", "R"), CIP = c("S", "S", "R", "R"), LVX = c("S", "S", "R", "R"), TCC = c("S", "S", "R", "R"), TZP = c("S", "S", "R", "R"), ATM = c("S", "S", "R", "R"), FOS = c("S", "S", "R", "R"), COL = c("S", "S", "R", "R"), PLB = c("S", "S", "R", "R"), stringsAsFactors = FALSE) expect_equal(as.integer(mdro(pseud)), c(1:4)) expect_s3_class(mdro(pseud, verbose = TRUE), "data.frame") acin <- data.frame(mo = c("A. baumannii", "A. baumannii", "A. baumannii", "A. baumannii"), GEN = c("R", "R", "S", "R"), TOB = c("S", "R", "S", "R"), AMK = c("S", "R", "R", "R"), NET = c("S", "R", "R", "R"), IPM = c("S", "S", "R", "R"), MEM = c("S", "R", "R", "R"), DOR = c("S", "S", "R", "R"), CIP = c("S", "S", "R", "R"), LVX = c("S", "S", "R", "R"), TZP = c("S", "S", "R", "R"), TCC = c("S", "S", "R", "R"), CTX = c("S", "S", "R", "R"), CRO = c("S", "S", "R", "R"), CAZ = c("S", "S", "R", "R"), FEP = c("S", "R", "R", "R"), SXT = c("S", "S", "R", "R"), SAM = c("S", "S", "R", "R"), COL = c("S", "S", "R", "R"), PLB = c("S", "S", "R", "R"), TCY = c("S", "S", "R", "R"), DOX = c("S", "S", "R", "R"), MNO = c("S", "S", "R", "R"), stringsAsFactors = FALSE) expect_equal(as.integer(mdro(acin)), c(1:4)) expect_s3_class(mdro(acin, verbose = TRUE), "data.frame") })