- For functions first_isolate, EUCAST_rules the antibiotic column names are case-insensitive

- Functions `first_isolate`, `EUCAST_rules` and `rsi_predict` supports tidyverse-like evaluation of parameters (no need to quote columns them anymore)
- Functions `clipboard_import` and `clipboard_export` as helper functions to quickly copy and paste from/to software like Excel and SPSS
- Renamed dataset `bactlist` to `microorganisms`

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
 Version: 0.1.2
-Date: 2018-03-19
+Date: 2018-03-23
 Title: Antimicrobial Resistance Analysis
 Authors@R: c(
     person(
@@ -25,8 +25,8 @@ Description: Functions to simplify the analysis of Antimicrobial Resistance (AMR
     on antibiograms according to Leclercq (2013)
     <doi:10.1111/j.1469-0691.2011.03703.x>.
 Depends: R (>= 3.0)
-Imports: dplyr (>= 0.7.0), reshape2 (>= 1.4.0), xml2, rvest
+Imports: dplyr (>= 0.7.0), knitr, reshape2 (>= 1.4.0), xml2, rvest
-URL: https://github.com/msberends/AMR
+URL: https://cran.r-project.org/package=AMR
 BugReports: https://github.com/msberends/AMR/issues
 License: GPL-2 | file LICENSE
 Encoding: UTF-8

NAMESPACE

@@ -13,25 +13,27 @@ S3method(summary,mic)
 S3method(summary,rsi)
 export(EUCAST_rules)
 export(abname)
-export(anti_join_bactlist)
+export(anti_join_microorganisms)
 export(as.mic)
 export(as.rsi)
 export(atc_property)
+export(clipboard_export)
+export(clipboard_import)
 export(first_isolate)
-export(full_join_bactlist)
+export(full_join_microorganisms)
 export(guess_bactid)
-export(inner_join_bactlist)
+export(inner_join_microorganisms)
 export(interpretive_reading)
 export(is.mic)
 export(is.rsi)
 export(key_antibiotics)
-export(left_join_bactlist)
+export(left_join_microorganisms)
 export(mo_property)
-export(right_join_bactlist)
+export(right_join_microorganisms)
 export(rsi)
 export(rsi_df)
 export(rsi_predict)
-export(semi_join_bactlist)
+export(semi_join_microorganisms)
 exportMethods(as.double.mic)
 exportMethods(as.integer.mic)
 exportMethods(as.numeric.mic)
@@ -48,6 +50,7 @@ importFrom(dplyr,all_vars)
 importFrom(dplyr,any_vars)
 importFrom(dplyr,arrange)
 importFrom(dplyr,arrange_at)
+importFrom(dplyr,as_tibble)
 importFrom(dplyr,between)
 importFrom(dplyr,filter)
 importFrom(dplyr,filter_at)
@@ -73,5 +76,9 @@ importFrom(graphics,text)
 importFrom(reshape2,dcast)
 importFrom(rvest,html_nodes)
 importFrom(rvest,html_table)
+importFrom(utils,object.size)
 importFrom(utils,packageDescription)
+importFrom(utils,read.delim)
+importFrom(utils,write.table)
+importFrom(utils,writeClipboard)
 importFrom(xml2,read_html)

NEWS

@@ -1,11 +1,14 @@
 ## 0.1.2
-- Added new function `guess_bactid` to determine the ID of a microorganism based on genus/species
+- NEW: Function `guess_bactid` to determine the ID of a microorganism based on genus/species
-- Renamed `ablist` to `antibiotics`
+- NEW: Functions `clipboard_import` and `clipboard_export` as helper functions to quickly copy and paste from/to software like Excel and SPSS
-- Added support for character vector in join functions
+- NEW: New algorithm to determine weighted isolates, can now be `"points"` or `"keyantibiotics"`, see `?first_isolate`
-- Altered `%like%` to make it case insensitive
+- EDIT: Renamed dataset `ablist` to `antibiotics`
-- Added new algorithm to determine weighted isolates, can now be `points` or `keyantibiotics, see `?first_isolate`
+- EDIT: Renamed dataset `bactlist` to `microorganisms`
-- Function `first_isolate` supports tidyverse-like evaluation of parameters (no need to quote them anymore)
+- EDIT: Added support for character vector in join functions
-- Functions `as.rsi` and `as.mic` now add the package name and version as attribute
+- EDIT: Altered `%like%` to make it case insensitive
+- EDIT: Functions `first_isolate`, `EUCAST_rules` and `rsi_predict` supports tidyverse-like evaluation of parameters (no need to quote columns them anymore)
+- EDIT: For functions `first_isolate`, `EUCAST_rules` the antibiotic column names are case-insensitive
+- EDIT: Functions `as.rsi` and `as.mic` now add the package name and version as attribute
 
 ## 0.1.1
 - `EUCAST_rules` applies for amoxicillin even if ampicillin is missing

R/EUCAST.R

@@ -20,7 +20,7 @@
 #'
 #' Apply expert rules (like intrinsic resistance), as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{http://eucast.org}), see \emph{Source}.
 #' @param tbl table with antibiotic columns, like e.g. \code{amox} and \code{amcl}
-#' @param col_bactcode column name of the bacteria ID in \code{tbl} - values of this column should be present in \code{bactlist$bactid}, see \code{\link{bactlist}}
+#' @param col_bactid column name of the bacteria ID in \code{tbl} - values of this column should be present in \code{microorganisms$bactid}, see \code{\link{microorganisms}}
 #' @param info print progress
 #' @param amcl,amik,amox,ampi,azit,aztr,cefa,cfra,cfep,cfot,cfox,cfta,cftr,cfur,chlo,cipr,clar,clin,clox,coli,czol,dapt,doxy,erta,eryt,fosf,fusi,gent,imip,kana,levo,linc,line,mero,mino,moxi,nali,neom,neti,nitr,novo,norf,oflo,peni,pita,poly,qida,rifa,roxi,siso,teic,tetr,tica,tige,tobr,trim,trsu,vanc column names of antibiotics. Use \code{NA} to skip a column, like \code{tica = NA}. Non-existing column will be skipped.
 #' @param ... parameters that are passed on to \code{EUCAST_rules}
@@ -33,8 +33,8 @@
 #'   Leclercq et al. \strong{EUCAST expert rules in antimicrobial susceptibility testing.} \emph{Clin Microbiol Infect.} 2013;19(2):141-60. \cr
 #'   \url{https://doi.org/10.1111/j.1469-0691.2011.03703.x} \cr
 #'   \cr
-#'   EUCAST Expert Rules Version 3.1: \cr
+#'   EUCAST Expert Rules Version 3.1 (Intrinsic Resistance and Exceptional Phenotypes Tables): \cr
-#'   \url{http://www.eucast.org/expert_rules_and_intrinsic_resistance}
+#'   \url{http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf}
 #' @examples
 #' a <- data.frame(bactid = c("STAAUR",  # Staphylococcus aureus
 #'                            "ENCFAE",  # Enterococcus faecalis
@@ -52,7 +52,7 @@
 #' b <- EUCAST_rules(a)
 #' b
 EUCAST_rules <- function(tbl,
-                         col_bactcode = 'bactid',
+                         col_bactid = 'bactid',
                          info = TRUE,
                          amcl = 'amcl',
                          amik = 'amik',
@@ -112,95 +112,168 @@ EUCAST_rules <- function(tbl,
                          trim = 'trim',
                          trsu = 'trsu',
                          vanc = 'vanc') {
+
+  EUCAST_VERSION <- "3.1"
   
-  if (!col_bactcode %in% colnames(tbl)) {
+  # support using columns as objects; the tidyverse way
-    stop('Column ', col_bactcode, ' not found.')
+  amcl <- quasiquotate(deparse(substitute(amcl)), amcl)
+  amik <- quasiquotate(deparse(substitute(amik)), amik)
+  amox <- quasiquotate(deparse(substitute(amox)), amox)
+  ampi <- quasiquotate(deparse(substitute(ampi)), ampi)
+  azit <- quasiquotate(deparse(substitute(azit)), azit)
+  aztr <- quasiquotate(deparse(substitute(aztr)), aztr)
+  cefa <- quasiquotate(deparse(substitute(cefa)), cefa)
+  cfra <- quasiquotate(deparse(substitute(cfra)), cfra)
+  cfep <- quasiquotate(deparse(substitute(cfep)), cfep)
+  cfot <- quasiquotate(deparse(substitute(cfot)), cfot)
+  cfox <- quasiquotate(deparse(substitute(cfox)), cfox)
+  cfta <- quasiquotate(deparse(substitute(cfta)), cfta)
+  cftr <- quasiquotate(deparse(substitute(cftr)), cftr)
+  cfur <- quasiquotate(deparse(substitute(cfur)), cfur)
+  chlo <- quasiquotate(deparse(substitute(chlo)), chlo)
+  cipr <- quasiquotate(deparse(substitute(cipr)), cipr)
+  clar <- quasiquotate(deparse(substitute(clar)), clar)
+  clin <- quasiquotate(deparse(substitute(clin)), clin)
+  clox <- quasiquotate(deparse(substitute(clox)), clox)
+  coli <- quasiquotate(deparse(substitute(coli)), coli)
+  czol <- quasiquotate(deparse(substitute(czol)), czol)
+  dapt <- quasiquotate(deparse(substitute(dapt)), dapt)
+  doxy <- quasiquotate(deparse(substitute(doxy)), doxy)
+  erta <- quasiquotate(deparse(substitute(erta)), erta)
+  eryt <- quasiquotate(deparse(substitute(eryt)), eryt)
+  fosf <- quasiquotate(deparse(substitute(fosf)), fosf)
+  fusi <- quasiquotate(deparse(substitute(fusi)), fusi)
+  gent <- quasiquotate(deparse(substitute(gent)), gent)
+  imip <- quasiquotate(deparse(substitute(imip)), imip)
+  kana <- quasiquotate(deparse(substitute(kana)), kana)
+  levo <- quasiquotate(deparse(substitute(levo)), levo)
+  linc <- quasiquotate(deparse(substitute(linc)), linc)
+  line <- quasiquotate(deparse(substitute(line)), line)
+  mero <- quasiquotate(deparse(substitute(mero)), mero)
+  mino <- quasiquotate(deparse(substitute(mino)), mino)
+  moxi <- quasiquotate(deparse(substitute(moxi)), moxi)
+  nali <- quasiquotate(deparse(substitute(nali)), nali)
+  neom <- quasiquotate(deparse(substitute(neom)), neom)
+  neti <- quasiquotate(deparse(substitute(neti)), neti)
+  nitr <- quasiquotate(deparse(substitute(nitr)), nitr)
+  novo <- quasiquotate(deparse(substitute(novo)), novo)
+  norf <- quasiquotate(deparse(substitute(norf)), norf)
+  oflo <- quasiquotate(deparse(substitute(oflo)), oflo)
+  peni <- quasiquotate(deparse(substitute(peni)), peni)
+  pita <- quasiquotate(deparse(substitute(pita)), pita)
+  poly <- quasiquotate(deparse(substitute(poly)), poly)
+  qida <- quasiquotate(deparse(substitute(qida)), qida)
+  rifa <- quasiquotate(deparse(substitute(rifa)), rifa)
+  roxi <- quasiquotate(deparse(substitute(roxi)), roxi)
+  siso <- quasiquotate(deparse(substitute(siso)), siso)
+  teic <- quasiquotate(deparse(substitute(teic)), teic)
+  tetr <- quasiquotate(deparse(substitute(tetr)), tetr)
+  tica <- quasiquotate(deparse(substitute(tica)), tica)
+  tige <- quasiquotate(deparse(substitute(tige)), tige)
+  tobr <- quasiquotate(deparse(substitute(tobr)), tobr)
+  trim <- quasiquotate(deparse(substitute(trim)), trim)
+  trsu <- quasiquotate(deparse(substitute(trsu)), trsu)
+  vanc <- quasiquotate(deparse(substitute(vanc)), vanc)
+
+  if (!col_bactid %in% colnames(tbl)) {
+    stop('Column ', col_bactid, ' not found.')
   }
   
-  # kolommen controleren
+  # check columns
-  col.list <- c(amcl, amik, amox, ampi, azit, aztr, cefa, cfra, cfep,
+  col.list <- c(amcl, amik, amox, ampi, azit, aztr, cefa, cfra, cfep, cfot,
-                cfot, cfox, cfta, cftr, cfur, cipr, clar, clin, clox, coli, czol,
+                cfox, cfta, cftr, cfur, chlo, cipr, clar, clin, clox, coli,
-                dapt, doxy, erta, eryt, fusi, gent, imip, kana, levo, linc, line,
+                czol, dapt, doxy, erta, eryt, fosf, fusi, gent, imip, kana,
-                mero, mino, moxi, nali, neom, neti, nitr, novo, norf, oflo, peni,
+                levo, linc, line, mero, mino, moxi, nali, neom, neti, nitr,
-                pita, poly, qida, rifa, roxi, siso, teic, tetr, tica, tige, tobr,
+                novo, norf, oflo, peni, pita, poly, qida, rifa, roxi, siso,
-                trim, trsu, vanc)
+                teic, tetr, tica, tige, tobr, trim, trsu, vanc)
   col.list <- col.list[!is.na(col.list)]
+  col.list.bak <- col.list
+  # are they available as upper case then?
+  for (i in 1:length(col.list)) {
+    if (toupper(col.list[i]) %in% colnames(tbl)) {
+      col.list[i] <- toupper(col.list[i])
+    } else if (tolower(col.list[i]) %in% colnames(tbl)) {
+      col.list[i] <- tolower(col.list[i])
+    } else if (!col.list[i] %in% colnames(tbl)) {
+      col.list[i] <- NA
+    }
+  }
   if (!all(col.list %in% colnames(tbl))) {
     if (info == TRUE) {
       cat('\n')
     }
     if (info == TRUE) {
-      warning('These columns do not exist and will be ignored:\n',
+      warning('These columns do not exist and will be ignored: ',
-              col.list[!(col.list %in% colnames(tbl))] %>% toString(),
+              col.list.bak[!(col.list %in% colnames(tbl))] %>% toString(),
               immediate. = TRUE,
               call. = FALSE)
     }
-    if (!amcl %in% colnames(tbl)) { amcl <- NA }
-    if (!amik %in% colnames(tbl)) { amik <- NA }
-    if (!amox %in% colnames(tbl)) { amox <- NA }
-    if (!ampi %in% colnames(tbl)) { ampi <- NA }
-    if (!azit %in% colnames(tbl)) { azit <- NA }
-    if (!aztr %in% colnames(tbl)) { aztr <- NA }
-    if (!cefa %in% colnames(tbl)) { cefa <- NA }
-    if (!cfra %in% colnames(tbl)) { cfra <- NA }
-    if (!cfep %in% colnames(tbl)) { cfep <- NA }
-    if (!cfot %in% colnames(tbl)) { cfot <- NA }
-    if (!cfox %in% colnames(tbl)) { cfox <- NA }
-    if (!cfta %in% colnames(tbl)) { cfta <- NA }
-    if (!cftr %in% colnames(tbl)) { cftr <- NA }
-    if (!cfur %in% colnames(tbl)) { cfur <- NA }
-    if (!chlo %in% colnames(tbl)) { chlo <- NA }
-    if (!cipr %in% colnames(tbl)) { cipr <- NA }
-    if (!clar %in% colnames(tbl)) { clar <- NA }
-    if (!clin %in% colnames(tbl)) { clin <- NA }
-    if (!clox %in% colnames(tbl)) { clox <- NA }
-    if (!coli %in% colnames(tbl)) { coli <- NA }
-    if (!czol %in% colnames(tbl)) { czol <- NA }
-    if (!dapt %in% colnames(tbl)) { dapt <- NA }
-    if (!doxy %in% colnames(tbl)) { doxy <- NA }
-    if (!erta %in% colnames(tbl)) { erta <- NA }
-    if (!eryt %in% colnames(tbl)) { eryt <- NA }
-    if (!fosf %in% colnames(tbl)) { fosf <- NA }
-    if (!fusi %in% colnames(tbl)) { fusi <- NA }
-    if (!gent %in% colnames(tbl)) { gent <- NA }
-    if (!imip %in% colnames(tbl)) { imip <- NA }
-    if (!kana %in% colnames(tbl)) { kana <- NA }
-    if (!levo %in% colnames(tbl)) { levo <- NA }
-    if (!linc %in% colnames(tbl)) { linc <- NA }
-    if (!line %in% colnames(tbl)) { line <- NA }
-    if (!mero %in% colnames(tbl)) { mero <- NA }
-    if (!mino %in% colnames(tbl)) { mino <- NA }
-    if (!moxi %in% colnames(tbl)) { moxi <- NA }
-    if (!nali %in% colnames(tbl)) { nali <- NA }
-    if (!neom %in% colnames(tbl)) { neom <- NA }
-    if (!neti %in% colnames(tbl)) { neti <- NA }
-    if (!nitr %in% colnames(tbl)) { nitr <- NA }
-    if (!novo %in% colnames(tbl)) { novo <- NA }
-    if (!norf %in% colnames(tbl)) { norf <- NA }
-    if (!oflo %in% colnames(tbl)) { oflo <- NA }
-    if (!peni %in% colnames(tbl)) { peni <- NA }
-    if (!pita %in% colnames(tbl)) { pita <- NA }
-    if (!poly %in% colnames(tbl)) { poly <- NA }
-    if (!qida %in% colnames(tbl)) { qida <- NA }
-    if (!rifa %in% colnames(tbl)) { rifa <- NA }
-    if (!roxi %in% colnames(tbl)) { roxi <- NA }
-    if (!siso %in% colnames(tbl)) { siso <- NA }
-    if (!teic %in% colnames(tbl)) { teic <- NA }
-    if (!tetr %in% colnames(tbl)) { tetr <- NA }
-    if (!tica %in% colnames(tbl)) { tica <- NA }
-    if (!tige %in% colnames(tbl)) { tige <- NA }
-    if (!tobr %in% colnames(tbl)) { tobr <- NA }
-    if (!trim %in% colnames(tbl)) { trim <- NA }
-    if (!trsu %in% colnames(tbl)) { trsu <- NA }
-    if (!vanc %in% colnames(tbl)) { vanc <- NA }
   }
   
+  amcl <- col.list[1]
+  amik <- col.list[2]
+  amox <- col.list[3]
+  ampi <- col.list[4]
+  azit <- col.list[5]
+  aztr <- col.list[6]
+  cefa <- col.list[7]
+  cfra <- col.list[8]
+  cfep <- col.list[9]
+  cfot <- col.list[10]
+  cfox <- col.list[11]
+  cfta <- col.list[12]
+  cftr <- col.list[13]
+  cfur <- col.list[14]
+  chlo <- col.list[15]
+  cipr <- col.list[16]
+  clar <- col.list[17]
+  clin <- col.list[18]
+  clox <- col.list[19]
+  coli <- col.list[20]
+  czol <- col.list[21]
+  dapt <- col.list[22]
+  doxy <- col.list[23]
+  erta <- col.list[24]
+  eryt <- col.list[25]
+  fosf <- col.list[26]
+  fusi <- col.list[27]
+  gent <- col.list[28]
+  imip <- col.list[29]
+  kana <- col.list[30]
+  levo <- col.list[31]
+  linc <- col.list[32]
+  line <- col.list[33]
+  mero <- col.list[34]
+  mino <- col.list[35]
+  moxi <- col.list[36]
+  nali <- col.list[37]
+  neom <- col.list[38]
+  neti <- col.list[39]
+  nitr <- col.list[40]
+  novo <- col.list[41]
+  norf <- col.list[42]
+  oflo <- col.list[43]
+  peni <- col.list[44]
+  pita <- col.list[45]
+  poly <- col.list[46]
+  qida <- col.list[47]
+  rifa <- col.list[48]
+  roxi <- col.list[49]
+  siso <- col.list[50]
+  teic <- col.list[51]
+  tetr <- col.list[52]
+  tica <- col.list[53]
+  tige <- col.list[54]
+  tobr <- col.list[55]
+  trim <- col.list[56]
+  trsu <- col.list[57]
+  vanc <- col.list[58]
+  
   total <- 0
   total_rows <- integer(0)
   
-  # functie voor uitvoeren
+  # helper function for editing the table
   edit_rsi <- function(to, rows, cols) {
-    #voortgang$tick()$print()
     cols <- cols[!is.na(cols)]
     if (length(rows) > 0 & length(cols) > 0) {
       tbl[rows, cols] <<- to
@@ -209,97 +282,99 @@ EUCAST_rules <- function(tbl,
     }
   }
   
-  # bactlist aan vastknopen (bestaande kolommen krijgen extra suffix)
+  # join to microorganisms table
-  joinby <- colnames(AMR::bactlist)[1]
+  joinby <- colnames(AMR::microorganisms)[1]
-  names(joinby) <- col_bactcode
+  names(joinby) <- col_bactid
-  tbl <- tbl %>% left_join(y = AMR::bactlist, by = joinby, suffix = c("_tempbactlist", ""))
+  tbl <- tbl %>% left_join(y = AMR::microorganisms, by = joinby, suffix = c("_tempmicroorganisms", ""))
   
-  # antibioticagroepen
+  # antibiotic classes
-  aminoglycosiden <- c(tobr, gent, kana, neom, neti, siso)
+  aminoglycosides <- c(tobr, gent, kana, neom, neti, siso)
-  tetracyclines <- c(doxy, mino, tetr) # sinds EUCAST v3.1 is tige(cycline) apart
+  tetracyclines <- c(doxy, mino, tetr) # since EUCAST v3.1 tige(cycline) is set apart
-  polymyxines <- c(poly, coli)
+  polymyxins <- c(poly, coli)
-  macroliden <- c(eryt, azit, roxi, clar) # sinds EUCAST v3.1 is clinda apart
+  macrolides <- c(eryt, azit, roxi, clar) # since EUCAST v3.1 clinda is set apart
-  glycopeptiden <- c(vanc, teic)
+  glycopeptides <- c(vanc, teic)
-  streptogramines <- qida # eigenlijk pristinamycine en quinupristine/dalfopristine
+  streptogramins <- qida # should officially also be pristinamycin and quinupristin/dalfopristin
-  cefalosporines <- c(cfep, cfot, cfox, cfra, cfta, cftr, cfur, czol)
+  cephalosporins <- c(cfep, cfot, cfox, cfra, cfta, cftr, cfur, czol)
   carbapenems <- c(erta, imip, mero)
-  aminopenicillines <- c(ampi, amox)
+  aminopenicillins <- c(ampi, amox)
-  ureidopenicillines <- pita # eigenlijk ook azlo en mezlo
+  ureidopenicillins <- pita # should officially also be azlo and mezlo
-  fluorochinolonen <- c(oflo, cipr, norf, levo, moxi)
+  fluoroquinolones <- c(oflo, cipr, norf, levo, moxi)
   
   if (info == TRUE) {
-    cat('\nApplying rules to',
+    cat(
+      paste0(
+        '\nApplying rules to ',
         tbl[!is.na(tbl$genus),] %>% nrow() %>% format(big.mark = ","),
-        'rows according to "EUCAST Expert Rules Version 3.1"\n\n')
+        ' rows according to "EUCAST Expert Rules Version ', EUCAST_VERSION, '"\n')
+    )
   }
   
   # Table 1: Intrinsic resistance in Enterobacteriaceae ----
   if (info == TRUE) {
     cat('...Table 1: Intrinsic resistance in Enterobacteriaceae\n')
   }
-  #voortgang <- progress_estimated(17)
+  # Intrisiek R for this group
-  # Intrisiek R voor groep
   edit_rsi(to = 'R',
            rows = which(tbl$family == 'Enterobacteriaceae'),
-           cols = c(peni, glycopeptiden, fusi, macroliden, linc, streptogramines, rifa, dapt, line))
+           cols = c(peni, glycopeptides, fusi, macrolides, linc, streptogramins, rifa, dapt, line))
   # Citrobacter
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Citrobacter (koseri|amalonaticus|sedlakii|farmeri|rodentium)'),
-           cols = c(aminopenicillines, tica))
+           cols = c(aminopenicillins, tica))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Citrobacter (freundii|braakii|murliniae|werkmanii|youngae)'),
-           cols = c(aminopenicillines, amcl, czol, cfox))
+           cols = c(aminopenicillins, amcl, czol, cfox))
   # Enterobacter
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Enterobacter cloacae'),
-           cols = c(aminopenicillines, amcl, czol, cfox))
+           cols = c(aminopenicillins, amcl, czol, cfox))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Enterobacter aerogenes'),
-           cols = c(aminopenicillines, amcl, czol, cfox))
+           cols = c(aminopenicillins, amcl, czol, cfox))
   # Escherichia
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Escherichia hermanni'),
-           cols = c(aminopenicillines, tica))
+           cols = c(aminopenicillins, tica))
   # Hafnia
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Hafnia alvei'),
-           cols = c(aminopenicillines, amcl, czol, cfox))
+           cols = c(aminopenicillins, amcl, czol, cfox))
   # Klebsiella
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Klebsiella'),
-           cols = c(aminopenicillines, tica))
+           cols = c(aminopenicillins, tica))
   # Morganella / Proteus
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Morganella morganii'),
-           cols = c(aminopenicillines, amcl, czol, tetracyclines, polymyxines, nitr))
+           cols = c(aminopenicillins, amcl, czol, tetracyclines, polymyxins, nitr))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Proteus mirabilis'),
-           cols = c(tetracyclines, tige, polymyxines, nitr))
+           cols = c(tetracyclines, tige, polymyxins, nitr))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Proteus penneri'),
-           cols = c(aminopenicillines, czol, cfur, tetracyclines, tige, polymyxines, nitr))
+           cols = c(aminopenicillins, czol, cfur, tetracyclines, tige, polymyxins, nitr))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Proteus vulgaris'),
-           cols = c(aminopenicillines, czol, cfur, tetracyclines, tige, polymyxines, nitr))
+           cols = c(aminopenicillins, czol, cfur, tetracyclines, tige, polymyxins, nitr))
   # Providencia
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Providencia rettgeri'),
-           cols = c(aminopenicillines, amcl, czol, cfur, tetracyclines, tige, polymyxines, nitr))
+           cols = c(aminopenicillins, amcl, czol, cfur, tetracyclines, tige, polymyxins, nitr))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Providencia stuartii'),
-           cols = c(aminopenicillines, amcl, czol, cfur, tetracyclines, tige, polymyxines, nitr))
+           cols = c(aminopenicillins, amcl, czol, cfur, tetracyclines, tige, polymyxins, nitr))
   # Raoultella
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Raoultella'),
-           cols = c(aminopenicillines, tica))
+           cols = c(aminopenicillins, tica))
   # Serratia
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Serratia marcescens'),
-           cols = c(aminopenicillines, amcl, czol, cfox, cfur, tetracyclines[tetracyclines != 'mino'], polymyxines, nitr))
+           cols = c(aminopenicillins, amcl, czol, cfox, cfur, tetracyclines[tetracyclines != 'mino'], polymyxins, nitr))
   # Yersinia
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Yersinia enterocolitica'),
-           cols = c(aminopenicillines, amcl, tica, czol, cfox))
+           cols = c(aminopenicillins, amcl, tica, czol, cfox))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Yersinia pseudotuberculosis'),
            cols = c(poly, coli))
@@ -309,8 +384,7 @@ EUCAST_rules <- function(tbl,
   if (info == TRUE) {
     cat('...Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria\n')
   }
-  #voortgang <- progress_estimated(8)
+  # Intrisiek R for this group
-  # Intrisiek R voor groep
   edit_rsi(to = 'R',
            rows = which(tbl$genus %in% c('Achromobacter',
                                          'Acinetobacter',
@@ -322,54 +396,53 @@ EUCAST_rules <- function(tbl,
                                          'Ochrobactrum',
                                          'Pseudomonas',
                                          'Stenotrophomonas')),
-           cols = c(peni, cfox, cfur, glycopeptiden, fusi, macroliden, linc, streptogramines, rifa, dapt, line))
+           cols = c(peni, cfox, cfur, glycopeptides, fusi, macrolides, linc, streptogramins, rifa, dapt, line))
   # Acinetobacter
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Acinetobacter (baumannii|pittii|nosocomialis|calcoaceticus)'),
-           cols = c(aminopenicillines, amcl, czol, cfot, cftr, aztr, erta, trim, fosf, tetracyclines[tetracyclines != 'mino']))
+           cols = c(aminopenicillins, amcl, czol, cfot, cftr, aztr, erta, trim, fosf, tetracyclines[tetracyclines != 'mino']))
   # Achromobacter
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Achromobacter (xylosoxydans|xylosoxidans)'),
-           cols = c(aminopenicillines, czol, cfot, cftr, erta))
+           cols = c(aminopenicillins, czol, cfot, cftr, erta))
   # Burkholderia
   edit_rsi(to = 'R',
            # onder 'Burkholderia cepacia complex' vallen deze species allemaal: PMID 16217180.
            rows = which(tbl$fullname %like% '^Burkholderia (cepacia|multivorans|cenocepacia|stabilis|vietnamiensis|dolosa|ambifaria|anthina|pyrrocinia|ubonensis)'),
-           cols = c(aminopenicillines, amcl, tica, pita, czol, cfot, cftr, aztr, erta, cipr, chlo, aminoglycosiden, trim, fosf, polymyxines))
+           cols = c(aminopenicillins, amcl, tica, pita, czol, cfot, cftr, aztr, erta, cipr, chlo, aminoglycosides, trim, fosf, polymyxins))
   # Elizabethkingia
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Elizabethkingia meningoseptic(a|um)'),
-           cols = c(aminopenicillines, amcl, tica, czol, cfot, cftr, cfta, cfep, aztr, erta, imip, mero, polymyxines))
+           cols = c(aminopenicillins, amcl, tica, czol, cfot, cftr, cfta, cfep, aztr, erta, imip, mero, polymyxins))
   # Ochrobactrum
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Ochrobactrum anthropi'),
-           cols = c(aminopenicillines, amcl, tica, pita, czol, cfot, cftr, cfta, cfep, aztr, erta))
+           cols = c(aminopenicillins, amcl, tica, pita, czol, cfot, cftr, cfta, cfep, aztr, erta))
   # Pseudomonas
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Pseudomonas aeruginosa'),
-           cols = c(aminopenicillines, amcl, czol, cfot, cftr, erta, chlo, kana, neom, trim, trsu, tetracyclines, tige))
+           cols = c(aminopenicillins, amcl, czol, cfot, cftr, erta, chlo, kana, neom, trim, trsu, tetracyclines, tige))
   # Stenotrophomonas
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Stenotrophomonas maltophilia'),
-           cols = c(aminopenicillines, amcl, tica, pita, czol, cfot, cftr, cfta, aztr, erta, imip, mero, aminoglycosiden, trim, fosf, tetr))
+           cols = c(aminopenicillins, amcl, tica, pita, czol, cfot, cftr, cfta, aztr, erta, imip, mero, aminoglycosides, trim, fosf, tetr))
   
   
   # Table 3: Intrinsic resistance in other Gram-negative bacteria ----
   if (info == TRUE) {
     cat('...Table 3: Intrinsic resistance in other Gram-negative bacteria\n')
   }
-  #voortgang <- progress_estimated(7)
+  # Intrisiek R for this group
-  # Intrisiek R voor groep
   edit_rsi(to = 'R',
            rows = which(tbl$genus %in% c('Haemophilus',
                                          'Moraxella',
                                          'Neisseria',
                                          'Campylobacter')),
-           cols = c(glycopeptiden, linc, dapt, line))
+           cols = c(glycopeptides, linc, dapt, line))
   # Haemophilus
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Haemophilus influenzae'),
-           cols = c(fusi, streptogramines))
+           cols = c(fusi, streptogramins))
   # Moraxella
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Moraxella catarrhalis'),
@@ -381,21 +454,20 @@ EUCAST_rules <- function(tbl,
   # Campylobacter
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Campylobacter fetus'),
-           cols = c(fusi, streptogramines, trim, nali))
+           cols = c(fusi, streptogramins, trim, nali))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Campylobacter (jejuni|coli)'),
-           cols = c(fusi, streptogramines, trim))
+           cols = c(fusi, streptogramins, trim))
   
   
   # Table 4: Intrinsic resistance in Gram-positive bacteria ----
   if (info == TRUE) {
     cat('...Table 4: Intrinsic resistance in Gram-positive bacteria\n')
   }
-  #voortgang <- progress_estimated(14)
+  # Intrisiek R for this group
-  # Intrisiek R voor groep
   edit_rsi(to = 'R',
            rows = which(tbl$gramstain %like% 'Positi(e|)(v|f)'),
-           cols = c(aztr, polymyxines, nali))
+           cols = c(aztr, polymyxins, nali))
   # Staphylococcus
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Staphylococcus saprophyticus'),
@@ -412,17 +484,17 @@ EUCAST_rules <- function(tbl,
   # Streptococcus
   edit_rsi(to = 'R',
            rows = which(tbl$genus == 'Streptococcus'),
-           cols = c(fusi, cfta, aminoglycosiden))
+           cols = c(fusi, cfta, aminoglycosides))
   # Enterococcus
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Enterococcus faecalis'),
-           cols = c(fusi, cfta, cefalosporines[cefalosporines != cfta], aminoglycosiden, macroliden, clin, qida, trim, trsu))
+           cols = c(fusi, cfta, cephalosporins[cephalosporins != cfta], aminoglycosides, macrolides, clin, qida, trim, trsu))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Enterococcus (gallinarum|casseliflavus)'),
-           cols = c(fusi, cfta, cefalosporines[cefalosporines != cfta], aminoglycosiden, macroliden, clin, qida, vanc, trim, trsu))
+           cols = c(fusi, cfta, cephalosporins[cephalosporins != cfta], aminoglycosides, macrolides, clin, qida, vanc, trim, trsu))
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Enterococcus faecium'),
-           cols = c(fusi, cfta, cefalosporines[cefalosporines != cfta], aminoglycosiden, macroliden, trim, trsu))
+           cols = c(fusi, cfta, cephalosporins[cephalosporins != cfta], aminoglycosides, macrolides, trim, trsu))
   # Corynebacterium
   edit_rsi(to = 'R',
            rows = which(tbl$genus == 'Corynebacterium'),
@@ -430,7 +502,7 @@ EUCAST_rules <- function(tbl,
   # Listeria
   edit_rsi(to = 'R',
            rows = which(tbl$fullname %like% '^Listeria monocytogenes'),
-           cols = c(cfta, cefalosporines[cefalosporines != cfta]))
+           cols = c(cfta, cephalosporins[cephalosporins != cfta]))
   # overig
   edit_rsi(to = 'R',
            rows = which(tbl$genus %in% c('Leuconostoc', 'Pediococcus')),
@@ -446,34 +518,32 @@ EUCAST_rules <- function(tbl,
   if (info == TRUE) {
     cat('...Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci\n')
   }
-  #voortgang <- progress_estimated(2)
+  # rule 8.3
-  # regel 8.3
   if (!is.na(peni)) {
     edit_rsi(to = 'S',
              rows = which(tbl$fullname %like% '^Streptococcus (pyogenes|agalactiae|dysgalactiae|groep A|groep B|groep C|groep G)'
                           & tbl[, peni] == 'S'),
-             cols = c(aminopenicillines, cefalosporines, carbapenems))
+             cols = c(aminopenicillins, cephalosporins, carbapenems))
   }
-  # regel 8.6
+  # rule 8.6
   if (!is.na(ampi)) {
     edit_rsi(to = 'R',
              rows = which(tbl$genus == 'Enterococcus'
                           & tbl[, ampi] == 'R'),
-             cols = c(ureidopenicillines, carbapenems))
+             cols = c(ureidopenicillins, carbapenems))
   }
   if (!is.na(amox)) {
     edit_rsi(to = 'R',
              rows = which(tbl$genus == 'Enterococcus'
                           & tbl[, amox] == 'R'),
-             cols = c(ureidopenicillines, carbapenems))
+             cols = c(ureidopenicillins, carbapenems))
   }
   
   # Table 9: Interpretive rules for B-lactam agents and Gram-negative rods ----
   if (info == TRUE) {
     cat('...Table 9: Interpretive rules for B-lactam agents and Gram-negative rods\n')
   }
-  #voortgang <- progress_estimated(1)
+  # rule 9.3
-  # regel 9.3
   if (!is.na(tica) & !is.na(pita)) {
     edit_rsi(to = 'R',
              rows = which(tbl$family == 'Enterobacteriaceae'
@@ -486,10 +556,9 @@ EUCAST_rules <- function(tbl,
   if (info == TRUE) {
     cat('...Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria\n')
   }
-  #voortgang <- progress_estimated(1)
+  # rule 10.2
-  # regel 10.2
   if (!is.na(ampi)) {
-    # hiervoor moeten we eerst weten of ze B-lactamase-positief zijn
+    # you should know first if the are B-lactamase positive, so do not run for now
     # edit_rsi(to = 'R',
     #          rows = which(tbl$fullname %like% '^Haemophilus influenza'
     #                       & tbl[, ampi] == 'R'),
@@ -500,7 +569,7 @@ EUCAST_rules <- function(tbl,
   if (info == TRUE) {
     cat('...Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins\n')
   }
-  # regel 11.1
+  # rule 11.1
   if (!is.na(eryt)) {
     if (!is.na(azit)) {
       tbl[, azit] <- tbl[, eryt]
@@ -514,22 +583,21 @@ EUCAST_rules <- function(tbl,
   if (info == TRUE) {
     cat('...Table 12: Interpretive rules for aminoglycosides\n')
   }
-  #voortgang <- progress_estimated(4)
+  # rule 12.2
-  # regel 12.2
   if (!is.na(tobr)) {
     edit_rsi(to = 'R',
              rows = which(tbl$genus == 'Staphylococcus'
                           & tbl[, tobr] == 'R'),
              cols = c(kana, amik))
   }
-  # regel 12.3
+  # rule 12.3
   if (!is.na(gent)) {
     edit_rsi(to = 'R',
              rows = which(tbl$genus == 'Staphylococcus'
                           & tbl[, gent] == 'R'),
-             cols = aminoglycosiden)
+             cols = aminoglycosides)
   }
-  # regel 12.8
+  # rule 12.8
   if (!is.na(gent) & !is.na(tobr)) {
     edit_rsi(to = 'R',
              rows = which(tbl$family == 'Enterobacteriaceae'
@@ -537,7 +605,7 @@ EUCAST_rules <- function(tbl,
                           & tbl[, tobr] == 'S'),
              cols = gent)
   }
-  # regel 12.9
+  # rule 12.9
   if (!is.na(gent) & !is.na(tobr)) {
     edit_rsi(to = 'R',
              rows = which(tbl$family == 'Enterobacteriaceae'
@@ -551,42 +619,40 @@ EUCAST_rules <- function(tbl,
   if (info == TRUE) {
     cat('...Table 13: Interpretive rules for quinolones\n')
   }
-  #voortgang <- progress_estimated(4)
+  # rule 13.2
-  # regel 13.2
   if (!is.na(moxi)) {
     edit_rsi(to = 'R',
              rows = which(tbl$genus == 'Staphylococcus'
                           & tbl[, moxi] == 'R'),
-             cols = fluorochinolonen)
+             cols = fluoroquinolones)
   }
-  # regel 13.4
+  # rule 13.4
   if (!is.na(moxi)) {
     edit_rsi(to = 'R',
              rows = which(tbl$fullname %like% '^Streptococcus pneumoniae'
                           & tbl[, moxi] == 'R'),
-             cols = fluorochinolonen)
+             cols = fluoroquinolones)
   }
-  # regel 13.5
+  # rule 13.5
   if (!is.na(cipr)) {
     edit_rsi(to = 'R',
              rows = which(tbl$family == 'Enterobacteriaceae'
                           & tbl[, cipr] == 'R'),
-             cols = fluorochinolonen)
+             cols = fluoroquinolones)
   }
-  # regel 13.8
+  # rule 13.8
   if (!is.na(cipr)) {
     edit_rsi(to = 'R',
              rows = which(tbl$fullname %like% '^Neisseria gonorrhoeae'
                           & tbl[, cipr] == 'R'),
-             cols = fluorochinolonen)
+             cols = fluoroquinolones)
   }
   
   
   # Other ----
   if (info == TRUE) {
-    cat('...Other\n')
+    cat('...Non-EUCAST: trim = R where trsu = R and ampi = R where amcl = R\n')
   }
-  #voortgang <- progress_estimated(2)
   if (!is.na(amcl)) {
     edit_rsi(to = 'R',
              rows = which(tbl[, amcl] == 'R'),
@@ -601,17 +667,17 @@ EUCAST_rules <- function(tbl,
     tbl[, amox] <- tbl %>% pull(ampi)
   }
   
-  # Toegevoegde kolommen weer verwijderen
+  # Remove added columns again
-  bactlist.ncol <- ncol(AMR::bactlist) - 2
+  microorganisms.ncol <- ncol(AMR::microorganisms) - 2
   tbl.ncol <- ncol(tbl)
-  tbl <- tbl %>% select(-c((tbl.ncol - bactlist.ncol):tbl.ncol))
+  tbl <- tbl %>% select(-c((tbl.ncol - microorganisms.ncol):tbl.ncol))
-  # en eventueel toegevoegde suffix aan bestaande kolommen weer verwijderen
+  # and remove added suffices
-  colnames(tbl) <- gsub("_tempbactlist", "", colnames(tbl))
+  colnames(tbl) <- gsub("_tempmicroorganisms", "", colnames(tbl))
   
   if (info == TRUE) {
-    cat('\nDone.\nEUCAST Expert rules applied to',
+    cat('Done.\n\nEUCAST Expert rules applied to',
         total_rows %>% unique() %>% length() %>% format(big.mark = ","),
-        'different rows, to a total of',
+        'different rows (isolates); edited a total of',
         total %>% format(big.mark = ","), 'test results.\n\n')
   }
   
@@ -626,14 +692,14 @@ interpretive_reading <- function(...) {
 
 #' Poperties of a microorganism
 #'
-#' @param bactcode ID of a microorganisme, like \code{"STAAUR} and \code{"ESCCOL}
+#' @param bactid ID of a microorganisme, like \code{"STAAUR} and \code{"ESCCOL}
 #' @param property One of the values \code{bactid}, \code{bactsys}, \code{family}, \code{genus}, \code{species}, \code{subspecies}, \code{fullname}, \code{type}, \code{gramstain}, \code{aerobic}
 #' @export
 #' @importFrom dplyr %>% filter select
-#' @seealso \code{\link{bactlist}}
+#' @seealso \code{\link{microorganisms}}
-mo_property <- function(bactcode, property = 'fullname') {
+mo_property <- function(bactid, property = 'fullname') {
   
-  mocode <- as.character(bactcode)
+  mocode <- as.character(bactid)
   
   for (i in 1:length(mocode)) {
     bug <- mocode[i]
@@ -641,8 +707,8 @@ mo_property <- function(bactcode, property = 'fullname') {
     if (!is.na(bug)) {
       result = tryCatch({
         mocode[i] <-
-          AMR::bactlist %>%
+          AMR::microorganisms %>%
-          filter(bactid == bactcode) %>%
+          filter(bactid == bactid) %>%
           select(property) %>%
           unlist() %>%
           as.character()

R/atc.R

@@ -129,7 +129,7 @@ atc_property <- function(atc_code,
 #'
 #' Convert antibiotic codes (from a laboratory information system like MOLIS or GLIMS) to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from \code{\link{antibiotics}}.
 #' @param abcode a code or name, like \code{"AMOX"}, \code{"AMCL"} or \code{"J01CA04"}
-#' @param from,to type to transform from and to. See \code{\link{antibiotics}} for its column names.
+#' @param from,to type to transform from and to. See \code{\link{antibiotics}} for its column names. WIth \code{from = "guess"} the from will be guessed from \code{"atc"}, \code{"molis"} and \code{"umcg"}.
 #' @param textbetween text to put between multiple returned texts
 #' @param tolower return output as lower case with function \code{\link{tolower}}.
 #' @keywords ab antibiotics
@@ -154,9 +154,22 @@ atc_property <- function(atc_code,
 #'
 #' abname("J01CR02", from = "atc", to = "umcg")
 #' # "AMCL"
-abname <- function(abcode, from = 'umcg', to = 'official', textbetween = ' + ', tolower = FALSE) {
+abname <- function(abcode, from = c("guess", "atc", "molis", "umcg"), to = 'official', textbetween = ' + ', tolower = FALSE) {
   
   antibiotics <- AMR::antibiotics
+  
+  from <- from[1]
+  if (from == "guess") {
+    for (i in 1:3) {
+      if (abcode[1] %in% (antibiotics %>% pull(i))) {
+        from <- colnames(antibiotics)[i]
+      }
+    }
+    if (from == "guess") {
+      from <- "umcg"
+    }
+  }
+  
   colnames(antibiotics) <- colnames(antibiotics) %>% tolower()
   from <- from %>% tolower()
   to <- to %>% tolower()
@@ -172,8 +185,8 @@ abname <- function(abcode, from = 'umcg', to = 'official', textbetween = ' + ',
   for (i in 1:length(abcode)) {
     drug <- abcode[i]
     if (!grepl('+', drug, fixed = TRUE) & !grepl(' en ', drug, fixed = TRUE)) {
-      # bestaat maar uit 1 middel
+      # only 1 drug
-      if (any(antibiotics[, from] == drug)) {
+      if (drug %in% (antibiotics %>% pull(from))) {
         abcode[i] <-
           antibiotics %>%
           filter(.[, from] == drug) %>%
@@ -181,12 +194,12 @@ abname <- function(abcode, from = 'umcg', to = 'official', textbetween = ' + ',
           slice(1) %>%
           as.character()
       } else {
-        # niet gevonden
+        # not found
         warning('Code "', drug, '" not found in antibiotics list.', call. = FALSE)
         abcode[i] <- NA
       }
     } else {
-      # meerdere middelen
+      # more than 1 drug
       if (grepl('+', drug, fixed = TRUE)) {
         drug.group <-
           strsplit(drug, '+', fixed = TRUE) %>%

R/clipboard.R

@@ -0,0 +1,84 @@
+#' Import/export from clipboard
+#'
+#' These are helper functions around \code{\link{read.table}} and \code{\link{write.table}} to import from and export to clipboard. The data will be read and written as tab-separated by default, which makes it possible to copy and paste from other software like Excel and SPSS without further transformation.
+#' @rdname clipboard
+#' @name clipboard
+#' @inheritParams utils::read.table
+#' @inheritParams utils::write.table
+#' @param startrow \emph{n}th row to start importing from. For \code{clipboard_import}, when \code{header = TRUE} the import will start on row \code{startrow} \emph{below} the header.
+#' @param as_vector a logical value indicating whether data consisting of only one column should be imported as vector using \code{\link[dplyr]{pull}}. This will strip off the header.
+#' @keywords clipboard clipboard_import clipboard_export import export
+#' @importFrom dplyr %>% pull as_tibble
+#' @importFrom utils read.delim write.table object.size writeClipboard
+#' @details For \code{clipboard_export}, the reserved clipboard size for exporting will be set automatically to 125\% of the object size of \code{x}. This way, it is possible to export data with thousands of rows as the only limit will be your systems RAM.
+#' @export
+#' @return data.frame
+clipboard_import <- function(sep = '\t',
+                             header = TRUE,
+                             dec = ".",
+                             na = c("", "NA", "NULL"),
+                             startrow = 1,
+                             as_vector = TRUE) {
+  
+  import_tbl <- read.delim(file = 'clipboard',
+                           sep = sep,
+                           header = header,
+                           strip.white = TRUE,
+                           dec = dec,
+                           na.strings = na,
+                           fileEncoding = 'UTF-8',
+                           encoding = 'UTF-8',
+                           stringsAsFactors = FALSE)
+  
+  # use tibble, so column types will be translated correctly
+  import_tbl <- as_tibble(import_tbl)
+  
+  if (startrow > 1) {
+    # would else lose column headers
+    import_tbl <- import_tbl[startrow:nrow(import_tbl),]
+  }
+  
+  colnames(import_tbl) <- gsub('[.]+', '_', colnames(import_tbl))
+  
+  if (NCOL(import_tbl) == 1 & as_vector == TRUE) {
+    import_tbl %>% pull(1)
+  } else {
+    import_tbl
+  }
+}
+
+#' @rdname clipboard
+#' @importFrom dplyr %>% pull as_tibble
+#' @export
+clipboard_export <- function(x,
+                             sep = '\t',
+                             dec = ".",
+                             na = "",
+                             header = TRUE) {
+  
+  x <- deparse(substitute(x))
+  size <- x %>%
+    get() %>% 
+    object.size() %>%
+    formatC(format = 'd') %>%
+    as.integer()
+  
+  x <- get(x)
+  
+  if (size > 25 * 1024 * 1024) {
+    # above 25 MB use a hacker function
+    writeClipboard(knitr::kable(x))
+  } else {
+    # set size of clipboard to 125% of the object size of x
+    write.table(x = x,
+                file = paste0("clipboard-", size * 1.25),
+                sep = sep,
+                na = na,
+                row.names = FALSE,
+                col.names = header,
+                dec = dec,
+                quote = FALSE)
+  }
+  cat("Successfully exported to clipboard:", NROW(x), "obs. of", NCOL(x), "variables.\n")
+  
+}

R/data.R

@@ -39,7 +39,7 @@
 #'   \item{\code{useful_grampositive}}{\code{FALSE} if not useful according to EUCAST, \code{NA} otherwise (see Source)}
 #' }
 #' @source - World Health Organization: \url{https://www.whocc.no/atc_ddd_index/} \cr - EUCAST - Expert rules intrinsic exceptional V3.1 \cr - MOLIS (LIS of Certe): \url{https://www.certe.nl} \cr - GLIMS (LIS of UMCG): \url{https://www.umcg.nl}
-#' @seealso \code{\link{bactlist}}
+#' @seealso \code{\link{microorganisms}}
 # last two columns created with:
 # antibiotics %>%
 #   mutate(useful_gramnegative = 
@@ -63,7 +63,7 @@
 
 #' Dataset with ~2500 microorganisms
 #'
-#' A dataset containing all microorganisms of MOLIS. MO codes of the UMCG can be looked up using \code{\link{bactlist.umcg}}.
+#' A dataset containing 2500 microorganisms. MO codes of the UMCG can be looked up using \code{\link{microorganisms.umcg}}.
 #' @format A data.frame with 2507 observations and 12 variables:
 #' \describe{
 #'   \item{\code{bactid}}{ID of microorganism}
@@ -80,24 +80,24 @@
 #'   \item{\code{gramstain_nl}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
 #' }
 #' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
-#' @seealso \code{\link{guess_bactid}} \code{\link{antibiotics}} \code{\link{bactlist.umcg}}
+#' @seealso \code{\link{guess_bactid}} \code{\link{antibiotics}} \code{\link{microorganisms.umcg}}
-"bactlist"
+"microorganisms"
 
 #' Translation table for UMCG with ~1100 microorganisms
 #'
-#' A dataset containing all bacteria codes of UMCG MMB. These codes can be joined to data with an ID from \code{\link{bactlist}$bactid} (using \code{\link{left_join_bactlist}}). GLIMS codes can also be translated to valid \code{bactid}'s with \code{\link{guess_bactid}}.
+#' A dataset containing all bacteria codes of UMCG MMB. These codes can be joined to data with an ID from \code{\link{microorganisms}$bactid} (using \code{\link{left_join_microorganisms}}). GLIMS codes can also be translated to valid \code{bactid}'s with \code{\link{guess_bactid}}.
 #' @format A data.frame with 1090 observations and 2 variables:
 #' \describe{
 #'   \item{\code{mocode}}{Code of microorganism according to UMCG MMB}
-#'   \item{\code{bactid}}{Code of microorganism in \code{\link{bactlist}}}
+#'   \item{\code{bactid}}{Code of microorganism in \code{\link{microorganisms}}}
 #' }
 #' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl}
-#' @seealso \code{\link{guess_bactid}} \code{\link{bactlist}}
+#' @seealso \code{\link{guess_bactid}} \code{\link{microorganisms}}
-"bactlist.umcg"
+"microorganisms.umcg"
 
 #' Dataset with 2000 blood culture isolates of septic patients
 #'
-#' An anonymised dataset containing 2000 microbial blood culture isolates with their antibiogram of septic patients found in 5 different hospitals in the Netherlands, between 2001 and 2017. This data.frame can be used to practice AMR analysis e.g. with \code{\link{rsi}} or \code{\link{rsi_predict}}, or it can be used to practice other statistics.
+#' An anonymised dataset containing 2000 microbial blood culture isolates with their antibiogram of septic patients found in 5 different hospitals in the Netherlands, between 2001 and 2017. This data.frame can be used to practice AMR analysis. For examples, press F1.
 #' @format A data.frame with 2000 observations and 47 variables:
 #' \describe{
 #'   \item{\code{date}}{date of receipt at the laboratory}
@@ -108,8 +108,47 @@
 #'   \item{\code{age}}{age of the patient}
 #'   \item{\code{sex}}{sex of the patient}
 #'   \item{\code{patient_id}}{ID of the patient, first 10 characters of an SHA hash containing irretrievable information}
-#'   \item{\code{bactid}}{ID of microorganism, see \code{\link{bactlist}}}
+#'   \item{\code{bactid}}{ID of microorganism, see \code{\link{microorganisms}}}
-#'   \item{\code{peni:mupi}}{38 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}), these column names occur in \code{\link{antibiotics}} and can be translated with \code{\link{abname}}}
+#'   \item{\code{peni:mupi}}{38 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}); these column names occur in \code{\link{antibiotics}} and can be translated with \code{\link{abname}}}
 #' }
 #' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
+#' @examples
+#' # ----------- #
+#' # PREPARATION #
+#' # ----------- #
+#' 
+#' # Save this example dataset to an object, so we can edit it:
+#' my_data <- septic_patients
+#' 
+#' # load the dplyr package to make data science A LOT easier
+#' library(dplyr)
+#' 
+#' # Add first isolates to our dataset:
+#' my_data <- my_data %>% 
+#'   mutate(first_isolates = first_isolate(my_data, date, patient_id, bactid))
+#' 
+#' # -------- #
+#' # ANALYSIS #
+#' # -------- #
+#' 
+#' # 1. Get the amoxicillin resistance percentages 
+#' #    of E. coli, divided by hospital:
+#' 
+#' my_data %>%
+#'   filter(bactid == "ESCCOL",
+#'          first_isolates == TRUE) %>% 
+#'   group_by(hospital_id) %>% 
+#'   summarise(n = n(),
+#'             amoxicillin_resistance = rsi(amox))
+#'   
+#'   
+#' # 2. Get the amoxicillin/clavulanic acid resistance 
+#' #    percentages of E. coli, trend over the years:
+#' 
+#' my_data %>% 
+#'   filter(bactid == guess_bactid("E. coli"),
+#'          first_isolates == TRUE) %>% 
+#'   group_by(year = format(date, "%Y")) %>% 
+#'   summarise(n = n(),
+#'             amoxclav_resistance = rsi(amcl, minimum = 20))
 "septic_patients"

R/first_isolates.R

@@ -22,8 +22,7 @@
 #' @param tbl a \code{data.frame} containing isolates.
 #' @param col_date column name of the result date (or date that is was received on the lab), supports tidyverse-like quotation
 #' @param col_patient_id column name of the unique IDs of the patients, supports tidyverse-like quotation
-#' @param col_genus column name of the genus of the microorganisms, supports tidyverse-like quotation
+#' @param col_bactid column name of the unique IDs of the microorganisms (should occur in the \code{\link{microorganisms}} dataset), supports tidyverse-like quotation
-#' @param col_species column name of the species of the microorganisms, supports tidyverse-like quotation
 #' @param col_testcode column name of the test codes. Use \code{col_testcode = NA} to \strong{not} exclude certain test codes (like test codes for screening). In that case \code{testcodes_exclude} will be ignored. Supports tidyverse-like quotation.
 #' @param col_specimen column name of the specimen type or group, supports tidyverse-like quotation
 #' @param col_icu column name of the logicals (\code{TRUE}/\code{FALSE}) whether a ward or department is an Intensive Care Unit (ICU), supports tidyverse-like quotation
@@ -37,6 +36,8 @@
 #' @param ignore_I logical to determine whether antibiotic interpretations with \code{"I"} will be ignored when \code{type = "keyantibiotics"}, see Details
 #' @param points_threshold points until the comparison of key antibiotics will lead to inclusion of an isolate when \code{type = "points"}, see Details
 #' @param info print progress
+#' @param col_genus (deprecated, use \code{col_bactid} instead) column name of the genus of the microorganisms, supports tidyverse-like quotation
+#' @param col_species (deprecated, use \code{col_bactid} instead) column name of the species of the microorganisms, supports tidyverse-like quotation
 #' @details \strong{WHY THIS IS SO IMPORTANT} \cr
 #'     To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode \href{https://www.ncbi.nlm.nih.gov/pubmed/17304462}{[1]}. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all \emph{S. aureus} isolates would be overestimated, because you included this MRSA more than once. It would be \href{https://en.wikipedia.org/wiki/Selection_bias}{selection bias}.
 #'
@@ -56,7 +57,7 @@
 #' 
 #' library(dplyr)
 #' my_patients$first_isolate <- my_patients %>%
-#'   left_join_bactlist() %>%
+#'   left_join_microorganisms() %>%
 #'   first_isolate(col_date = date,
 #'                 col_patient_id = patient_id,
 #'                 col_genus = genus,
@@ -104,8 +105,7 @@
 first_isolate <- function(tbl,
                           col_date,
                           col_patient_id,
-                          col_genus,
+                          col_bactid = NA,
-                          col_species,
                           col_testcode = NA,
                           col_specimen = NA,
                           col_icu = NA,
@@ -118,11 +118,14 @@ first_isolate <- function(tbl,
                           type = "keyantibiotics",
                           ignore_I = TRUE,
                           points_threshold = 2,
-                          info = TRUE) {
+                          info = TRUE,
+                          col_genus = NA,
+                          col_species = NA) {
   
   # support tidyverse-like quotation
   col_date <- quasiquotate(deparse(substitute(col_date)), col_date)
   col_patient_id <- quasiquotate(deparse(substitute(col_patient_id)), col_patient_id)
+  col_bactid <- quasiquotate(deparse(substitute(col_bactid)), col_bactid)
   col_genus <- quasiquotate(deparse(substitute(col_genus)), col_genus)
   col_species <- quasiquotate(deparse(substitute(col_species)), col_species)
   col_testcode <- quasiquotate(deparse(substitute(col_testcode)), col_testcode)
@@ -145,12 +148,19 @@ first_isolate <- function(tbl,
   
   check_columns_existance(col_date)
   check_columns_existance(col_patient_id)
+  check_columns_existance(col_bactid)
   check_columns_existance(col_genus)
   check_columns_existance(col_species)
   check_columns_existance(col_testcode)
   check_columns_existance(col_icu)
   check_columns_existance(col_keyantibiotics)
   
+  if (!is.na(col_bactid)) {
+    tbl <- tbl %>% left_join_microorganisms()
+    col_genus <- "genus"
+    col_species <- "species"
+  }
+  
   if (is.na(col_testcode)) {
     testcodes_exclude <- NA
   }
@@ -395,7 +405,7 @@ first_isolate <- function(tbl,
 #' Key antibiotics based on bacteria ID
 #'
 #' @param tbl table with antibiotics coloms, like \code{amox} and \code{amcl}.
-#' @param col_bactcode column of bacteria IDs in \code{tbl}; these should occur in \code{bactlist$bactid}, see \code{\link{bactlist}}
+#' @param col_bactid column of bacteria IDs in \code{tbl}; these should occur in \code{microorganisms$bactid}, see \code{\link{microorganisms}}
 #' @param info print warnings
 #' @param amcl,amox,cfot,cfta,cftr,cfur,cipr,clar,clin,clox,doxy,gent,line,mero,peni,pita,rifa,teic,trsu,vanc column names of antibiotics, case-insensitive
 #' @export
@@ -408,7 +418,7 @@ first_isolate <- function(tbl,
 #' tbl$keyab <- key_antibiotics(tbl)
 #' }
 key_antibiotics <- function(tbl,
-                            col_bactcode = 'bactid',
+                            col_bactid = 'bactid',
                             info = TRUE,
                             amcl = 'amcl',
                             amox = 'amox',
@@ -443,6 +453,8 @@ key_antibiotics <- function(tbl,
       col.list[i] <- toupper(col.list[i])
     } else if (tolower(col.list[i]) %in% colnames(tbl)) {
       col.list[i] <- tolower(col.list[i])
+    } else if (!col.list[i] %in% colnames(tbl)) {
+      col.list[i] <- NA
     }
   }
   if (!all(col.list %in% colnames(tbl))) {
@@ -473,8 +485,8 @@ key_antibiotics <- function(tbl,
   trsu <- col.list[18]
   vanc <- col.list[19]
   
-  # join bactlist
+  # join microorganisms
-  tbl <- tbl %>% left_join_bactlist(col_bactcode)
+  tbl <- tbl %>% left_join_microorganisms(col_bactid)
   
   tbl$key_ab <- NA_character_
   
@@ -595,7 +607,7 @@ key_antibiotics_equal <- function(x,
         result[i] <- all(x2 == y2)
         
       } else {
-        stop('`', type, '` is not a valid value for type, must be `points` or `keyantibiotics`. See ?first_isolate.')
+        stop('`', type, '` is not a valid value for type, must be "points" or "keyantibiotics". See ?first_isolate.')
       }
     }
   }
@@ -612,7 +624,7 @@ key_antibiotics_equal <- function(x,
 #' @export
 #' @importFrom dplyr %>% filter slice pull
 #' @return Character (vector).
-#' @seealso \code{\link{bactlist}} for the dataframe that is being used to determine ID's.
+#' @seealso \code{\link{microorganisms}} for the dataframe that is being used to determine ID's.
 #' @examples 
 #' # These examples all return "STAAUR", the ID of S. aureus:
 #' guess_bactid("stau")
@@ -662,24 +674,24 @@ guess_bactid <- function(x) {
     }
 
     # let's try the ID's first
-    found <- AMR::bactlist %>% filter(bactid == x.bak[i])
+    found <- AMR::microorganisms %>% filter(bactid == x.bak[i])
     
     if (nrow(found) == 0) {
       # now try exact match
-      found <- AMR::bactlist %>% filter(fullname == x[i])
+      found <- AMR::microorganisms %>% filter(fullname == x[i])
     }
     if (nrow(found) == 0) {
       # try any match
-      found <- AMR::bactlist %>% filter(fullname %like% x[i])
+      found <- AMR::microorganisms %>% filter(fullname %like% x[i])
     }
     if (nrow(found) == 0) {
       # try only genus, with 'species' attached
-      found <- AMR::bactlist %>% filter(fullname %like% x_species[i])
+      found <- AMR::microorganisms %>% filter(fullname %like% x_species[i])
     }
     if (nrow(found) == 0) {
       # search for GLIMS code
-      if (toupper(x.bak[i]) %in% toupper(AMR::bactlist.umcg$mocode)) {
+      if (toupper(x.bak[i]) %in% toupper(AMR::microorganisms.umcg$mocode)) {
-        found <- AMR::bactlist.umcg %>% filter(toupper(mocode) == toupper(x.bak[i]))
+        found <- AMR::microorganisms.umcg %>% filter(toupper(mocode) == toupper(x.bak[i]))
       }
     }
     if (nrow(found) == 0) {
@@ -689,7 +701,7 @@ guess_bactid <- function(x) {
       x[i] <- paste0(x.bak[i] %>% substr(1, x_length / 2) %>% trimws(),
                      '.* ',
                      x.bak[i] %>% substr((x_length / 2) + 1, x_length) %>% trimws())
-      found <- AMR::bactlist %>% filter(fullname %like% paste0('^', x[i]))
+      found <- AMR::microorganisms %>% filter(fullname %like% paste0('^', x[i]))
     }
     
     if (nrow(found) != 0) {

R/join.R

@@ -1,20 +1,20 @@
-#' Join a table with \code{bactlist}
+#' Join a table with \code{microorganisms}
 #'
-#' Join the list of microorganisms \code{\link{bactlist}} easily to an existing table.
+#' Join the dataset \code{\link{microorganisms}} easily to an existing table or character vector.
 #' @rdname join
 #' @name join
 #' @aliases join inner_join
 #' @param x existing table to join, also supports character vectors
-#' @param by a variable to join by - could be a column name of \code{x} with values that exist in \code{bactlist$bactid} (like \code{by = "bacteria_id"}), or another column in \code{\link{bactlist}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})
+#' @param by a variable to join by - could be a column name of \code{x} with values that exist in \code{microorganisms$bactid} (like \code{by = "bacteria_id"}), or another column in \code{\link{microorganisms}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})
 #' @param suffix if there are non-joined duplicate variables in \code{x} and \code{y}, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.
 #' @param ... other parameters to pass on to \code{dplyr::\link[dplyr]{join}}.
 #' @details As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, characters vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
 #' @export
 #' @examples 
-#' left_join_bactlist("STAAUR")
+#' left_join_microorganisms("STAAUR")
 #' 
 #' library(dplyr)
-#' septic_patients %>% left_join_bactlist()
+#' septic_patients %>% left_join_microorganisms()
 #' 
 #' df <- data.frame(date = seq(from = as.Date("2018-01-01"),
 #'                             to = as.Date("2018-01-07"),
@@ -23,20 +23,20 @@
 #'                                  "ESCCOL", "ESCCOL", "ESCCOL"),
 #'                  stringsAsFactors = FALSE)
 #' colnames(df)
-#' df2 <- left_join_bactlist(df, "bacteria_id")
+#' df2 <- left_join_microorganisms(df, "bacteria_id")
 #' colnames(df2)
-inner_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
+inner_join_microorganisms <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
   if (any(class(x) %in% c('character', 'factor'))) {
     x <- data.frame(bactid = x, stringsAsFactors = FALSE)
   }
   # no name set to `by` parameter
   if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
+    joinby <- colnames(AMR::microorganisms)[1]
     names(joinby) <- by
   } else {
     joinby <- by
   }
-  join <- dplyr::inner_join(x = x, y = AMR::bactlist, by = joinby, suffix = c("2", ""), ...)
+  join <- dplyr::inner_join(x = x, y = AMR::microorganisms, by = joinby, suffix = c("2", ""), ...)
   if (nrow(join) > nrow(x)) {
     warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
   }
@@ -45,18 +45,18 @@ inner_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
 
 #' @rdname join
 #' @export
-left_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
+left_join_microorganisms <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
   if (any(class(x) %in% c('character', 'factor'))) {
     x <- data.frame(bactid = x, stringsAsFactors = FALSE)
   }
   # no name set to `by` parameter
   if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
+    joinby <- colnames(AMR::microorganisms)[1]
     names(joinby) <- by
   } else {
     joinby <- by
   }
-  join <- dplyr::left_join(x = x, y = AMR::bactlist, by = joinby, suffix = c("2", ""), ...)
+  join <- dplyr::left_join(x = x, y = AMR::microorganisms, by = joinby, suffix = c("2", ""), ...)
   if (nrow(join) > nrow(x)) {
     warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
   }
@@ -65,18 +65,18 @@ left_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
 
 #' @rdname join
 #' @export
-right_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
+right_join_microorganisms <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
   if (any(class(x) %in% c('character', 'factor'))) {
     x <- data.frame(bactid = x, stringsAsFactors = FALSE)
   }
   # no name set to `by` parameter
   if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
+    joinby <- colnames(AMR::microorganisms)[1]
     names(joinby) <- by
   } else {
     joinby <- by
   }
-  join <- dplyr::right_join(x = x, y = AMR::bactlist, by = joinby, suffix = c("2", ""), ...)
+  join <- dplyr::right_join(x = x, y = AMR::microorganisms, by = joinby, suffix = c("2", ""), ...)
   if (nrow(join) > nrow(x)) {
     warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
   }
@@ -85,48 +85,48 @@ right_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
 
 #' @rdname join
 #' @export
-full_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
+full_join_microorganisms <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
   if (any(class(x) %in% c('character', 'factor'))) {
     x <- data.frame(bactid = x, stringsAsFactors = FALSE)
   }
   # no name set to `by` parameter
   if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
+    joinby <- colnames(AMR::microorganisms)[1]
     names(joinby) <- by
   } else {
     joinby <- by
   }
-  dplyr::full_join(x = x, y = AMR::bactlist, by = joinby, suffix = c("2", ""), ...)
+  dplyr::full_join(x = x, y = AMR::microorganisms, by = joinby, suffix = c("2", ""), ...)
 }
 
 #' @rdname join
 #' @export
-semi_join_bactlist <- function(x, by = 'bactid', ...) {
+semi_join_microorganisms <- function(x, by = 'bactid', ...) {
   if (any(class(x) %in% c('character', 'factor'))) {
     x <- data.frame(bactid = x, stringsAsFactors = FALSE)
   }
   # no name set to `by` parameter
   if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
+    joinby <- colnames(AMR::microorganisms)[1]
     names(joinby) <- by
   } else {
     joinby <- by
   }
-  dplyr::semi_join(x = x, y = AMR::bactlist, by = joinby, ...)
+  dplyr::semi_join(x = x, y = AMR::microorganisms, by = joinby, ...)
 }
 
 #' @rdname join
 #' @export
-anti_join_bactlist <- function(x, by = 'bactid', ...) {
+anti_join_microorganisms <- function(x, by = 'bactid', ...) {
   if (any(class(x) %in% c('character', 'factor'))) {
     x <- data.frame(bactid = x, stringsAsFactors = FALSE)
   }
   # no name set to `by` parameter
   if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
+    joinby <- colnames(AMR::microorganisms)[1]
     names(joinby) <- by
   } else {
     joinby <- by
   }
-  dplyr::anti_join(x = x, y = AMR::bactlist, by = joinby, ...)
+  dplyr::anti_join(x = x, y = AMR::microorganisms, by = joinby, ...)
 }

R/misc.R

@@ -40,9 +40,9 @@ quasiquotate <- function(deparsed, parsed) {
   }
   # apply if needed
   if (any(!deparsed %like% '[[$:()]'
-      & !deparsed %in% c('""', "''", "", # empty text
+      & !deparsed %in% c('""', "''", "",      # empty text
-                         ".", ".data", # dplyr references
+                         ".", ".data",        # dplyr references
-                         "TRUE", "FALSE", # logicals
+                         "TRUE", "FALSE",     # logicals
                          "NA", "NaN", "NULL", # empty values
                          ls(.GlobalEnv)))) {
     deparsed

R/rsi_analysis.R

@@ -20,7 +20,7 @@
 #'
 #' \strong{NOTE: use \code{\link{rsi}} in dplyr functions like \code{\link[dplyr]{summarise}}.} \cr Calculate the percentage of S, SI, I, IR or R of a \code{data.frame} containing isolates.
 #' @param tbl \code{data.frame} containing columns with antibiotic interpretations.
-#' @param antibiotics character vector with 1, 2 or 3 antibiotics that occur as column names in \code{tbl}, like \code{antibiotics = c("amox", "amcl")}
+#' @param ab character vector with 1, 2 or 3 antibiotics that occur as column names in \code{tbl}, like \code{ab = c("amox", "amcl")}
 #' @param interpretation antimicrobial interpretation of which the portion must be calculated. Valid values are \code{"S"}, \code{"SI"}, \code{"I"}, \code{"IR"} or \code{"R"}.
 #' @param minimum minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA} with a warning (when \code{warning = TRUE}).
 #' @param percent return output as percent (text), will else (at default) be a double
@@ -43,27 +43,27 @@
 #' my_table %>%
 #'   filter(first_isolate == TRUE, 
 #'          genus == "Helicobacter") %>%
-#'   rsi_df(antibiotics = c("amox", "metr"))
+#'   rsi_df(ab = c("amox", "metr"))
 #' }
 rsi_df <- function(tbl,
-                   antibiotics,
+                   ab,
                    interpretation = 'IR',
                    minimum = 30,
                    percent = FALSE,
                    info = TRUE,
                    warning = TRUE) {
+
+  # in case tbl$interpretation already exists:
+  interpretations_to_check <- paste(interpretation, collapse = "")
   
-  # we willen niet dat tbl$interpretation toevallig ook bestaat, dus:
+  # validate:
-  te_testen_uitslag_ab <- interpretation
+  if (min(grepl('^[a-z]{3,4}$', ab)) == 0 &
-  
+      min(grepl('^rsi[1-2]$', ab)) == 0) {
-  # validatie:
+    for (i in 1:length(ab)) {
-  if (min(grepl('^[a-z]{3,4}$', antibiotics)) == 0 &
+      ab[i] <- paste0('rsi', i)
-      min(grepl('^rsi[1-2]$', antibiotics)) == 0) {
-    for (i in 1:length(antibiotics)) {
-      antibiotics[i] <- paste0('rsi', i)
     }
   }
-  if (!grepl('^(S|SI|IS|I|IR|RI|R){1}$', te_testen_uitslag_ab)) {
+  if (!grepl('^(S|SI|IS|I|IR|RI|R){1}$', interpretations_to_check)) {
     stop('Invalid `interpretation`; must be "S", "SI", "I", "IR", or "R".')
   }
   if ('is_ic' %in% colnames(tbl)) {
@@ -72,59 +72,59 @@ rsi_df <- function(tbl,
     }
   }
   
-  # transformeren wanneer gezocht wordt op verschillende uitslagen
+  # transform when checking for different results
-  if (te_testen_uitslag_ab %in% c('SI', 'IS')) {
+  if (interpretations_to_check %in% c('SI', 'IS')) {
-    for (i in 1:length(antibiotics)) {
+    for (i in 1:length(ab)) {
-      lijst <- tbl[, antibiotics[i]]
+      lijst <- tbl[, ab[i]]
       if ('I' %in% lijst) {
-        tbl[which(tbl[antibiotics[i]] == 'I'), ][antibiotics[i]] <- 'S'
+        tbl[which(tbl[ab[i]] == 'I'), ][ab[i]] <- 'S'
       }
     }
-    te_testen_uitslag_ab <- 'S'
+    interpretations_to_check <- 'S'
   }
-  if (te_testen_uitslag_ab %in% c('RI', 'IR')) {
+  if (interpretations_to_check %in% c('RI', 'IR')) {
-    for (i in 1:length(antibiotics)) {
+    for (i in 1:length(ab)) {
-      lijst <- tbl[, antibiotics[i]]
+      lijst <- tbl[, ab[i]]
       if ('I' %in% lijst) {
-        tbl[which(tbl[antibiotics[i]] == 'I'), ][antibiotics[i]] <- 'R'
+        tbl[which(tbl[ab[i]] == 'I'), ][ab[i]] <- 'R'
       }
     }
-    te_testen_uitslag_ab <- 'R'
+    interpretations_to_check <- 'R'
   }
-  
+
-  # breuk samenstellen
+  # get fraction
-  if (length(antibiotics) == 1) {
+  if (length(ab) == 1) {
     numerator <- tbl %>%
-      filter(pull(., antibiotics[1]) == te_testen_uitslag_ab) %>%
+      filter(pull(., ab[1]) == interpretations_to_check) %>%
       nrow()
-    
+
     denominator <- tbl %>%
-      filter(pull(., antibiotics[1]) %in% c("S", "I", "R")) %>%
+      filter(pull(., ab[1]) %in% c("S", "I", "R")) %>%
       nrow()
     
-  } else if (length(antibiotics) == 2) {
+  } else if (length(ab) == 2) {
     numerator <- tbl %>%
-      filter_at(vars(antibiotics[1], antibiotics[2]),
+      filter_at(vars(ab[1], ab[2]),
-                any_vars(. == te_testen_uitslag_ab)) %>%
+                any_vars(. == interpretations_to_check)) %>%
-      filter_at(vars(antibiotics[1], antibiotics[2]),
+      filter_at(vars(ab[1], ab[2]),
                 all_vars(. %in% c("S", "R", "I"))) %>%
       nrow()
     
     denominator <- tbl %>%
-      filter_at(vars(antibiotics[1], antibiotics[2]),
+      filter_at(vars(ab[1], ab[2]),
                 all_vars(. %in% c("S", "R", "I"))) %>%
       nrow()
     
-  } else if (length(antibiotics) == 3) {
+  } else if (length(ab) == 3) {
     numerator <- tbl %>%
-      filter_at(vars(antibiotics[1], antibiotics[2], antibiotics[3]),
+      filter_at(vars(ab[1], ab[2], ab[3]),
-                any_vars(. == te_testen_uitslag_ab)) %>%
+                any_vars(. == interpretations_to_check)) %>%
-      filter_at(vars(antibiotics[1], antibiotics[2], antibiotics[3]),
+      filter_at(vars(ab[1], ab[2], ab[3]),
                 all_vars(. %in% c("S", "R", "I"))) %>%
       nrow()
     
     denominator <- tbl %>%
-      filter_at(vars(antibiotics[1], antibiotics[2], antibiotics[3]),
+      filter_at(vars(ab[1], ab[2], ab[3]),
                 all_vars(. %in% c("S", "R", "I"))) %>%
       nrow()
     
@@ -132,7 +132,7 @@ rsi_df <- function(tbl,
     stop('Maximum of 3 drugs allowed.')
   }
   
-  # tekstdeel opbouwen
+  # build text part
   if (info == TRUE) {
     cat('n =', denominator)
     info.txt1 <- percent(denominator / nrow(tbl))
@@ -140,23 +140,22 @@ rsi_df <- function(tbl,
       info.txt1 <- 'none'
     }
     info.txt2 <- gsub(',', ' and',
-                      antibiotics %>%
+                      ab %>%
-                        abname(to = 'trivial',
+                        abname(tolower = TRUE) %>%
-                               tolower = TRUE) %>%
                         toString(), fixed = TRUE)
     info.txt2 <- gsub('rsi1 and rsi2', 'these two drugs', info.txt2, fixed = TRUE)
     info.txt2 <- gsub('rsi1', 'this drug', info.txt2, fixed = TRUE)
     cat(paste0(' (of ', nrow(tbl), ' in total; ', info.txt1, ' tested on ', info.txt2, ')\n'))
   }
   
-  # rekenen en opmaken
+  # calculate and format
   y <- numerator / denominator
   if (percent == TRUE) {
     y <- percent(y)
   }
   if (denominator < minimum) {
     if (warning == TRUE) {
-      warning(paste0('TOO FEW ISOLATES OF ', toString(antibiotics), ' (n = ', denominator, ', n < ', minimum, '); NO RESULT.'))
+      warning(paste0('TOO FEW ISOLATES OF ', toString(ab), ' (n = ', denominator, ', n < ', minimum, '); NO RESULT.'))
     }
     y <- NA
   }
@@ -192,26 +191,31 @@ rsi_df <- function(tbl,
 #' rsi(as.rsi(isolates$amcl), interpretation = "S")
 #' }
 rsi <- function(ab1, ab2 = NA, interpretation = 'IR', minimum = 30, percent = FALSE, info = FALSE, warning = FALSE) {
-  function_text <- as.character(match.call())
+  ab1.name <- deparse(substitute(ab1))
-  # param 1 = functienaam
+  if (ab1.name %like% '.[$].') {
-  # param 2 = ab1
+    ab1.name <- unlist(strsplit(ab1.name, "$", fixed = TRUE))
-  # param 3 = ab2
+    ab1.name <- ab1.name[length(ab1.name)]
-  ab1.naam <- function_text[2]
-  if (!grepl('^[a-z]{3,4}$', ab1.naam)) {
-    ab1.naam <- 'rsi1'
   }
-  ab2.naam <- function_text[3]
+  if (!ab1.name %like% '^[a-z]{3,4}$') {
-  if (!grepl('^[a-z]{3,4}$', ab2.naam)) {
+    ab1.name <- 'rsi1'
-    ab2.naam <- 'rsi2'
   }
+  ab2.name <- deparse(substitute(ab2))
+  if (ab2.name %like% '.[$].') {
+    ab2.name <- unlist(strsplit(ab2.name, "$", fixed = TRUE))
+    ab2.name <- ab2.name[length(ab2.name)]
+  }
+  if (!ab2.name %like% '^[a-z]{3,4}$') {
+    ab2.name <- 'rsi2'
+  }
+  
+  interpretation <- paste(interpretation, collapse = "")
   
   tbl <- tibble(rsi1 = ab1, rsi2 = ab2)
-  
+  colnames(tbl) <- c(ab1.name, ab2.name)
-  colnames(tbl) <- c(ab1.naam, ab2.naam)
   
   if (length(ab2) == 1) {
     return(rsi_df(tbl = tbl,
-                  antibiotics = ab1.naam,
+                  ab = ab1.name,
                   interpretation = interpretation,
                   minimum = minimum,
                   percent = percent,
@@ -225,7 +229,7 @@ rsi <- function(ab1, ab2 = NA, interpretation = 'IR', minimum = 30, percent = FA
       warning('`interpretation` is not set to S, albeit analysing a combination therapy.')
     }
     return(rsi_df(tbl = tbl,
-                  antibiotics = c(ab1.naam, ab2.naam),
+                  ab = c(ab1.name, ab2.name),
                   interpretation = interpretation,
                   minimum = minimum,
                   percent = percent,
@@ -270,7 +274,7 @@ rsi <- function(ab1, ab2 = NA, interpretation = 'IR', minimum = 30, percent = FA
 #' library(dplyr)
 #' septic_patients %>%
 #'   # get bacteria properties like genus and species
-#'   left_join_bactlist("bactid") %>% 
+#'   left_join_microorganisms("bactid") %>% 
 #'   # calculate first isolates
 #'   mutate(first_isolate = 
 #'            first_isolate(.,

man/EUCAST.Rd

@@ -9,11 +9,11 @@ EUCAST Expert Rules Version 2.0: \cr
   Leclercq et al. \strong{EUCAST expert rules in antimicrobial susceptibility testing.} \emph{Clin Microbiol Infect.} 2013;19(2):141-60. \cr
   \url{https://doi.org/10.1111/j.1469-0691.2011.03703.x} \cr
   \cr
-  EUCAST Expert Rules Version 3.1: \cr
+  EUCAST Expert Rules Version 3.1 (Intrinsic Resistance and Exceptional Phenotypes Tables): \cr
-  \url{http://www.eucast.org/expert_rules_and_intrinsic_resistance}
+  \url{http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf}
 }
 \usage{
-EUCAST_rules(tbl, col_bactcode = "bactid", info = TRUE, amcl = "amcl",
+EUCAST_rules(tbl, col_bactid = "bactid", info = TRUE, amcl = "amcl",
   amik = "amik", amox = "amox", ampi = "ampi", azit = "azit",
   aztr = "aztr", cefa = "cefa", cfra = "cfra", cfep = "cfep",
   cfot = "cfot", cfox = "cfox", cfta = "cfta", cftr = "cftr",
@@ -35,7 +35,7 @@ interpretive_reading(...)
 \arguments{
 \item{tbl}{table with antibiotic columns, like e.g. \code{amox} and \code{amcl}}
 
-\item{col_bactcode}{column name of the bacteria ID in \code{tbl} - values of this column should be present in \code{bactlist$bactid}, see \code{\link{bactlist}}}
+\item{col_bactid}{column name of the bacteria ID in \code{tbl} - values of this column should be present in \code{microorganisms$bactid}, see \code{\link{microorganisms}}}
 
 \item{info}{print progress}
 

man/abname.Rd

@@ -7,13 +7,13 @@
 \code{\link{antibiotics}}
 }
 \usage{
-abname(abcode, from = "umcg", to = "official", textbetween = " + ",
+abname(abcode, from = c("guess", "atc", "molis", "umcg"), to = "official",
-  tolower = FALSE)
+  textbetween = " + ", tolower = FALSE)
 }
 \arguments{
 \item{abcode}{a code or name, like \code{"AMOX"}, \code{"AMCL"} or \code{"J01CA04"}}
 
-\item{from, to}{type to transform from and to. See \code{\link{antibiotics}} for its column names.}
+\item{from, to}{type to transform from and to. See \code{\link{antibiotics}} for its column names. WIth \code{from = "guess"} the from will be guessed from \code{"atc"}, \code{"molis"} and \code{"umcg"}.}
 
 \item{textbetween}{text to put between multiple returned texts}
 

man/antibiotics.Rd

@@ -33,6 +33,6 @@ antibiotics
 A dataset containing all antibiotics with a J0 code, with their DDD's. Properties were downloaded from the WHO, see Source.
 }
 \seealso{
-\code{\link{bactlist}}
+\code{\link{microorganisms}}
 }
 \keyword{datasets}

man/clipboard.Rd

@@ -0,0 +1,50 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/clipboard.R
+\name{clipboard}
+\alias{clipboard}
+\alias{clipboard_import}
+\alias{clipboard_export}
+\title{Import/export from clipboard}
+\usage{
+clipboard_import(sep = "\\t", header = TRUE, dec = ".", na = c("", "NA",
+  "NULL"), startrow = 1, as_vector = TRUE)
+
+clipboard_export(x, sep = "\\t", dec = ".", na = "", header = TRUE)
+}
+\arguments{
+\item{sep}{the field separator character.  Values on each line of the
+    file are separated by this character.  If \code{sep = ""} (the
+    default for \code{read.table}) the separator is \sQuote{white space},
+    that is one or more spaces, tabs, newlines or carriage returns.}
+
+\item{header}{a logical value indicating whether the file contains the
+    names of the variables as its first line.  If missing, the value is
+    determined from the file format: \code{header} is set to \code{TRUE}
+    if and only if the first row contains one fewer field than the
+    number of columns.}
+
+\item{dec}{the character used in the file for decimal points.}
+
+\item{na}{the string to use for missing values in the data.}
+
+\item{startrow}{\emph{n}th row to start importing from. For \code{clipboard_import}, when \code{header = TRUE} the import will start on row \code{startrow} \emph{below} the header.}
+
+\item{as_vector}{a logical value indicating whether data consisting of only one column should be imported as vector using \code{\link[dplyr]{pull}}. This will strip off the header.}
+
+\item{x}{the object to be written, preferably a matrix or data frame.
+    If not, it is attempted to coerce \code{x} to a data frame.}
+}
+\value{
+data.frame
+}
+\description{
+These are helper functions around \code{\link{read.table}} and \code{\link{write.table}} to import from and export to clipboard. The data will be read and written as tab-separated by default, which makes it possible to copy and paste from other software like Excel and SPSS without further transformation.
+}
+\details{
+For \code{clipboard_export}, the reserved clipboard size for exporting will be set automatically to 125\% of the object size of \code{x}. This way, it is possible to export data with thousands of rows as the only limit will be your systems RAM.
+}
+\keyword{clipboard}
+\keyword{clipboard_export}
+\keyword{clipboard_import}
+\keyword{export}
+\keyword{import}

man/first_isolate.Rd

@@ -4,12 +4,12 @@
 \alias{first_isolate}
 \title{Determine first (weighted) isolates}
 \usage{
-first_isolate(tbl, col_date, col_patient_id, col_genus, col_species,
+first_isolate(tbl, col_date, col_patient_id, col_bactid = NA,
   col_testcode = NA, col_specimen = NA, col_icu = NA,
   col_keyantibiotics = NA, episode_days = 365, testcodes_exclude = "",
   icu_exclude = FALSE, filter_specimen = NA, output_logical = TRUE,
   type = "keyantibiotics", ignore_I = TRUE, points_threshold = 2,
-  info = TRUE)
+  info = TRUE, col_genus = NA, col_species = NA)
 }
 \arguments{
 \item{tbl}{a \code{data.frame} containing isolates.}
@@ -18,9 +18,7 @@ first_isolate(tbl, col_date, col_patient_id, col_genus, col_species,
 
 \item{col_patient_id}{column name of the unique IDs of the patients, supports tidyverse-like quotation}
 
-\item{col_genus}{column name of the genus of the microorganisms, supports tidyverse-like quotation}
+\item{col_bactid}{column name of the unique IDs of the microorganisms (should occur in the \code{\link{microorganisms}} dataset), supports tidyverse-like quotation}
-
-\item{col_species}{column name of the species of the microorganisms, supports tidyverse-like quotation}
 
 \item{col_testcode}{column name of the test codes. Use \code{col_testcode = NA} to \strong{not} exclude certain test codes (like test codes for screening). In that case \code{testcodes_exclude} will be ignored. Supports tidyverse-like quotation.}
 
@@ -47,6 +45,10 @@ first_isolate(tbl, col_date, col_patient_id, col_genus, col_species,
 \item{points_threshold}{points until the comparison of key antibiotics will lead to inclusion of an isolate when \code{type = "points"}, see Details}
 
 \item{info}{print progress}
+
+\item{col_genus}{(deprecated, use \code{col_bactid} instead) column name of the genus of the microorganisms, supports tidyverse-like quotation}
+
+\item{col_species}{(deprecated, use \code{col_bactid} instead) column name of the species of the microorganisms, supports tidyverse-like quotation}
 }
 \value{
 A vector to add to table, see Examples.
@@ -71,7 +73,7 @@ my_patients <- septic_patients
 
 library(dplyr)
 my_patients$first_isolate <- my_patients \%>\%
-  left_join_bactlist() \%>\%
+  left_join_microorganisms() \%>\%
   first_isolate(col_date = date,
                 col_patient_id = patient_id,
                 col_genus = genus,

man/guess_bactid.Rd

@@ -27,5 +27,5 @@ guess_bactid("MRSA") # Methicillin-resistant S. aureus
 guess_bactid("VISA") # Vancomycin Intermediate S. aureus
 }
 \seealso{
-\code{\link{bactlist}} for the dataframe that is being used to determine ID's.
+\code{\link{microorganisms}} for the dataframe that is being used to determine ID's.
 }

man/join.Rd

@@ -2,47 +2,47 @@
 % Please edit documentation in R/join.R
 \name{join}
 \alias{join}
-\alias{inner_join_bactlist}
+\alias{inner_join_microorganisms}
 \alias{inner_join}
-\alias{left_join_bactlist}
+\alias{left_join_microorganisms}
-\alias{right_join_bactlist}
+\alias{right_join_microorganisms}
-\alias{full_join_bactlist}
+\alias{full_join_microorganisms}
-\alias{semi_join_bactlist}
+\alias{semi_join_microorganisms}
-\alias{anti_join_bactlist}
+\alias{anti_join_microorganisms}
-\title{Join a table with \code{bactlist}}
+\title{Join a table with \code{microorganisms}}
 \usage{
-inner_join_bactlist(x, by = "bactid", suffix = c("2", ""), ...)
+inner_join_microorganisms(x, by = "bactid", suffix = c("2", ""), ...)
 
-left_join_bactlist(x, by = "bactid", suffix = c("2", ""), ...)
+left_join_microorganisms(x, by = "bactid", suffix = c("2", ""), ...)
 
-right_join_bactlist(x, by = "bactid", suffix = c("2", ""), ...)
+right_join_microorganisms(x, by = "bactid", suffix = c("2", ""), ...)
 
-full_join_bactlist(x, by = "bactid", suffix = c("2", ""), ...)
+full_join_microorganisms(x, by = "bactid", suffix = c("2", ""), ...)
 
-semi_join_bactlist(x, by = "bactid", ...)
+semi_join_microorganisms(x, by = "bactid", ...)
 
-anti_join_bactlist(x, by = "bactid", ...)
+anti_join_microorganisms(x, by = "bactid", ...)
 }
 \arguments{
 \item{x}{existing table to join, also supports character vectors}
 
-\item{by}{a variable to join by - could be a column name of \code{x} with values that exist in \code{bactlist$bactid} (like \code{by = "bacteria_id"}), or another column in \code{\link{bactlist}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})}
+\item{by}{a variable to join by - could be a column name of \code{x} with values that exist in \code{microorganisms$bactid} (like \code{by = "bacteria_id"}), or another column in \code{\link{microorganisms}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})}
 
 \item{suffix}{if there are non-joined duplicate variables in \code{x} and \code{y}, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.}
 
 \item{...}{other parameters to pass on to \code{dplyr::\link[dplyr]{join}}.}
 }
 \description{
-Join the list of microorganisms \code{\link{bactlist}} easily to an existing table.
+Join the dataset \code{\link{microorganisms}} easily to an existing table or character vector.
 }
 \details{
 As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, characters vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
 }
 \examples{
-left_join_bactlist("STAAUR")
+left_join_microorganisms("STAAUR")
 
 library(dplyr)
-septic_patients \%>\% left_join_bactlist()
+septic_patients \%>\% left_join_microorganisms()
 
 df <- data.frame(date = seq(from = as.Date("2018-01-01"),
                             to = as.Date("2018-01-07"),
@@ -51,6 +51,6 @@ df <- data.frame(date = seq(from = as.Date("2018-01-01"),
                                  "ESCCOL", "ESCCOL", "ESCCOL"),
                  stringsAsFactors = FALSE)
 colnames(df)
-df2 <- left_join_bactlist(df, "bacteria_id")
+df2 <- left_join_microorganisms(df, "bacteria_id")
 colnames(df2)
 }

man/key_antibiotics.Rd

@@ -4,7 +4,7 @@
 \alias{key_antibiotics}
 \title{Key antibiotics based on bacteria ID}
 \usage{
-key_antibiotics(tbl, col_bactcode = "bactid", info = TRUE, amcl = "amcl",
+key_antibiotics(tbl, col_bactid = "bactid", info = TRUE, amcl = "amcl",
   amox = "amox", cfot = "cfot", cfta = "cfta", cftr = "cftr",
   cfur = "cfur", cipr = "cipr", clar = "clar", clin = "clin",
   clox = "clox", doxy = "doxy", gent = "gent", line = "line",
@@ -14,7 +14,7 @@ key_antibiotics(tbl, col_bactcode = "bactid", info = TRUE, amcl = "amcl",
 \arguments{
 \item{tbl}{table with antibiotics coloms, like \code{amox} and \code{amcl}.}
 
-\item{col_bactcode}{column of bacteria IDs in \code{tbl}; these should occur in \code{bactlist$bactid}, see \code{\link{bactlist}}}
+\item{col_bactid}{column of bacteria IDs in \code{tbl}; these should occur in \code{microorganisms$bactid}, see \code{\link{microorganisms}}}
 
 \item{info}{print warnings}
 

man/microorganisms.Rd

@@ -1,8 +1,8 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/data.R
 \docType{data}
-\name{bactlist}
+\name{microorganisms}
-\alias{bactlist}
+\alias{microorganisms}
 \title{Dataset with ~2500 microorganisms}
 \format{A data.frame with 2507 observations and 12 variables:
 \describe{
@@ -23,12 +23,12 @@
 MOLIS (LIS of Certe) - \url{https://www.certe.nl}
 }
 \usage{
-bactlist
+microorganisms
 }
 \description{
-A dataset containing all microorganisms of MOLIS. MO codes of the UMCG can be looked up using \code{\link{bactlist.umcg}}.
+A dataset containing 2500 microorganisms. MO codes of the UMCG can be looked up using \code{\link{microorganisms.umcg}}.
 }
 \seealso{
-\code{\link{guess_bactid}} \code{\link{antibiotics}} \code{\link{bactlist.umcg}}
+\code{\link{guess_bactid}} \code{\link{antibiotics}} \code{\link{microorganisms.umcg}}
 }
 \keyword{datasets}

man/microorganisms.umcg.Rd

@@ -1,24 +1,24 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/data.R
 \docType{data}
-\name{bactlist.umcg}
+\name{microorganisms.umcg}
-\alias{bactlist.umcg}
+\alias{microorganisms.umcg}
 \title{Translation table for UMCG with ~1100 microorganisms}
 \format{A data.frame with 1090 observations and 2 variables:
 \describe{
   \item{\code{mocode}}{Code of microorganism according to UMCG MMB}
-  \item{\code{bactid}}{Code of microorganism in \code{\link{bactlist}}}
+  \item{\code{bactid}}{Code of microorganism in \code{\link{microorganisms}}}
 }}
 \source{
 MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl}
 }
 \usage{
-bactlist.umcg
+microorganisms.umcg
 }
 \description{
-A dataset containing all bacteria codes of UMCG MMB. These codes can be joined to data with an ID from \code{\link{bactlist}$bactid} (using \code{\link{left_join_bactlist}}). GLIMS codes can also be translated to valid \code{bactid}'s with \code{\link{guess_bactid}}.
+A dataset containing all bacteria codes of UMCG MMB. These codes can be joined to data with an ID from \code{\link{microorganisms}$bactid} (using \code{\link{left_join_microorganisms}}). GLIMS codes can also be translated to valid \code{bactid}'s with \code{\link{guess_bactid}}.
 }
 \seealso{
-\code{\link{guess_bactid}} \code{\link{bactlist}}
+\code{\link{guess_bactid}} \code{\link{microorganisms}}
 }
 \keyword{datasets}

man/mo_property.Rd

@@ -4,10 +4,10 @@
 \alias{mo_property}
 \title{Poperties of a microorganism}
 \usage{
-mo_property(bactcode, property = "fullname")
+mo_property(bactid, property = "fullname")
 }
 \arguments{
-\item{bactcode}{ID of a microorganisme, like \code{"STAAUR} and \code{"ESCCOL}}
+\item{bactid}{ID of a microorganisme, like \code{"STAAUR} and \code{"ESCCOL}}
 
 \item{property}{One of the values \code{bactid}, \code{bactsys}, \code{family}, \code{genus}, \code{species}, \code{subspecies}, \code{fullname}, \code{type}, \code{gramstain}, \code{aerobic}}
 }
@@ -15,5 +15,5 @@ mo_property(bactcode, property = "fullname")
 Poperties of a microorganism
 }
 \seealso{
-\code{\link{bactlist}}
+\code{\link{microorganisms}}
 }

man/rsi_df.Rd

@@ -4,13 +4,13 @@
 \alias{rsi_df}
 \title{Resistance of isolates in data.frame}
 \usage{
-rsi_df(tbl, antibiotics, interpretation = "IR", minimum = 30,
+rsi_df(tbl, ab, interpretation = "IR", minimum = 30, percent = FALSE,
-  percent = FALSE, info = TRUE, warning = TRUE)
+  info = TRUE, warning = TRUE)
 }
 \arguments{
 \item{tbl}{\code{data.frame} containing columns with antibiotic interpretations.}
 
-\item{antibiotics}{character vector with 1, 2 or 3 antibiotics that occur as column names in \code{tbl}, like \code{antibiotics = c("amox", "amcl")}}
+\item{ab}{character vector with 1, 2 or 3 antibiotics that occur as column names in \code{tbl}, like \code{ab = c("amox", "amcl")}}
 
 \item{interpretation}{antimicrobial interpretation of which the portion must be calculated. Valid values are \code{"S"}, \code{"SI"}, \code{"I"}, \code{"IR"} or \code{"R"}.}
 
@@ -42,7 +42,7 @@ library(dplyr)
 my_table \%>\%
   filter(first_isolate == TRUE, 
          genus == "Helicobacter") \%>\%
-  rsi_df(antibiotics = c("amox", "metr"))
+  rsi_df(ab = c("amox", "metr"))
 }
 }
 \seealso{

man/rsi_predict.Rd

@@ -53,7 +53,7 @@ tbl \%>\%
 library(dplyr)
 septic_patients \%>\%
   # get bacteria properties like genus and species
-  left_join_bactlist("bactid") \%>\% 
+  left_join_microorganisms("bactid") \%>\% 
   # calculate first isolates
   mutate(first_isolate = 
            first_isolate(.,

man/septic_patients.Rd

@@ -14,8 +14,8 @@
   \item{\code{age}}{age of the patient}
   \item{\code{sex}}{sex of the patient}
   \item{\code{patient_id}}{ID of the patient, first 10 characters of an SHA hash containing irretrievable information}
-  \item{\code{bactid}}{ID of microorganism, see \code{\link{bactlist}}}
+  \item{\code{bactid}}{ID of microorganism, see \code{\link{microorganisms}}}
-  \item{\code{peni:mupi}}{38 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}), these column names occur in \code{\link{antibiotics}} and can be translated with \code{\link{abname}}}
+  \item{\code{peni:mupi}}{38 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}); these column names occur in \code{\link{antibiotics}} and can be translated with \code{\link{abname}}}
 }}
 \source{
 MOLIS (LIS of Certe) - \url{https://www.certe.nl}
@@ -24,6 +24,46 @@ MOLIS (LIS of Certe) - \url{https://www.certe.nl}
 septic_patients
 }
 \description{
-An anonymised dataset containing 2000 microbial blood culture isolates with their antibiogram of septic patients found in 5 different hospitals in the Netherlands, between 2001 and 2017. This data.frame can be used to practice AMR analysis e.g. with \code{\link{rsi}} or \code{\link{rsi_predict}}, or it can be used to practice other statistics.
+An anonymised dataset containing 2000 microbial blood culture isolates with their antibiogram of septic patients found in 5 different hospitals in the Netherlands, between 2001 and 2017. This data.frame can be used to practice AMR analysis. For examples, press F1.
+}
+\examples{
+# ----------- #
+# PREPARATION #
+# ----------- #
+
+# Save this example dataset to an object, so we can edit it:
+my_data <- septic_patients
+
+# load the dplyr package to make data science A LOT easier
+library(dplyr)
+
+# Add first isolates to our dataset:
+my_data <- my_data \%>\% 
+  mutate(first_isolates = first_isolate(my_data, date, patient_id, bactid))
+
+# -------- #
+# ANALYSIS #
+# -------- #
+
+# 1. Get the amoxicillin resistance percentages 
+#    of E. coli, divided by hospital:
+
+my_data \%>\%
+  filter(bactid == "ESCCOL",
+         first_isolates == TRUE) \%>\% 
+  group_by(hospital_id) \%>\% 
+  summarise(n = n(),
+            amoxicillin_resistance = rsi(amox))
+  
+  
+# 2. Get the amoxicillin/clavulanic acid resistance 
+#    percentages of E. coli, trend over the years:
+
+my_data \%>\% 
+  filter(bactid == guess_bactid("E. coli"),
+         first_isolates == TRUE) \%>\% 
+  group_by(year = format(date, "\%Y")) \%>\% 
+  summarise(n = n(),
+            amoxclav_resistance = rsi(amcl, minimum = 20))
 }
 \keyword{datasets}