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mo codes for WHONET

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dr. M.S. (Matthijs) Berends 2019-02-08 16:06:54 +01:00
parent 3d3366faf7
commit ed30312048
60 changed files with 1103 additions and 615 deletions
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4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR Package: AMR
Version: 0.5.0.9016 Version: 0.5.0.9017
Date: 2019-02-04 Date: 2019-02-08
Title: Antimicrobial Resistance Analysis Title: Antimicrobial Resistance Analysis
Authors@R: c( Authors@R: c(
person( person(

2
NAMESPACE
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@ -128,6 +128,7 @@ export(mo_subkingdom)
export(mo_subspecies) export(mo_subspecies)
export(mo_taxonomy) export(mo_taxonomy)
export(mo_type) export(mo_type)
export(mo_uncertainties)
export(mo_year) export(mo_year)
export(mrgn) export(mrgn)
export(n_rsi) export(n_rsi)
@ -195,6 +196,7 @@ importFrom(crayon,black)
importFrom(crayon,blue) importFrom(crayon,blue)
importFrom(crayon,bold) importFrom(crayon,bold)
importFrom(crayon,green) importFrom(crayon,green)
importFrom(crayon,has_color)
importFrom(crayon,italic) importFrom(crayon,italic)
importFrom(crayon,magenta) importFrom(crayon,magenta)
importFrom(crayon,red) importFrom(crayon,red)

14
NEWS.md
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@ -6,6 +6,7 @@
* Support for data from [WHONET](https://whonet.org/) and [EARS-Net](https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net) (European Antimicrobial Resistance Surveillance Network): * Support for data from [WHONET](https://whonet.org/) and [EARS-Net](https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net) (European Antimicrobial Resistance Surveillance Network):
* Exported files from WHONET can be read and used in this package. For functions like `first_isolate()` and `eucast_rules()`, all parameters will be filled in automatically. * Exported files from WHONET can be read and used in this package. For functions like `first_isolate()` and `eucast_rules()`, all parameters will be filled in automatically.
* This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the `antibiotics` data set now contains a column `ears_net`. * This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the `antibiotics` data set now contains a column `ears_net`.
* The function `as.mo()` now knows all WHONET species abbreviations too, because more than 1,600 microbial abbreviations were added to the `microorganisms.codes` data set.
* All `ab_*` functions are deprecated and replaced by `atc_*` functions: * All `ab_*` functions are deprecated and replaced by `atc_*` functions:
```r ```r
ab_property -> atc_property() ab_property -> atc_property()
@ -24,6 +25,7 @@
* Support for the upcoming [`dplyr`](https://dplyr.tidyverse.org) version 0.8.0 * Support for the upcoming [`dplyr`](https://dplyr.tidyverse.org) version 0.8.0
* New function `guess_ab_col()` to find an antibiotic column in a table * New function `guess_ab_col()` to find an antibiotic column in a table
* New function `mo_failures()` to review values that could not be coerced to a valid MO code, using `as.mo()`. This latter function will now only show a maximum of 10 uncoerced values and will refer to `mo_failures()`. * New function `mo_failures()` to review values that could not be coerced to a valid MO code, using `as.mo()`. This latter function will now only show a maximum of 10 uncoerced values and will refer to `mo_failures()`.
* New function `mo_uncertainties()` to review values that could be coerced to a valid MO code using `as.mo()`, but with uncertainty.
* New function `mo_renamed()` to get a list of all returned values from `as.mo()` that have had taxonomic renaming * New function `mo_renamed()` to get a list of all returned values from `as.mo()` that have had taxonomic renaming
* New function `age()` to calculate the (patients) age in years * New function `age()` to calculate the (patients) age in years
* New function `age_groups()` to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group. * New function `age_groups()` to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.
@ -46,23 +48,27 @@
filter(only_firsts == TRUE) %>% filter(only_firsts == TRUE) %>%
select(-only_firsts) select(-only_firsts)
``` ```
* New function `availability()` to check the number of available (non-empty) results in a `data.frame`
* New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the *G*-test and more. These are also available (and even easier readable) on our website: https://msberends.gitlab.io/AMR. * New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the *G*-test and more. These are also available (and even easier readable) on our website: https://msberends.gitlab.io/AMR.
#### Changed #### Changed
* Function `eucast_rules()`:
* Updated EUCAST Clinical breakpoints to [version 9.0 of 1 January 2019](http://www.eucast.org/clinical_breakpoints/), the data set `septic_patients` now reflects these changes
* Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately
* Emphasised in manual that penicillin is meant as benzylpenicillin (ATC [J01CE01](https://www.whocc.no/atc_ddd_index/?code=J01CE01))
* New info is returned when running this function, stating exactly what has been changed or added. Use `eucast_rules(..., verbose = TRUE)` to get a data set with all changed per bug and drug combination.
* Added 605 *Aspergillus* species and 23 *Trichophyton* species to the `microorganisms` data set
* Added 65 antibiotics to the `antibiotics` data set, from the [Pharmaceuticals Community Register](http://ec.europa.eu/health/documents/community-register/html/atc.htm) of the European Commission * Added 65 antibiotics to the `antibiotics` data set, from the [Pharmaceuticals Community Register](http://ec.europa.eu/health/documents/community-register/html/atc.htm) of the European Commission
* Removed columns `atc_group1_nl` and `atc_group2_nl` from the `antibiotics` data set * Removed columns `atc_group1_nl` and `atc_group2_nl` from the `antibiotics` data set
* Functions `atc_ddd()` and `atc_groups()` have been renamed `atc_online_ddd()` and `atc_online_groups()`. The old functions are deprecated and will be removed in a future version. * Functions `atc_ddd()` and `atc_groups()` have been renamed `atc_online_ddd()` and `atc_online_groups()`. The old functions are deprecated and will be removed in a future version.
* Function `guess_mo()` is now deprecated in favour of `as.mo()` and will be removed in future versions * Function `guess_mo()` is now deprecated in favour of `as.mo()` and will be removed in future versions
* Function `guess_atc()` is now deprecated in favour of `as.atc()` and will be removed in future versions * Function `guess_atc()` is now deprecated in favour of `as.atc()` and will be removed in future versions
* Function `eucast_rules()`:
* Updated EUCAST Clinical breakpoints to [version 9.0 of 1 January 2019](http://www.eucast.org/clinical_breakpoints/)
* Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately
* Emphasised in manual that penicillin is meant as benzylpenicillin (ATC [J01CE01](https://www.whocc.no/atc_ddd_index/?code=J01CE01))
* Improvements for `as.mo()`: * Improvements for `as.mo()`:
* Fix for vector containing only empty values * Fix for vector containing only empty values
* Finds better results when input is in other languages * Finds better results when input is in other languages
* Better handling for subspecies * Better handling for subspecies
* Better handling for *Salmonellae* * Better handling for *Salmonellae*
* Understanding of highly virulent *E. coli* strains like EIEC, EPEC and STEC
* There will be looked for uncertain results at default - these results will be returned with an informative warning * There will be looked for uncertain results at default - these results will be returned with an informative warning
* Manual now contains more info about the algorithms * Manual now contains more info about the algorithms
* Progress bar will be shown when it takes more than 3 seconds to get results * Progress bar will be shown when it takes more than 3 seconds to get results

38
R/data.R
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@ -134,7 +134,7 @@
#' #'
#' A data set containing the complete microbial taxonomy of the kingdoms Bacteria, Fungi and Protozoa from ITIS. MO codes can be looked up using \code{\link{as.mo}}. #' A data set containing the complete microbial taxonomy of the kingdoms Bacteria, Fungi and Protozoa from ITIS. MO codes can be looked up using \code{\link{as.mo}}.
#' @inheritSection ITIS ITIS #' @inheritSection ITIS ITIS
#' @format A \code{\link{data.frame}} with 18,833 observations and 15 variables: #' @format A \code{\link{data.frame}} with 19,456 observations and 15 variables:
#' \describe{ #' \describe{
#' \item{\code{mo}}{ID of microorganism} #' \item{\code{mo}}{ID of microorganism}
#' \item{\code{tsn}}{Taxonomic Serial Number (TSN), as defined by ITIS} #' \item{\code{tsn}}{Taxonomic Serial Number (TSN), as defined by ITIS}
@ -153,6 +153,17 @@
#' \item{\code{ref}}{Author(s) and year of concerning publication as found in ITIS, see Source} #' \item{\code{ref}}{Author(s) and year of concerning publication as found in ITIS, see Source}
#' } #' }
#' @source Integrated Taxonomic Information System (ITIS) public online database, \url{https://www.itis.gov}. #' @source Integrated Taxonomic Information System (ITIS) public online database, \url{https://www.itis.gov}.
#' @details Manually added were:
#' \itemize{
#' \item{605 species of Aspergillus (as Aspergillus misses from ITIS, list from https://en.wikipedia.org/wiki/List_of_Aspergillus_species on 2019-02-05)}
#' \item{23 species of Trichophyton (as Trichophyton misses from ITIS, list from https://en.wikipedia.org/wiki/Trichophyton on 2019-02-05)}
#' \item{9 species of Streptococcus (beta haemolytic groups A, B, C, D, F, G, H, K and unspecified)}
#' \item{2 species of Straphylococcus (coagulase-negative [CoNS] and coagulase-positive [CoPS])}
#' \item{1 species of Candida (C. glabrata)}
#' \item{2 other undefined (unknown Gram negatives and unknown Gram positives)}
#' }
#'
#' These manual entries have no Taxonomic Serial Number (TSN), so can be looked up with \code{filter(microorganisms, is.na(tsn)}.
#' @inheritSection AMR Read more on our website! #' @inheritSection AMR Read more on our website!
#' @seealso \code{\link{as.mo}} \code{\link{mo_property}} \code{\link{microorganisms.codes}} #' @seealso \code{\link{as.mo}} \code{\link{mo_property}} \code{\link{microorganisms.codes}}
"microorganisms" "microorganisms"
@ -175,12 +186,13 @@
#' Translation table for microorganism codes #' Translation table for microorganism codes
#' #'
#' A data set containing commonly used codes for microorganisms. Define your own with \code{\link{set_mo_source}}. #' A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with \code{\link{set_mo_source}}.
#' @format A \code{\link{data.frame}} with 3,303 observations and 2 variables: #' @format A \code{\link{data.frame}} with 4,731 observations and 2 variables:
#' \describe{ #' \describe{
#' \item{\code{certe}}{Commonly used code of a microorganism} #' \item{\code{certe}}{Commonly used code of a microorganism}
#' \item{\code{mo}}{Code of microorganism in \code{\link{microorganisms}}} #' \item{\code{mo}}{ID of the microorganism in the \code{\link{microorganisms}} data set}
#' } #' }
#' @inheritSection ITIS ITIS
#' @inheritSection AMR Read more on our website! #' @inheritSection AMR Read more on our website!
#' @seealso \code{\link{as.mo}} \code{\link{microorganisms}} #' @seealso \code{\link{as.mo}} \code{\link{microorganisms}}
"microorganisms.codes" "microorganisms.codes"
@ -246,17 +258,21 @@
#' @name supplementary_data #' @name supplementary_data
#' @inheritSection AMR Read more on our website! #' @inheritSection AMR Read more on our website!
# # Renew data: # # Renew data:
# # sorted on (1) bacteria, (2) fungi, (3) protozoa and then human pathogenic prevalence and then TSN:
# microorganismsDT <- data.table::as.data.table(AMR::microorganisms) # microorganismsDT <- data.table::as.data.table(AMR::microorganisms)
# # sort on (1) bacteria, (2) fungi, (3) protozoa and then human pathogenic prevalence and then TSN:
# data.table::setkey(microorganismsDT, kingdom, prevalence, fullname) # data.table::setkey(microorganismsDT, kingdom, prevalence, fullname)
# microorganisms.prevDT <- microorganismsDT[prevalence == 9999,] # microorganisms.prevDT <- microorganismsDT[prevalence != 9999,]
# microorganisms.unprevDT <- microorganismsDT[prevalence != 9999,] # microorganisms.unprevDT <- microorganismsDT[prevalence == 9999,]
# microorganisms.oldDT <- data.table::as.data.table(AMR::microorganisms.old) # microorganisms.oldDT <- data.table::as.data.table(AMR::microorganisms.old)
# data.table::setkey(microorganisms.oldDT, tsn, name) # data.table::setkey(microorganisms.oldDT, tsn, name)
# devtools::use_data(microorganismsDT, overwrite = TRUE) # usethis::use_data(microorganismsDT, overwrite = TRUE)
# devtools::use_data(microorganisms.prevDT, overwrite = TRUE) # usethis::use_data(microorganisms.prevDT, overwrite = TRUE)
# devtools::use_data(microorganisms.unprevDT, overwrite = TRUE) # usethis::use_data(microorganisms.unprevDT, overwrite = TRUE)
# devtools::use_data(microorganisms.oldDT, overwrite = TRUE) # usethis::use_data(microorganisms.oldDT, overwrite = TRUE)
# rm(microorganismsDT)
# rm(microorganisms.prevDT)
# rm(microorganisms.unprevDT)
# rm(microorganisms.oldDT)
"microorganismsDT" "microorganismsDT"
#' @rdname supplementary_data #' @rdname supplementary_data

166
R/eucast_rules.R
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@ -25,7 +25,7 @@
#' @param tbl table with antibiotic columns, like e.g. \code{amox} and \code{amcl} #' @param tbl table with antibiotic columns, like e.g. \code{amox} and \code{amcl}
#' @param info print progress #' @param info print progress
#' @param rules a character vector that specifies which rules should be applied - one or more of \code{c("breakpoints", "expert", "other", "all")} #' @param rules a character vector that specifies which rules should be applied - one or more of \code{c("breakpoints", "expert", "other", "all")}
#' @param verbose a logical to indicate whether extensive info should be returned as a \code{data.frame} with info about which rows and columns are effected #' @param verbose a logical to indicate whether extensive info should be returned as a \code{data.frame} with info about which rows and columns are effected. It runs all EUCAST rules, but will not be applied to an output - only an informative \code{data.frame} with changes will be returned as output.
#' @param amcl,amik,amox,ampi,azit,azlo,aztr,cefa,cfep,cfot,cfox,cfra,cfta,cftr,cfur,chlo,cipr,clar,clin,clox,coli,czol,dapt,doxy,erta,eryt,fosf,fusi,gent,imip,kana,levo,linc,line,mero,mezl,mino,moxi,nali,neom,neti,nitr,norf,novo,oflo,oxac,peni,pipe,pita,poly,pris,qida,rifa,roxi,siso,teic,tetr,tica,tige,tobr,trim,trsu,vanc column name of an antibiotic, see Antibiotics #' @param amcl,amik,amox,ampi,azit,azlo,aztr,cefa,cfep,cfot,cfox,cfra,cfta,cftr,cfur,chlo,cipr,clar,clin,clox,coli,czol,dapt,doxy,erta,eryt,fosf,fusi,gent,imip,kana,levo,linc,line,mero,mezl,mino,moxi,nali,neom,neti,nitr,norf,novo,oflo,oxac,peni,pipe,pita,poly,pris,qida,rifa,roxi,siso,teic,tetr,tica,tige,tobr,trim,trsu,vanc column name of an antibiotic, see Antibiotics
#' @param ... parameters that are passed on to \code{eucast_rules} #' @param ... parameters that are passed on to \code{eucast_rules}
#' @inheritParams first_isolate #' @inheritParams first_isolate
@ -101,7 +101,7 @@
#' @export #' @export
#' @importFrom dplyr %>% select pull mutate_at vars #' @importFrom dplyr %>% select pull mutate_at vars
#' @importFrom crayon bold bgGreen bgYellow bgRed black green blue italic strip_style #' @importFrom crayon bold bgGreen bgYellow bgRed black green blue italic strip_style
#' @return The input of \code{tbl}, possibly with edited values of antibiotics. Or, if \code{verbose = TRUE}, a \code{data.frame} with verbose info. #' @return The input of \code{tbl}, possibly with edited values of antibiotics. Or, if \code{verbose = TRUE}, a \code{data.frame} with all original and new values of the affected bug-drug combinations.
#' @source #' @source
#' \itemize{ #' \itemize{
#' \item{ #' \item{
@ -144,7 +144,9 @@
#' # 4 Klebsiella pneumoniae - - - - - S S #' # 4 Klebsiella pneumoniae - - - - - S S
#' # 5 Pseudomonas aeruginosa - - - - - S S #' # 5 Pseudomonas aeruginosa - - - - - S S
#' #'
#' b <- eucast_rules(a, "mo") # 18 results are forced as R or S #'
#' # apply EUCAST rules: 18 results are forced as R or S
#' b <- eucast_rules(a)
#' #'
#' b #' b
#' # mo vanc amox coli cfta cfur peni cfox #' # mo vanc amox coli cfta cfur peni cfox
@ -153,6 +155,11 @@
#' # 3 Escherichia coli R - - - - R S #' # 3 Escherichia coli R - - - - R S
#' # 4 Klebsiella pneumoniae R R - - - R S #' # 4 Klebsiella pneumoniae R R - - - R S
#' # 5 Pseudomonas aeruginosa R R - - R R R #' # 5 Pseudomonas aeruginosa R R - - R R R
#'
#'
#' # do not apply EUCAST rules, but rather get a a data.frame
#' # with 18 rows, containing all details about the transformations:
#' c <- eucast_rules(a, verbose = TRUE)
eucast_rules <- function(tbl, eucast_rules <- function(tbl,
col_mo = NULL, col_mo = NULL,
info = TRUE, info = TRUE,
@ -406,22 +413,31 @@ eucast_rules <- function(tbl,
trsu <- col.list[trsu] trsu <- col.list[trsu]
vanc <- col.list[vanc] vanc <- col.list[vanc]
number_changed <- 0 number_added_S <- 0
number_added_I <- 0
number_added_R <- 0
number_changed_to_S <- 0
number_changed_to_I <- 0
number_changed_to_R <- 0
number_affected_rows <- integer(0) number_affected_rows <- integer(0)
verbose_info <- data.frame(rule_type = character(0), verbose_info <- data.frame(row = integer(0),
rule_set = character(0), col = character(0),
force_to = character(0), mo = character(0),
found = integer(0), mo_fullname = character(0),
changed = integer(0), old = character(0),
target_columns = integer(0), new = character(0),
target_rows = integer(0), rule_source = character(0),
rule_group = character(0),
stringsAsFactors = FALSE) stringsAsFactors = FALSE)
# helper function for editing the table # helper function for editing the table
edit_rsi <- function(to, rule, rows, cols) { edit_rsi <- function(to, rule, rows, cols) {
cols <- unique(cols[!is.na(cols) & !is.null(cols)]) cols <- unique(cols[!is.na(cols) & !is.null(cols)])
if (length(rows) > 0 & length(cols) > 0) { if (length(rows) > 0 & length(cols) > 0) {
before_df <- tbl_original
before <- as.character(unlist(as.list(tbl_original[rows, cols]))) before <- as.character(unlist(as.list(tbl_original[rows, cols])))
tryCatch( tryCatch(
# insert into original table # insert into original table
tbl_original[rows, cols] <<- to, tbl_original[rows, cols] <<- to,
@ -442,29 +458,81 @@ eucast_rules <- function(tbl,
suppressWarnings( suppressWarnings(
tbl[rows, cols] <<- to tbl[rows, cols] <<- to
)) ))
after <- as.character(unlist(as.list(tbl_original[rows, cols]))) after <- as.character(unlist(as.list(tbl_original[rows, cols])))
number_changed <<- number_changed + sum(before != after, na.rm = TRUE)
tbl[rows, cols] <<- tbl_original[rows, cols]
number_newly_added_S <- sum(!before %in% c("S", "I", "R") & after == "S", na.rm = TRUE)
number_newly_added_I <- sum(!before %in% c("S", "I", "R") & after == "I", na.rm = TRUE)
number_newly_added_R <- sum(!before %in% c("S", "I", "R") & after == "R", na.rm = TRUE)
number_newly_changed_to_S <- sum(before %in% c("I", "R") & after == "S", na.rm = TRUE)
number_newly_changed_to_I <- sum(before %in% c("S", "R") & after == "I", na.rm = TRUE)
number_newly_changed_to_R <- sum(before %in% c("S", "I") & after == "R", na.rm = TRUE)
# totals
number_added_S <<- number_added_S + number_newly_added_S
number_added_I <<- number_added_I + number_newly_added_I
number_added_R <<- number_added_R + number_newly_added_R
number_changed_to_S <<- number_changed_to_S + number_newly_changed_to_S
number_changed_to_I <<- number_changed_to_I + number_newly_changed_to_I
number_changed_to_R <<- number_changed_to_R + number_newly_changed_to_R
number_affected_rows <<- unique(c(number_affected_rows, rows)) number_affected_rows <<- unique(c(number_affected_rows, rows))
changed_results <<- changed_results + sum(before != after, na.rm = TRUE) # will be reset at start of every rule
# will be reset at start of every rule
changed_results <<- changed_results +
number_newly_added_S +
number_newly_added_I +
number_newly_added_R +
number_newly_changed_to_S +
number_newly_changed_to_I +
number_newly_changed_to_R
if (verbose == TRUE) { if (verbose == TRUE) {
for (i in 1:length(cols)) { for (r in 1:length(rows)) {
# add new row for every affected column for (c in 1:length(cols)) {
verbose_new <- data.frame(rule_type = strip_style(rule[1]), old <- before_df[rows[r], cols[c]]
rule_set = strip_style(rule[2]), new <- tbl[rows[r], cols[c]]
force_to = to, if (!identical(old, new)) {
found = length(before), verbose_new <- data.frame(row = rows[r],
changed = sum(before != after, na.rm = TRUE), col = cols[c],
target_column = cols[i], mo = tbl_original[rows[r], col_mo],
mo_fullname = "",
old = old,
new = new,
rule_source = strip_style(rule[1]),
rule_group = strip_style(rule[2]),
stringsAsFactors = FALSE) stringsAsFactors = FALSE)
verbose_new$target_rows <- list(unname(rows))
rownames(verbose_new) <- NULL
verbose_info <<- rbind(verbose_info, verbose_new) verbose_info <<- rbind(verbose_info, verbose_new)
} }
}
}
# verbose_new <- data.frame(row = integer(0),
# col = character(0),
# old = character(0),
# new = character(0),
# rule_source = character(0),
# rule_group = character(0),
# stringsAsFactors = FALSE)
# a <<- rule
# for (i in 1:length(cols)) {
# # add new row for every affected column
# verbose_new <- data.frame(rule_type = strip_style(rule[1]),
# rule_set = strip_style(rule[2]),
# force_to = to,
# found = length(before),
# changed = sum(before != after, na.rm = TRUE),
# target_column = cols[i],
# stringsAsFactors = FALSE)
# verbose_new$target_rows <- list(unname(rows))
# rownames(verbose_new) <- NULL
# verbose_info <<- rbind(verbose_info, verbose_new)
# }
} }
} }
} }
na.rm <- function(col) { na.rm <- function(col) {
if (is.null(col)) { if (is.null(col)) {
"" ""
@ -489,15 +557,15 @@ eucast_rules <- function(tbl,
# since ampicillin ^= amoxicillin, get the first from the latter (not in original EUCAST table) # since ampicillin ^= amoxicillin, get the first from the latter (not in original EUCAST table)
if (!is.null(ampi) & !is.null(amox)) { if (!is.null(ampi) & !is.null(amox)) {
if (verbose == TRUE) { if (verbose == TRUE) {
cat(bgGreen("\n VERBOSE: transforming", cat("\n VERBOSE: transforming",
length(which(tbl[, amox] == "S" & !tbl[, ampi] %in% c("S", "I", "R"))), length(which(tbl[, amox] == "S" & !tbl[, ampi] %in% c("S", "I", "R"))),
"empty ampicillin fields to 'S' based on amoxicillin. ")) "empty ampicillin fields to 'S' based on amoxicillin. ")
cat(bgGreen("\n VERBOSE: transforming", cat("\n VERBOSE: transforming",
length(which(tbl[, amox] == "I" & !tbl[, ampi] %in% c("S", "I", "R"))), length(which(tbl[, amox] == "I" & !tbl[, ampi] %in% c("S", "I", "R"))),
"empty ampicillin fields to 'I' based on amoxicillin. ")) "empty ampicillin fields to 'I' based on amoxicillin. ")
cat(bgGreen("\n VERBOSE: transforming", cat("\n VERBOSE: transforming",
length(which(tbl[, amox] == "R" & !tbl[, ampi] %in% c("S", "I", "R"))), length(which(tbl[, amox] == "R" & !tbl[, ampi] %in% c("S", "I", "R"))),
"empty ampicillin fields to 'R' based on amoxicillin. \n")) "empty ampicillin fields to 'R' based on amoxicillin. \n")
} }
tbl[which(tbl[, amox] == "S" & !tbl[, ampi] %in% c("S", "I", "R")), ampi] <- "S" tbl[which(tbl[, amox] == "S" & !tbl[, ampi] %in% c("S", "I", "R")), ampi] <- "S"
tbl[which(tbl[, amox] == "I" & !tbl[, ampi] %in% c("S", "I", "R")), ampi] <- "I" tbl[which(tbl[, amox] == "I" & !tbl[, ampi] %in% c("S", "I", "R")), ampi] <- "I"
@ -1804,22 +1872,46 @@ eucast_rules <- function(tbl,
} else { } else {
wouldve <- "" wouldve <- ""
} }
if (number_changed == 0) { if (sum(number_added_S, number_added_I, number_added_R,
colour <- green number_changed_to_S, number_changed_to_I, number_changed_to_R,
na.rm = TRUE) == 0) {
colour <- green # is function
} else { } else {
colour <- blue colour <- blue # is function
} }
decimal.mark <- getOption("OutDec") decimal.mark <- getOption("OutDec")
big.mark <- ifelse(decimal.mark != ",", ",", ".") big.mark <- ifelse(decimal.mark != ",", ",", ".")
formatnr <- function(x) {
format(x, big.mark = big.mark, decimal.mark = decimal.mark)
}
cat(bold(paste('\n=> EUCAST rules', paste0(wouldve, 'affected'), cat(bold(paste('\n=> EUCAST rules', paste0(wouldve, 'affected'),
number_affected_rows %>% length() %>% format(big.mark = big.mark, decimal.mark = decimal.mark), number_affected_rows %>% length() %>% formatnr(),
'out of', nrow(tbl_original) %>% format(big.mark = big.mark, decimal.mark = decimal.mark), 'out of', nrow(tbl_original) %>% formatnr(),
'rows ->', 'rows\n')))
colour(paste0(wouldve, 'changed'), total_added <- number_added_S + number_added_I + number_added_R
number_changed %>% format(big.mark = big.mark, decimal.mark = decimal.mark), 'test results.\n\n')))) total_changed <- number_changed_to_S + number_changed_to_I + number_changed_to_R
cat(colour(paste0(" -> ", wouldve, "added ",
bold(formatnr(total_added), "test results"),
if(total_added > 0)
paste0(" (", formatnr(number_added_S), " as S; ",
formatnr(number_added_I), " as I; ",
formatnr(number_added_R), " as R)"),
"\n")))
cat(colour(paste0(" -> ", wouldve, "changed ",
bold(formatnr(total_changed), "test results"),
if(total_changed > 0)
paste0(" (", formatnr(number_changed_to_S), " to S; ",
formatnr(number_changed_to_I), " to I; ",
formatnr(number_changed_to_R), " to R)"),
"\n")))
} }
if (verbose == TRUE) { if (verbose == TRUE) {
suppressWarnings(
suppressMessages(
verbose_info$mo_fullname <- mo_fullname(verbose_info$mo)
)
)
return(verbose_info) return(verbose_info)
} }

36
R/freq.R
View File

@ -228,7 +228,7 @@ frequency_tbl <- function(x,
x.name <- x.name %>% strsplit("%>%", fixed = TRUE) %>% unlist() %>% .[1] %>% trimws() x.name <- x.name %>% strsplit("%>%", fixed = TRUE) %>% unlist() %>% .[1] %>% trimws()
} }
if (x.name == ".") { if (x.name == ".") {
x.name <- "a `data.frame`" x.name <- "a data.frame"
} else { } else {
x.name <- paste0("`", x.name, "`") x.name <- paste0("`", x.name, "`")
} }
@ -797,11 +797,30 @@ print.frequency_tbl <- function(x,
opt <- attr(x, "opt") opt <- attr(x, "opt")
opt$header_txt <- header(x) opt$header_txt <- header(x)
dots <- list(...)
if ("markdown" %in% names(dots)) {
if (dots$markdown == TRUE) {
opt$tbl_format <- "markdown"
} else {
opt$tbl_format <- "pandoc"
}
}
if (!missing(markdown)) {
if (markdown == TRUE) {
opt$tbl_format <- "markdown"
} else {
opt$tbl_format <- "pandoc"
}
}
if (length(opt$vars) == 0) { if (length(opt$vars) == 0) {
opt$vars <- NULL opt$vars <- NULL
} }
if (is.null(opt$title)) { if (is.null(opt$title)) {
if (isTRUE(opt$data %like% "^a data.frame") & opt$tbl_format == "markdown") {
opt$data <- gsub("data.frame", "`data.frame`", opt$data, fixed = TRUE)
}
if (!is.null(opt$data) & !is.null(opt$vars)) { if (!is.null(opt$data) & !is.null(opt$vars)) {
title <- paste0("`", paste0(opt$vars, collapse = "` and `"), "` from ", opt$data) title <- paste0("`", paste0(opt$vars, collapse = "` and `"), "` from ", opt$data)
} else if (!is.null(opt$data) & is.null(opt$vars)) { } else if (!is.null(opt$data) & is.null(opt$vars)) {
@ -845,21 +864,6 @@ print.frequency_tbl <- function(x,
if (!missing(big.mark)) { if (!missing(big.mark)) {
opt$big.mark <- big.mark opt$big.mark <- big.mark
} }
dots <- list(...)
if ("markdown" %in% names(dots)) {
if (dots$markdown == TRUE) {
opt$tbl_format <- "markdown"
} else {
opt$tbl_format <- "pandoc"
}
}
if (!missing(markdown)) {
if (markdown == TRUE) {
opt$tbl_format <- "markdown"
} else {
opt$tbl_format <- "pandoc"
}
}
if (!missing(header)) { if (!missing(header)) {
opt$header <- header opt$header <- header
} }

243
R/mo.R
View File

@ -54,7 +54,7 @@
#' #'
#' This function uses Artificial Intelligence (AI) to help getting fast and logical results. It tries to find matches in this order: #' This function uses Artificial Intelligence (AI) to help getting fast and logical results. It tries to find matches in this order:
#' \itemize{ #' \itemize{
#' \item{Taxonomic kingdom: it first searches in bacteria, then fungi, then protozoa} #' \item{Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa}
#' \item{Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones} #' \item{Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones}
#' \item{Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations} #' \item{Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations}
#' \item{Breakdown of input values: from here it starts to breakdown input values to find possible matches} #' \item{Breakdown of input values: from here it starts to breakdown input values to find possible matches}
@ -69,13 +69,30 @@
#' } #' }
#' This means that looking up human pathogenic microorganisms takes less time than looking up human \strong{non}-pathogenic microorganisms. #' This means that looking up human pathogenic microorganisms takes less time than looking up human \strong{non}-pathogenic microorganisms.
#' #'
#' When using \code{allow_uncertain = TRUE} (which is the default setting), it will use additional rules if all previous AI rules failed to get valid results. Examples: #' \strong{UNCERTAIN RESULTS} \cr
#' When using \code{allow_uncertain = TRUE} (which is the default setting), it will use additional rules if all previous AI rules failed to get valid results. These are:
#' \itemize{
#' \item{It tries to look for previously accepted (but now invalid) taxonomic names}
#' \item{It strips off values between brackets and the brackets itself, and re-evaluates the input with all previous rules}
#' \item{It strips off words from the end one by one and re-evaluates the input with all previous rules}
#' \item{It strips off words from the start one by one and re-evaluates the input with all previous rules}
#' \item{It tries to look for some manual changes which are not yet published to the ITIS database (like \emph{Propionibacterium} not yet being \emph{Cutibacterium})}
#' }
#'
#' Examples:
#' \itemize{ #' \itemize{
#' \item{\code{"Streptococcus group B (known as S. agalactiae)"}. The text between brackets will be removed and a warning will be thrown that the result \emph{Streptococcus group B} (\code{B_STRPTC_GRB}) needs review.} #' \item{\code{"Streptococcus group B (known as S. agalactiae)"}. The text between brackets will be removed and a warning will be thrown that the result \emph{Streptococcus group B} (\code{B_STRPTC_GRB}) needs review.}
#' \item{\code{"S. aureus - please mind: MRSA"}. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result \emph{Staphylococcus aureus} (\code{B_STPHY_AUR}) needs review.} #' \item{\code{"S. aureus - please mind: MRSA"}. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result \emph{Staphylococcus aureus} (\code{B_STPHY_AUR}) needs review.}
#' \item{\code{"D. spartina"}. This is the abbreviation of an old taxonomic name: \emph{Didymosphaeria spartinae} (the last "e" was missing from the input). This fungus was renamed to \emph{Leptosphaeria obiones}, so a warning will be thrown that this result (\code{F_LPTSP_OBI}) needs review.} #' \item{\code{"D. spartina"}. This is the abbreviation of an old taxonomic name: \emph{Didymosphaeria spartinae} (the last "e" was missing from the input). This fungus was renamed to \emph{Leptosphaeria obiones}, so a warning will be thrown that this result (\code{F_LPTSP_OBI}) needs review.}
#' \item{\code{"Fluoroquinolone-resistant Neisseria gonorrhoeae"}. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result \emph{Neisseria gonorrhoeae} (\code{B_NESSR_GON}) needs review.}
#' } #' }
#' #'
#' Use \code{mo_failures()} to get a vector with all values that could not be coerced to a valid value.
#'
#' Use \code{mo_uncertainties()} to get a vector with all values that were coerced to a valid value, but with uncertainty.
#'
#' Use \code{mo_renamed()} to get a vector with all values that could be coerced based on an old, previously accepted taxonomic name.
#'
#' @inheritSection ITIS ITIS #' @inheritSection ITIS ITIS
# (source as a section, so it can be inherited by other man pages) # (source as a section, so it can be inherited by other man pages)
#' @section Source: #' @section Source:
@ -154,7 +171,7 @@ is.mo <- function(x) {
#' @importFrom dplyr %>% pull left_join n_distinct progress_estimated filter #' @importFrom dplyr %>% pull left_join n_distinct progress_estimated filter
#' @importFrom data.table data.table as.data.table setkey #' @importFrom data.table data.table as.data.table setkey
#' @importFrom crayon magenta red italic #' @importFrom crayon magenta red silver italic has_color
exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
allow_uncertain = TRUE, reference_df = get_mo_source(), allow_uncertain = TRUE, reference_df = get_mo_source(),
property = "mo", clear_options = TRUE) { property = "mo", clear_options = TRUE) {
@ -170,6 +187,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
if (clear_options == TRUE) { if (clear_options == TRUE) {
options(mo_failures = NULL) options(mo_failures = NULL)
options(mo_uncertainties = NULL)
options(mo_renamed = NULL) options(mo_renamed = NULL)
} }
@ -194,6 +212,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
} }
notes <- character(0) notes <- character(0)
uncertainties <- character(0)
failures <- character(0) failures <- character(0)
x_input <- x x_input <- x
# only check the uniques, which is way faster # only check the uniques, which is way faster
@ -251,7 +270,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
x_backup <- trimws(x, which = "both") x_backup <- trimws(x, which = "both")
# remove spp and species # remove spp and species
x <- trimws(gsub(" +(spp.?|ssp.?|subsp.?|species)", " ", x_backup, ignore.case = TRUE), which = "both") x <- trimws(gsub(" +(spp.?|ssp.?|sp.? |ss ?.?|subsp.?|subspecies|biovar |serovar |species)", " ", x_backup, ignore.case = TRUE), which = "both")
x_species <- paste(x, "species") x_species <- paste(x, "species")
# translate to English for supported languages of mo_property # translate to English for supported languages of mo_property
x <- gsub("(Gruppe|gruppe|groep|grupo|gruppo|groupe)", "group", x, ignore.case = TRUE) x <- gsub("(Gruppe|gruppe|groep|grupo|gruppo|groupe)", "group", x, ignore.case = TRUE)
@ -259,6 +278,14 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
x <- gsub("(no MO)", "", x, fixed = TRUE) x <- gsub("(no MO)", "", x, fixed = TRUE)
# remove non-text in case of "E. coli" except dots and spaces # remove non-text in case of "E. coli" except dots and spaces
x <- gsub("[^.a-zA-Z0-9/ \\-]+", "", x) x <- gsub("[^.a-zA-Z0-9/ \\-]+", "", x)
# replace minus by a space
x <- gsub("-+", " ", x)
# replace hemolytic by haemolytic
x <- gsub("ha?emoly", "haemoly", x)
# place minus back in streptococci
x <- gsub("(alpha|beta|gamma) haemoly", "\\1-haemolytic", x)
# remove genus as first word
x <- gsub("^Genus ", "", x)
# but spaces before and after should be omitted # but spaces before and after should be omitted
x <- trimws(x, which = "both") x <- trimws(x, which = "both")
@ -272,13 +299,13 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
x <- gsub("[ .]+", ".*", x) x <- gsub("[ .]+", ".*", x)
# add start en stop regex # add start en stop regex
x <- paste0('^', x, '$') x <- paste0('^', x, '$')
x_withspaces_start <- paste0('^', x_withspaces) x_withspaces_start_only <- paste0('^', x_withspaces)
x_withspaces <- paste0('^', x_withspaces, '$') x_withspaces_start_end <- paste0('^', x_withspaces, '$')
# cat(paste0('x "', x, '"\n')) # cat(paste0('x "', x, '"\n'))
# cat(paste0('x_species "', x_species, '"\n')) # cat(paste0('x_species "', x_species, '"\n'))
# cat(paste0('x_withspaces_start "', x_withspaces_start, '"\n')) # cat(paste0('x_withspaces_start_only "', x_withspaces_start_only, '"\n'))
# cat(paste0('x_withspaces "', x_withspaces, '"\n')) # cat(paste0('x_withspaces_start_end "', x_withspaces_start_end, '"\n'))
# cat(paste0('x_backup "', x_backup, '"\n')) # cat(paste0('x_backup "', x_backup, '"\n'))
# cat(paste0('x_trimmed "', x_trimmed, '"\n')) # cat(paste0('x_trimmed "', x_trimmed, '"\n'))
# cat(paste0('x_trimmed_species "', x_trimmed_species, '"\n')) # cat(paste0('x_trimmed_species "', x_trimmed_species, '"\n'))
@ -290,16 +317,17 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
progress$tick()$print() progress$tick()$print()
if (identical(x_trimmed[i], "")) { if (tolower(x_trimmed[i]) %in% c("", "xxx", "other", "none", "unknown")) {
# empty values # empty and nonsense values, ignore without warning ("xxx" is WHONET code for 'no growth')
x[i] <- NA_character_ x[i] <- NA_character_
next next
} }
if (nchar(x_trimmed[i]) < 3) {
if (nchar(gsub("[^a-zA-Z]", "", x_trimmed[i])) < 3) {
# check if search term was like "A. species", then return first genus found with ^A # check if search term was like "A. species", then return first genus found with ^A
if (x_backup[i] %like% "species" | x_backup[i] %like% "spp[.]?") { if (x_backup[i] %like% "[a-z]+ species" | x_backup[i] %like% "[a-z] spp[.]?") {
# get mo code of first hit # get mo code of first hit
found <- microorganismsDT[fullname %like% x_withspaces_start[i], mo] found <- microorganismsDT[fullname %like% x_withspaces_start_only[i], mo]
if (length(found) > 0) { if (length(found) > 0) {
mo_code <- found[1L] %>% strsplit("_") %>% unlist() %>% .[1:2] %>% paste(collapse = "_") mo_code <- found[1L] %>% strsplit("_") %>% unlist() %>% .[1:2] %>% paste(collapse = "_")
found <- microorganismsDT[mo == mo_code, ..property][[1]] found <- microorganismsDT[mo == mo_code, ..property][[1]]
@ -316,14 +344,13 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
next next
} }
# no nonsense text if (x_trimmed[i] %like% "virus") {
if (toupper(x_trimmed[i]) %in% c('OTHER', 'NONE', 'UNKNOWN')) { # there is no fullname like virus, so don't try to coerce it
x[i] <- NA_character_ x[i] <- NA_character_
failures <- c(failures, x_backup[i]) failures <- c(failures, x_backup[i])
next next
} }
# translate known trivial abbreviations to genus + species ---- # translate known trivial abbreviations to genus + species ----
if (!is.na(x_trimmed[i])) { if (!is.na(x_trimmed[i])) {
if (toupper(x_trimmed[i]) %in% c('MRSA', 'MSSA', 'VISA', 'VRSA')) { if (toupper(x_trimmed[i]) %in% c('MRSA', 'MSSA', 'VISA', 'VRSA')) {
@ -339,6 +366,10 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
x[i] <- microorganismsDT[mo == 'B_ENTRC', ..property][[1]][1L] x[i] <- microorganismsDT[mo == 'B_ENTRC', ..property][[1]][1L]
next next
} }
if (toupper(x_trimmed[i]) %in% c('EHEC', 'EPEC', 'EIEC', 'STEC', 'ATEC')) {
x[i] <- microorganismsDT[mo == 'B_ESCHR_COL', ..property][[1]][1L]
next
}
if (toupper(x_trimmed[i]) == 'MRPA') { if (toupper(x_trimmed[i]) == 'MRPA') {
# multi resistant P. aeruginosa # multi resistant P. aeruginosa
x[i] <- microorganismsDT[mo == 'B_PDMNS_AER', ..property][[1]][1L] x[i] <- microorganismsDT[mo == 'B_PDMNS_AER', ..property][[1]][1L]
@ -398,13 +429,25 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
next next
} }
if (grepl("[sS]almonella [A-Z][a-z]+ ?.*", x_trimmed[i])) { if (grepl("[sS]almonella [A-Z][a-z]+ ?.*", x_trimmed[i])) {
if (x_trimmed[i] %like% "Salmonella group") {
# Salmonella Group A to Z, just return S. species for now
x[i] <- microorganismsDT[mo == 'B_SLMNL', ..property][[1]][1L]
notes <- c(notes,
magenta(paste0("Note: ",
italic("Salmonella"), " ", trimws(gsub("Salmonella", "", x_trimmed[i])),
" was considered ",
italic("Salmonella species"),
" (B_SLMNL)")))
} else {
# Salmonella with capital letter species like "Salmonella Goettingen" - they're all S. enterica # Salmonella with capital letter species like "Salmonella Goettingen" - they're all S. enterica
x[i] <- microorganismsDT[mo == 'B_SLMNL_ENT', ..property][[1]][1L] x[i] <- microorganismsDT[mo == 'B_SLMNL_ENT', ..property][[1]][1L]
notes <- c(notes, notes <- c(notes,
magenta(paste0("Note: ", italic(x_trimmed[i]), magenta(paste0("Note: ",
" was considered (a subspecies of) ", italic("Salmonella"), " ", trimws(gsub("Salmonella", "", x_trimmed[i])),
" was considered a subspecies of ",
italic("Salmonella enterica"), italic("Salmonella enterica"),
" (B_SLMNL_ENT)"))) " (B_SLMNL_ENT)")))
}
next next
} }
} }
@ -417,14 +460,14 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
x[i] <- found[1L] x[i] <- found[1L]
next next
} }
if (nchar(x_trimmed[i]) > 4) { if (nchar(x_trimmed[i]) >= 6) {
# not when abbr is esco, stau, klpn, etc. found <- microorganismsDT[tolower(fullname) %like% paste0(x_withspaces_start_only[i], "[a-z]+ species"), ..property][[1]]
found <- microorganismsDT[tolower(fullname) %like% gsub(" ", ".*", x_trimmed_species[i], fixed = TRUE), ..property][[1]]
if (length(found) > 0) { if (length(found) > 0) {
x[i] <- found[1L] x[i] <- found[1L]
next next
} }
} }
# rest of genus only is in allow_uncertain part.
} }
# TRY OTHER SOURCES ---- # TRY OTHER SOURCES ----
@ -472,29 +515,27 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
next next
} }
# try any match keeping spaces ---- # try any match keeping spaces ----
found <- microorganisms.prevDT[fullname %like% x_withspaces[i], ..property][[1]] found <- microorganisms.prevDT[fullname %like% x_withspaces_start_end[i], ..property][[1]]
if (length(found) > 0) { if (length(found) > 0 & nchar(x_trimmed[i]) >= 6) {
x[i] <- found[1L] x[i] <- found[1L]
next next
} }
# try any match keeping spaces, not ending with $ ---- # try any match keeping spaces, not ending with $ ----
found <- microorganisms.prevDT[fullname %like% x_withspaces_start[i], ..property][[1]] found <- microorganisms.prevDT[fullname %like% x_withspaces_start_only[i], ..property][[1]]
if (length(found) > 0) { if (length(found) > 0 & nchar(x_trimmed[i]) >= 6) {
x[i] <- found[1L] x[i] <- found[1L]
next next
} }
# try any match diregarding spaces ---- # try any match diregarding spaces ----
found <- microorganisms.prevDT[fullname %like% x[i], ..property][[1]] found <- microorganisms.prevDT[fullname %like% x[i], ..property][[1]]
if (length(found) > 0) { if (length(found) > 0 & nchar(x_trimmed[i]) >= 6) {
x[i] <- found[1L] x[i] <- found[1L]
next next
} }
# try splitting of characters in the middle and then find ID ---- # try splitting of characters in the middle and then find ID ----
# only when text length is 6 or lower # only when text length is 6 or lower
# like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus, staaur = S. aureus # like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus, staaur = S. aureus
@ -512,7 +553,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
# try fullname without start and stop regex, to also find subspecies ---- # try fullname without start and stop regex, to also find subspecies ----
# like "K. pneu rhino" >> "Klebsiella pneumoniae (rhinoscleromatis)" = KLEPNERH # like "K. pneu rhino" >> "Klebsiella pneumoniae (rhinoscleromatis)" = KLEPNERH
found <- microorganisms.prevDT[fullname %like% x_withspaces_start[i], ..property][[1]] found <- microorganisms.prevDT[fullname %like% x_withspaces_start_only[i], ..property][[1]]
if (length(found) > 0) { if (length(found) > 0) {
x[i] <- found[1L] x[i] <- found[1L]
next next
@ -549,13 +590,13 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
next next
} }
# try any match keeping spaces ---- # try any match keeping spaces ----
found <- microorganisms.unprevDT[fullname %like% x_withspaces[i], ..property][[1]] found <- microorganisms.unprevDT[fullname %like% x_withspaces_start_end[i], ..property][[1]]
if (length(found) > 0) { if (length(found) > 0) {
x[i] <- found[1L] x[i] <- found[1L]
next next
} }
# try any match keeping spaces, not ending with $ ---- # try any match keeping spaces, not ending with $ ----
found <- microorganisms.unprevDT[fullname %like% x_withspaces_start[i], ..property][[1]] found <- microorganisms.unprevDT[fullname %like% x_withspaces_start_only[i], ..property][[1]]
if (length(found) > 0) { if (length(found) > 0) {
x[i] <- found[1L] x[i] <- found[1L]
next next
@ -583,7 +624,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
# try fullname without start and stop regex, to also find subspecies ---- # try fullname without start and stop regex, to also find subspecies ----
# like "K. pneu rhino" >> "Klebsiella pneumoniae (rhinoscleromatis)" = KLEPNERH # like "K. pneu rhino" >> "Klebsiella pneumoniae (rhinoscleromatis)" = KLEPNERH
found <- microorganisms.unprevDT[fullname %like% x_withspaces_start[i], ..property][[1]] found <- microorganisms.unprevDT[fullname %like% x_withspaces_start_only[i], ..property][[1]]
if (length(found) > 0) { if (length(found) > 0) {
x[i] <- found[1L] x[i] <- found[1L]
next next
@ -594,7 +635,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
# look for old taxonomic names ---- # look for old taxonomic names ----
found <- microorganisms.oldDT[tolower(name) == tolower(x_backup[i]) found <- microorganisms.oldDT[tolower(name) == tolower(x_backup[i])
| tsn == x_trimmed[i] | tsn == x_trimmed[i]
| name %like% x_withspaces[i],] | name %like% x_withspaces_start_end[i],]
if (NROW(found) > 0) { if (NROW(found) > 0) {
# when property is "ref" (which is the case in mo_ref, mo_authors and mo_year), return the old value, so: # when property is "ref" (which is the case in mo_ref, mo_authors and mo_year), return the old value, so:
# mo_ref("Chlamydia psittaci) = "Page, 1968" (with warning) # mo_ref("Chlamydia psittaci) = "Page, 1968" (with warning)
@ -604,22 +645,36 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
} else { } else {
x[i] <- microorganismsDT[tsn == found[1, tsn_new], ..property][[1]] x[i] <- microorganismsDT[tsn == found[1, tsn_new], ..property][[1]]
} }
notes <- c(notes, was_renamed(name_old = found[1, name],
renamed_note(name_old = found[1, name],
name_new = microorganismsDT[tsn == found[1, tsn_new], fullname], name_new = microorganismsDT[tsn == found[1, tsn_new], fullname],
ref_old = found[1, ref], ref_old = found[1, ref],
ref_new = microorganismsDT[tsn == found[1, tsn_new], ref], ref_new = microorganismsDT[tsn == found[1, tsn_new], ref],
mo = microorganismsDT[tsn == found[1, tsn_new], mo])) mo = microorganismsDT[tsn == found[1, tsn_new], mo])
next next
} }
# check for uncertain results ---- # check for uncertain results ----
if (allow_uncertain == TRUE) { if (allow_uncertain == TRUE) {
uncertain_fn <- function(a.x_backup, b.x_trimmed, c.x_withspaces, d.x_withspaces_start, e.x) { uncertain_fn <- function(a.x_backup, b.x_trimmed, c.x_withspaces_start_end, d.x_withspaces_start_only, e.x) {
# (1) look again for old taxonomic names, now for G. species ----
found <- microorganisms.oldDT[name %like% c.x_withspaces # (1) look for genus only, part of name ----
| name %like% d.x_withspaces_start if (nchar(b.x_trimmed) > 4 & !b.x_trimmed %like% " ") {
if (!grepl("^[A-Z][a-z]+", b.x_trimmed, ignore.case = FALSE)) {
# not when input is like Genustext, because then Neospora would lead to Actinokineospora
found <- microorganismsDT[tolower(fullname) %like% paste(b.x_trimmed, "species"), ..property][[1]]
if (length(found) > 0) {
x[i] <- found[1L]
uncertainties <<- c(uncertainties,
paste0("'", a.x_backup, "' >> ", microorganismsDT[mo == found[1L], fullname][[1]], " (", found[1L], ")"))
return(x)
}
}
}
# (2) look again for old taxonomic names, now for G. species ----
found <- microorganisms.oldDT[name %like% c.x_withspaces_start_end
| name %like% d.x_withspaces_start_only
| name %like% e.x,] | name %like% e.x,]
if (NROW(found) > 0 & nchar(b.x_trimmed) >= 6) { if (NROW(found) > 0 & nchar(b.x_trimmed) >= 6) {
if (property == "ref") { if (property == "ref") {
@ -630,32 +685,29 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
} else { } else {
x <- microorganismsDT[tsn == found[1, tsn_new], ..property][[1]] x <- microorganismsDT[tsn == found[1, tsn_new], ..property][[1]]
} }
warning(red(paste0('(UNCERTAIN) "', was_renamed(name_old = found[1, name],
a.x_backup, '" >> ', italic(found[1, name]), " (TSN ", found[1, tsn], ")")),
call. = FALSE, immediate. = FALSE)
notes <<- c(notes,
renamed_note(name_old = found[1, name],
name_new = microorganismsDT[tsn == found[1, tsn_new], fullname], name_new = microorganismsDT[tsn == found[1, tsn_new], fullname],
ref_old = found[1, ref], ref_old = found[1, ref],
ref_new = microorganismsDT[tsn == found[1, tsn_new], ref], ref_new = microorganismsDT[tsn == found[1, tsn_new], ref],
mo = microorganismsDT[tsn == found[1, tsn_new], mo])) mo = microorganismsDT[tsn == found[1, tsn_new], mo])
uncertainties <<- c(uncertainties,
paste0("'", a.x_backup, "' >> ", found[1, name], " (TSN ", found[1, tsn], ")"))
return(x) return(x)
} }
# (2) strip values between brackets ---- # (3) strip values between brackets ----
a.x_backup_stripped <- gsub("( [(].*[)])", "", a.x_backup) a.x_backup_stripped <- gsub("( [(].*[)])", "", a.x_backup)
a.x_backup_stripped <- trimws(gsub(" ", " ", a.x_backup_stripped, fixed = TRUE)) a.x_backup_stripped <- trimws(gsub(" ", " ", a.x_backup_stripped, fixed = TRUE))
found <- suppressMessages(suppressWarnings(exec_as.mo(a.x_backup_stripped, clear_options = FALSE, allow_uncertain = FALSE))) found <- suppressMessages(suppressWarnings(exec_as.mo(a.x_backup_stripped, clear_options = FALSE, allow_uncertain = FALSE)))
if (!is.na(found) & nchar(b.x_trimmed) >= 6) { if (!is.na(found) & nchar(b.x_trimmed) >= 6) {
found_result <- found found_result <- found
found <- microorganismsDT[mo == found, ..property][[1]] found <- microorganismsDT[mo == found, ..property][[1]]
warning(red(paste0('(UNCERTAIN) "', uncertainties <<- c(uncertainties,
a.x_backup, '" >> ', italic(microorganismsDT[mo == found_result[1L], fullname][[1]]), " (", found_result[1L], ")")), paste0("'", a.x_backup, "' >> ", microorganismsDT[mo == found_result[1L], fullname][[1]], " (", found_result[1L], ")"))
call. = FALSE, immediate. = FALSE)
return(found[1L]) return(found[1L])
} }
# (3) try to strip off one element and check the remains ---- # (4) try to strip off one element from end and check the remains ----
x_strip <- a.x_backup %>% strsplit(" ") %>% unlist() x_strip <- a.x_backup %>% strsplit(" ") %>% unlist()
if (length(x_strip) > 1 & nchar(b.x_trimmed) >= 6) { if (length(x_strip) > 1 & nchar(b.x_trimmed) >= 6) {
for (i in 1:(length(x_strip) - 1)) { for (i in 1:(length(x_strip) - 1)) {
@ -664,22 +716,39 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
if (!is.na(found)) { if (!is.na(found)) {
found_result <- found found_result <- found
found <- microorganismsDT[mo == found, ..property][[1]] found <- microorganismsDT[mo == found, ..property][[1]]
warning(red(paste0('(UNCERTAIN) "', uncertainties <<- c(uncertainties,
a.x_backup, '" >> ', italic(microorganismsDT[mo == found_result[1L], fullname][[1]]), " (", found_result[1L], ")")), paste0("'", a.x_backup, "' >> ", microorganismsDT[mo == found_result[1L], fullname][[1]], " (", found_result[1L], ")"))
call. = FALSE, immediate. = FALSE)
return(found[1L]) return(found[1L])
} }
} }
} }
# (4) not yet implemented taxonomic changes in ITIS # (5) try to strip off one element from start and check the remains ----
x_strip <- a.x_backup %>% strsplit(" ") %>% unlist()
if (length(x_strip) > 1 & nchar(b.x_trimmed) >= 6) {
for (i in 2:(length(x_strip))) {
x_strip_collapsed <- paste(x_strip[i:length(x_strip)], collapse = " ")
found <- suppressMessages(suppressWarnings(exec_as.mo(x_strip_collapsed, clear_options = FALSE, allow_uncertain = FALSE)))
if (!is.na(found)) {
found_result <- found
found <- microorganismsDT[mo == found, ..property][[1]]
uncertainties <<- c(uncertainties,
paste0("'", a.x_backup, "' >> ", microorganismsDT[mo == found_result[1L], fullname][[1]], " (", found_result[1L], ")"))
return(found[1L])
}
}
}
# (6) not yet implemented taxonomic changes in ITIS ----
found <- suppressMessages(suppressWarnings(exec_as.mo(TEMPORARY_TAXONOMY(b.x_trimmed), clear_options = FALSE, allow_uncertain = FALSE))) found <- suppressMessages(suppressWarnings(exec_as.mo(TEMPORARY_TAXONOMY(b.x_trimmed), clear_options = FALSE, allow_uncertain = FALSE)))
if (!is.na(found)) { if (!is.na(found)) {
found_result <- found found_result <- found
found <- microorganismsDT[mo == found, ..property][[1]] found <- microorganismsDT[mo == found, ..property][[1]]
warning(red(paste0('(UNCERTAIN) "', warning(silver(paste0('Guessed with uncertainty: "',
a.x_backup, '" >> ', italic(microorganismsDT[mo == found_result[1L], fullname][[1]]), " (", found_result[1L], ")")), a.x_backup, '" >> ', italic(microorganismsDT[mo == found_result[1L], fullname][[1]]), " (", found_result[1L], ")")),
call. = FALSE, immediate. = FALSE) call. = FALSE, immediate. = FALSE)
uncertainties <<- c(uncertainties,
paste0('"', a.x_backup, '" >> ', microorganismsDT[mo == found_result[1L], fullname][[1]], " (", found_result[1L], ")"))
return(found[1L]) return(found[1L])
} }
@ -687,7 +756,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
return(NA_character_) return(NA_character_)
} }
x[i] <- uncertain_fn(x_backup[i], x_trimmed[i], x_withspaces[i], x_withspaces_start[i], x[i]) x[i] <- uncertain_fn(x_backup[i], x_trimmed[i], x_withspaces_start_end[i], x_withspaces_start_only[i], x[i])
if (!is.na(x[i])) { if (!is.na(x[i])) {
next next
} }
@ -696,26 +765,39 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
# not found ---- # not found ----
x[i] <- NA_character_ x[i] <- NA_character_
failures <- c(failures, x_backup[i]) failures <- c(failures, x_backup[i])
} }
} }
# failures
failures <- failures[!failures %in% c(NA, NULL, NaN)] failures <- failures[!failures %in% c(NA, NULL, NaN)]
if (length(failures) > 0) { if (length(failures) > 0) {
options(mo_failures = sort(unique(failures))) options(mo_failures = sort(unique(failures)))
plural <- "" plural <- c("value", "it")
if (n_distinct(failures) > 1) { if (n_distinct(failures) > 1) {
plural <- "s" plural <- c("values", "them")
} }
total_failures <- length(x_input[x_input %in% failures & !x_input %in% c(NA, NULL, NaN)]) total_failures <- length(x_input[x_input %in% failures & !x_input %in% c(NA, NULL, NaN)])
total_n <- length(x_input[!x_input %in% c(NA, NULL, NaN)]) total_n <- length(x_input[!x_input %in% c(NA, NULL, NaN)])
msg <- paste0("\n", n_distinct(failures), " unique value", plural, msg <- paste0("\n", n_distinct(failures), " unique ", plural[1],
" (^= ", percent(total_failures / total_n, round = 1, force_zero = TRUE), " (^= ", percent(total_failures / total_n, round = 1, force_zero = TRUE),
") could not be coerced to a valid MO code") ") could not be coerced to a valid MO code")
if (n_distinct(failures) <= 10) { if (n_distinct(failures) <= 10) {
msg <- paste0(msg, ": ", paste('"', unique(failures), '"', sep = "", collapse = ', ')) msg <- paste0(msg, ": ", paste('"', unique(failures), '"', sep = "", collapse = ', '))
} }
msg <- paste0(msg, ". Use mo_failures() to review failured input.") msg <- paste0(msg, ". Use mo_failures() to review ", plural[2], ".")
warning(red(msg),
call. = FALSE,
immediate. = TRUE) # thus will always be shown, even if >= warnings
}
# uncertainties
if (length(uncertainties) > 0) {
options(mo_uncertainties = sort(unique(uncertainties)))
plural <- c("value", "it")
if (n_distinct(failures) > 1) {
plural <- c("values", "them")
}
msg <- paste0("\nResults of ", n_distinct(uncertainties), " input ", plural[1],
" guessed with uncertainty. Use mo_uncertainties() to review ", plural[2], ".")
warning(red(msg), warning(red(msg),
call. = FALSE, call. = FALSE,
immediate. = TRUE) # thus will always be shown, even if >= warnings immediate. = TRUE) # thus will always be shown, even if >= warnings
@ -774,6 +856,9 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
x[x == microorganismsDT[mo == 'B_STRPTC_SAL', ..property][[1]][1L]] <- microorganismsDT[mo == 'B_STRPTC_GRK', ..property][[1]][1L] x[x == microorganismsDT[mo == 'B_STRPTC_SAL', ..property][[1]][1L]] <- microorganismsDT[mo == 'B_STRPTC_GRK', ..property][[1]][1L]
} }
# Wrap up ----------------------------------------------------------------
# comply to x, which is also unique and without empty values # comply to x, which is also unique and without empty values
x_input_unique_nonempty <- unique(x_input[!is.na(x_input) & !is.null(x_input) & !identical(x_input, "")]) x_input_unique_nonempty <- unique(x_input[!is.na(x_input) & !is.null(x_input) & !identical(x_input, "")])
@ -794,10 +879,15 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
x <- as.integer(x) x <- as.integer(x)
} }
if (length(notes > 0)) { if (length(mo_renamed()) > 0) {
if (has_color()) {
notes <- getOption("mo_renamed")
} else {
notes <- mo_renamed()
}
notes <- sort(notes) notes <- sort(notes)
for (i in 1:length(notes)) { for (i in 1:length(notes)) {
base::message(notes[i]) base::message(blue(paste("Note:", notes[i])))
} }
} }
@ -810,7 +900,7 @@ TEMPORARY_TAXONOMY <- function(x) {
} }
#' @importFrom crayon blue italic #' @importFrom crayon blue italic
renamed_note <- function(name_old, name_new, ref_old = "", ref_new = "", mo = "") { was_renamed <- function(name_old, name_new, ref_old = "", ref_new = "", mo = "") {
if (!is.na(ref_old)) { if (!is.na(ref_old)) {
ref_old <- paste0(" (", ref_old, ")") ref_old <- paste0(" (", ref_old, ")")
} else { } else {
@ -828,10 +918,7 @@ renamed_note <- function(name_old, name_new, ref_old = "", ref_new = "", mo = ""
} }
msg <- paste0(italic(name_old), ref_old, " was renamed ", italic(name_new), ref_new, mo) msg <- paste0(italic(name_old), ref_old, " was renamed ", italic(name_new), ref_new, mo)
msg <- gsub("et al.", italic("et al."), msg) msg <- gsub("et al.", italic("et al."), msg)
msg_plain <- paste0(name_old, ref_old, " >> ", name_new, ref_new) options(mo_renamed = sort(msg))
msg_plain <- c(getOption("mo_renamed", character(0)), msg_plain)
options(mo_renamed = sort(msg_plain))
return(blue(paste("Note:", msg)))
} }
#' @exportMethod print.mo #' @exportMethod print.mo
@ -882,20 +969,20 @@ pull.mo <- function(.data, ...) {
pull(as.data.frame(.data), ...) pull(as.data.frame(.data), ...)
} }
#' Vector of failed coercion attempts #' @rdname as.mo
#'
#' Returns a vector of all failed attempts to coerce values to a valid MO code with \code{\link{as.mo}}.
#' @seealso \code{\link{as.mo}}
#' @export #' @export
mo_failures <- function() { mo_failures <- function() {
getOption("mo_failures") getOption("mo_failures")
} }
#' Vector of taxonomic renamed items #' @rdname as.mo
#' #' @export
#' Returns a vector of all renamed items of the last coercion to valid MO codes with \code{\link{as.mo}}. mo_uncertainties <- function() {
#' @seealso \code{\link{as.mo}} getOption("mo_uncertainties")
}
#' @rdname as.mo
#' @export #' @export
mo_renamed <- function() { mo_renamed <- function() {
getOption("mo_renamed") strip_style(gsub("was renamed", ">>", getOption("mo_renamed"), fixed = TRUE))
} }

6
R/mo_property.R
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@ -248,7 +248,11 @@ mo_gramstain <- function(x, language = get_locale(), ...) {
#' @rdname mo_property #' @rdname mo_property
#' @export #' @export
mo_TSN <- function(x, ...) { mo_TSN <- function(x, ...) {
mo_validate(x = x, property = "tsn", ...) res <- mo_validate(x = x, property = "tsn", ...)
if (any(is.na(res))) {
warning("Some results do not have a TSN, because they are missing from ITIS and were added manually. See ?microorganisms.")
}
res
} }
#' @rdname mo_property #' @rdname mo_property

3
_pkgdown.yml
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@ -119,6 +119,7 @@ reference:
Functions for conducting AMR analysis, like counting isolates, calculating Functions for conducting AMR analysis, like counting isolates, calculating
resistance or susceptibility, creating frequency tables or make plots. resistance or susceptibility, creating frequency tables or make plots.
contents: contents:
- '`availability`'
- '`count`' - '`count`'
- '`portion`' - '`portion`'
- '`freq`' - '`freq`'
@ -148,8 +149,6 @@ reference:
contents: contents:
- '`get_locale`' - '`get_locale`'
- '`like`' - '`like`'
- '`mo_failures`'
- '`mo_renamed`'
- '`ab_property`' - '`ab_property`'

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2
docs/LICENSE-text.html
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@ -78,7 +78,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a> <a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9017</span>
</span> </span>
</div> </div>

435
docs/articles/AMR.html
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@ -185,7 +185,7 @@
<h1>How to conduct AMR analysis</h1> <h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4> <h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">04 February 2019</h4> <h4 class="date">08 February 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div> <div class="hidden name"><code>AMR.Rmd</code></div>
@ -194,7 +194,7 @@
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">RMarkdown</a>. However, the methodology remains unchanged. This page was generated on 04 February 2019.</p> <p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">RMarkdown</a>. However, the methodology remains unchanged. This page was generated on 08 February 2019.</p>
<div id="introduction" class="section level1"> <div id="introduction" class="section level1">
<h1 class="hasAnchor"> <h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1> <a href="#introduction" class="anchor"></a>Introduction</h1>
@ -210,21 +210,21 @@
</tr></thead> </tr></thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">2019-02-04</td> <td align="center">2019-02-08</td>
<td align="center">abcd</td> <td align="center">abcd</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2019-02-04</td> <td align="center">2019-02-08</td>
<td align="center">abcd</td> <td align="center">abcd</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">2019-02-04</td> <td align="center">2019-02-08</td>
<td align="center">efgh</td> <td align="center">efgh</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">R</td> <td align="center">R</td>
@ -313,41 +313,52 @@
</tr></thead> </tr></thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">2010-05-26</td> <td align="center">2010-10-06</td>
<td align="center">E8</td> <td align="center">F7</td>
<td align="center">Hospital C</td> <td align="center">Hospital D</td>
<td align="center">Escherichia coli</td> <td align="center">Klebsiella pneumoniae</td>
<td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2016-11-27</td>
<td align="center">D6</td>
<td align="center">Hospital B</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">M</td> <td align="center">M</td>
</tr> </tr>
<tr class="odd"> <tr class="even">
<td align="center">2015-03-24</td> <td align="center">2015-07-29</td>
<td align="center">J2</td> <td align="center">T1</td>
<td align="center">Hospital A</td> <td align="center">Hospital A</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">M</td> <td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2017-10-20</td>
<td align="center">P2</td>
<td align="center">Hospital B</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2014-09-12</td> <td align="center">2010-02-07</td>
<td align="center">Y4</td> <td align="center">Z6</td>
<td align="center">Hospital A</td>
<td align="center">Klebsiella pneumoniae</td>
<td align="center">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2012-06-26</td>
<td align="center">V4</td>
<td align="center">Hospital A</td> <td align="center">Hospital A</td>
<td align="center">Staphylococcus aureus</td> <td align="center">Staphylococcus aureus</td>
<td align="center">S</td> <td align="center">S</td>
@ -356,22 +367,11 @@
<td align="center">S</td> <td align="center">S</td>
<td align="center">F</td> <td align="center">F</td>
</tr> </tr>
<tr class="odd"> <tr class="even">
<td align="center">2015-05-27</td> <td align="center">2016-02-08</td>
<td align="center">M8</td> <td align="center">S2</td>
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2017-10-14</td>
<td align="center">R8</td>
<td align="center">Hospital C</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
@ -388,7 +388,7 @@
<a href="#cleaning-the-data" class="anchor"></a>Cleaning the data</h1> <a href="#cleaning-the-data" class="anchor"></a>Cleaning the data</h1>
<p>Use the frequency table function <code><a href="../reference/freq.html">freq()</a></code> to look specifically for unique values in any variable. For example, for the <code>gender</code> variable:</p> <p>Use the frequency table function <code><a href="../reference/freq.html">freq()</a></code> to look specifically for unique values in any variable. For example, for the <code>gender</code> variable:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender) <span class="co"># this would be the same: freq(data$gender)</span></a></code></pre></div> <div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender) <span class="co"># this would be the same: freq(data$gender)</span></a></code></pre></div>
<pre><code># Frequency table of `gender` from a `data.frame` (5,000 x 9) <pre><code># Frequency table of `gender` from a data.frame (5,000 x 9)
# Class: factor (numeric) # Class: factor (numeric)
# Levels: F, M # Levels: F, M
# Length: 5,000 (of which NA: 0 = 0.00%) # Length: 5,000 (of which NA: 0 = 0.00%)
@ -396,8 +396,8 @@
# #
# Item Count Percent Cum. Count Cum. Percent # Item Count Percent Cum. Count Cum. Percent
# --- ----- ------ -------- ----------- ------------- # --- ----- ------ -------- ----------- -------------
# 1 M 2,560 51.2% 2,560 51.2% # 1 M 2,551 51.0% 2,551 51.0%
# 2 F 2,440 48.8% 5,000 100.0%</code></pre> # 2 F 2,449 49.0% 5,000 100.0%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientist perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researcher perspective: there are slightly more men. Nothing we didn’t already know.</p> <p>So, we can draw at least two conclusions immediately. From a data scientist perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researcher perspective: there are slightly more men. Nothing we didn’t already know.</p>
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p> <p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a> <div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -428,10 +428,10 @@
<a class="sourceLine" id="cb14-19" data-line-number="19"><span class="co"># Kingella kingae (no changes)</span></a> <a class="sourceLine" id="cb14-19" data-line-number="19"><span class="co"># Kingella kingae (no changes)</span></a>
<a class="sourceLine" id="cb14-20" data-line-number="20"><span class="co"># </span></a> <a class="sourceLine" id="cb14-20" data-line-number="20"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-21" data-line-number="21"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a> <a class="sourceLine" id="cb14-21" data-line-number="21"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb14-22" data-line-number="22"><span class="co"># Table 1: Intrinsic resistance in Enterobacteriaceae (348 changes)</span></a> <a class="sourceLine" id="cb14-22" data-line-number="22"><span class="co"># Table 1: Intrinsic resistance in Enterobacteriaceae (345 changes)</span></a>
<a class="sourceLine" id="cb14-23" data-line-number="23"><span class="co"># Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a> <a class="sourceLine" id="cb14-23" data-line-number="23"><span class="co"># Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-24" data-line-number="24"><span class="co"># Table 3: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a> <a class="sourceLine" id="cb14-24" data-line-number="24"><span class="co"># Table 3: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-25" data-line-number="25"><span class="co"># Table 4: Intrinsic resistance in Gram-positive bacteria (702 changes)</span></a> <a class="sourceLine" id="cb14-25" data-line-number="25"><span class="co"># Table 4: Intrinsic resistance in Gram-positive bacteria (673 changes)</span></a>
<a class="sourceLine" id="cb14-26" data-line-number="26"><span class="co"># Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a> <a class="sourceLine" id="cb14-26" data-line-number="26"><span class="co"># Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb14-27" data-line-number="27"><span class="co"># Table 9: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a> <a class="sourceLine" id="cb14-27" data-line-number="27"><span class="co"># Table 9: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb14-28" data-line-number="28"><span class="co"># Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria (no changes)</span></a> <a class="sourceLine" id="cb14-28" data-line-number="28"><span class="co"># Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria (no changes)</span></a>
@ -447,7 +447,9 @@
<a class="sourceLine" id="cb14-38" data-line-number="38"><span class="co"># Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a> <a class="sourceLine" id="cb14-38" data-line-number="38"><span class="co"># Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a> <a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a>
<a class="sourceLine" id="cb14-40" data-line-number="40"><span class="co"># </span></a> <a class="sourceLine" id="cb14-40" data-line-number="40"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-41" data-line-number="41"><span class="co"># =&gt; EUCAST rules affected 1,820 out of 5,000 rows -&gt; changed 1,050 test results.</span></a></code></pre></div> <a class="sourceLine" id="cb14-41" data-line-number="41"><span class="co"># =&gt; EUCAST rules affected 1,814 out of 5,000 rows</span></a>
<a class="sourceLine" id="cb14-42" data-line-number="42"><span class="co"># -&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb14-43" data-line-number="43"><span class="co"># -&gt; changed 1,018 test results (0 to S; 0 to I; 1,018 to R)</span></a></code></pre></div>
</div> </div>
<div id="adding-new-variables" class="section level1"> <div id="adding-new-variables" class="section level1">
<h1 class="hasAnchor"> <h1 class="hasAnchor">
@ -472,8 +474,8 @@
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a> <a class="sourceLine" id="cb16-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a> <a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
<a class="sourceLine" id="cb16-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a> <a class="sourceLine" id="cb16-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 2,951 first isolates (59.0% of total)</span></a></code></pre></div> <a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 2,939 first isolates (58.8% of total)</span></a></code></pre></div>
<p>So only 59% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p> <p>So only 58.8% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a> <div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div> <a class="sourceLine" id="cb17-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
<p>For future use, the above two syntaxes can be shortened with the <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> function:</p> <p>For future use, the above two syntaxes can be shortened with the <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> function:</p>
@ -499,30 +501,30 @@
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">1</td> <td align="center">1</td>
<td align="center">2010-03-08</td> <td align="center">2010-04-03</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">I</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2</td> <td align="center">2</td>
<td align="center">2010-05-08</td> <td align="center">2010-10-31</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td> <td align="center">FALSE</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">3</td> <td align="center">3</td>
<td align="center">2010-06-21</td> <td align="center">2010-11-12</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
@ -532,21 +534,21 @@
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">4</td> <td align="center">4</td>
<td align="center">2010-12-01</td> <td align="center">2010-11-21</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td> <td align="center">FALSE</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">5</td> <td align="center">5</td>
<td align="center">2011-01-05</td> <td align="center">2010-12-01</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">R</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
@ -554,52 +556,41 @@
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">6</td> <td align="center">6</td>
<td align="center">2012-01-16</td> <td align="center">2011-10-22</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">I</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">7</td> <td align="center">7</td>
<td align="center">2012-04-11</td> <td align="center">2012-03-22</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">R</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">FALSE</td> <td align="center">FALSE</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">8</td> <td align="center">8</td>
<td align="center">2012-10-23</td> <td align="center">2012-05-14</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">FALSE</td> <td align="center">FALSE</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">9</td> <td align="center">9</td>
<td align="center">2012-11-24</td> <td align="center">2012-10-26</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2014-01-26</td>
<td align="center">G3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
@ -607,6 +598,17 @@
<td align="center">S</td> <td align="center">S</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2013-06-13</td>
<td align="center">C3</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
</tbody> </tbody>
</table> </table>
<p>Only 3 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p> <p>Only 3 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
@ -620,7 +622,7 @@
<a class="sourceLine" id="cb19-7" data-line-number="7"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a> <a class="sourceLine" id="cb19-7" data-line-number="7"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb19-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a> <a class="sourceLine" id="cb19-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
<a class="sourceLine" id="cb19-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I.</span></a> <a class="sourceLine" id="cb19-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I.</span></a>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 4,424 first weighted isolates (88.5% of total)</span></a></code></pre></div> <a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 4,387 first weighted isolates (87.7% of total)</span></a></code></pre></div>
<table class="table"> <table class="table">
<thead><tr class="header"> <thead><tr class="header">
<th align="center">isolate</th> <th align="center">isolate</th>
@ -637,11 +639,11 @@
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">1</td> <td align="center">1</td>
<td align="center">2010-03-08</td> <td align="center">2010-04-03</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">I</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
@ -649,20 +651,20 @@
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2</td> <td align="center">2</td>
<td align="center">2010-05-08</td> <td align="center">2010-10-31</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td> <td align="center">FALSE</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">3</td> <td align="center">3</td>
<td align="center">2010-06-21</td> <td align="center">2010-11-12</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
@ -673,22 +675,22 @@
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">4</td> <td align="center">4</td>
<td align="center">2010-12-01</td> <td align="center">2010-11-21</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td> <td align="center">FALSE</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">5</td> <td align="center">5</td>
<td align="center">2011-01-05</td> <td align="center">2010-12-01</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">R</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
@ -697,11 +699,11 @@
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">6</td> <td align="center">6</td>
<td align="center">2012-01-16</td> <td align="center">2011-10-22</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">I</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
@ -709,23 +711,23 @@
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">7</td> <td align="center">7</td>
<td align="center">2012-04-11</td> <td align="center">2012-03-22</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">R</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">FALSE</td> <td align="center">FALSE</td>
<td align="center">TRUE</td> <td align="center">FALSE</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">8</td> <td align="center">8</td>
<td align="center">2012-10-23</td> <td align="center">2012-05-14</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">FALSE</td> <td align="center">FALSE</td>
@ -733,20 +735,8 @@
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">9</td> <td align="center">9</td>
<td align="center">2012-11-24</td> <td align="center">2012-10-26</td>
<td align="center">G3</td> <td align="center">C3</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2014-01-26</td>
<td align="center">G3</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
@ -755,13 +745,25 @@
<td align="center">TRUE</td> <td align="center">TRUE</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2013-06-13</td>
<td align="center">C3</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
</tbody> </tbody>
</table> </table>
<p>Instead of 3, now 9 isolates are flagged. In total, 88.5% of all isolates are marked ‘first weighted’ - 29.5% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p> <p>Instead of 3, now 9 isolates are flagged. In total, 87.7% of all isolates are marked ‘first weighted’ - 29% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p> <p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a> <div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div> <a class="sourceLine" id="cb20-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
<p>So we end up with 4,424 isolates for analysis.</p> <p>So we end up with 4,387 isolates for analysis.</p>
<p>We can remove unneeded columns:</p> <p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a> <div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(first, keyab))</a></code></pre></div> <a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(first, keyab))</a></code></pre></div>
@ -769,6 +771,7 @@
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/head">head</a></span>(data_1st)</a></code></pre></div> <div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/head">head</a></span>(data_1st)</a></code></pre></div>
<table class="table"> <table class="table">
<thead><tr class="header"> <thead><tr class="header">
<th></th>
<th align="center">date</th> <th align="center">date</th>
<th align="center">patient_id</th> <th align="center">patient_id</th>
<th align="center">hospital</th> <th align="center">hospital</th>
@ -785,58 +788,46 @@
</tr></thead> </tr></thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">2010-05-26</td> <td>1</td>
<td align="center">E8</td> <td align="center">2010-10-06</td>
<td align="center">Hospital C</td> <td align="center">F7</td>
<td align="center">B_ESCHR_COL</td> <td align="center">Hospital D</td>
<td align="center">B_KLBSL_PNE</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">R</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">M</td> <td align="center">M</td>
<td align="center">Gram negative</td> <td align="center">Gram negative</td>
<td align="center">Escherichia</td> <td align="center">Klebsiella</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2016-11-27</td>
<td align="center">D6</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPTC_PNE</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td> <td align="center">pneumoniae</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="odd"> <tr class="even">
<td align="center">2015-03-24</td> <td>2</td>
<td align="center">J2</td> <td align="center">2015-07-29</td>
<td align="center">T1</td>
<td align="center">Hospital A</td> <td align="center">Hospital A</td>
<td align="center">B_ESCHR_COL</td> <td align="center">B_ESCHR_COL</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">M</td> <td align="center">F</td>
<td align="center">Gram negative</td> <td align="center">Gram negative</td>
<td align="center">Escherichia</td> <td align="center">Escherichia</td>
<td align="center">coli</td> <td align="center">coli</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="even"> <tr class="odd">
<td align="center">2014-09-12</td> <td>3</td>
<td align="center">Y4</td> <td align="center">2017-10-20</td>
<td align="center">Hospital A</td> <td align="center">P2</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AUR</td> <td align="center">B_STPHY_AUR</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">F</td> <td align="center">F</td>
<td align="center">Gram positive</td> <td align="center">Gram positive</td>
@ -844,31 +835,49 @@
<td align="center">aureus</td> <td align="center">aureus</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="odd"> <tr class="even">
<td align="center">2015-05-27</td> <td>4</td>
<td align="center">M8</td> <td align="center">2010-02-07</td>
<td align="center">Hospital B</td> <td align="center">Z6</td>
<td align="center">B_ESCHR_COL</td> <td align="center">Hospital A</td>
<td align="center">B_KLBSL_PNE</td>
<td align="center">R</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram negative</td>
<td align="center">Klebsiella</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>6</td>
<td align="center">2016-02-08</td>
<td align="center">S2</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">M</td> <td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram negative</td> <td align="center">Gram negative</td>
<td align="center">Escherichia</td> <td align="center">Escherichia</td>
<td align="center">coli</td> <td align="center">coli</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2017-10-14</td> <td>9</td>
<td align="center">R8</td> <td align="center">2016-10-31</td>
<td align="center">H3</td>
<td align="center">Hospital C</td> <td align="center">Hospital C</td>
<td align="center">B_STPHY_AUR</td> <td align="center">B_STPHY_AUR</td>
<td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">M</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram positive</td> <td align="center">Gram positive</td>
<td align="center">Staphylococcus</td> <td align="center">Staphylococcus</td>
<td align="center">aureus</td> <td align="center">aureus</td>
@ -891,9 +900,9 @@
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" data-line-number="1"><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(data_1st<span class="op">$</span>genus, data_1st<span class="op">$</span>species))</a></code></pre></div> <div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" data-line-number="1"><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(data_1st<span class="op">$</span>genus, data_1st<span class="op">$</span>species))</a></code></pre></div>
<p>Or can be used like the <code>dplyr</code> way, which is easier readable:</p> <p>Or can be used like the <code>dplyr</code> way, which is easier readable:</p>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species)</a></code></pre></div> <div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (4,424 x 13)</strong><br> <p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (4,387 x 13)</strong><br>
Columns: 2<br> Columns: 2<br>
Length: 4,424 (of which NA: 0 = 0.00%)<br> Length: 4,387 (of which NA: 0 = 0.00%)<br>
Unique: 4</p> Unique: 4</p>
<p>Shortest: 16<br> <p>Shortest: 16<br>
Longest: 24</p> Longest: 24</p>
@ -910,33 +919,33 @@ Longest: 24</p>
<tr class="odd"> <tr class="odd">
<td align="left">1</td> <td align="left">1</td>
<td align="left">Escherichia coli</td> <td align="left">Escherichia coli</td>
<td align="right">2,141</td> <td align="right">2,129</td>
<td align="right">48.4%</td> <td align="right">48.5%</td>
<td align="right">2,141</td> <td align="right">2,129</td>
<td align="right">48.4%</td> <td align="right">48.5%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">2</td> <td align="left">2</td>
<td align="left">Staphylococcus aureus</td> <td align="left">Staphylococcus aureus</td>
<td align="right">1,126</td> <td align="right">1,098</td>
<td align="right">25.5%</td> <td align="right">25.0%</td>
<td align="right">3,267</td> <td align="right">3,227</td>
<td align="right">73.8%</td> <td align="right">73.6%</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">3</td> <td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td> <td align="left">Streptococcus pneumoniae</td>
<td align="right">699</td> <td align="right">688</td>
<td align="right">15.8%</td> <td align="right">15.7%</td>
<td align="right">3,966</td> <td align="right">3,915</td>
<td align="right">89.6%</td> <td align="right">89.2%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">4</td> <td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td> <td align="left">Klebsiella pneumoniae</td>
<td align="right">458</td> <td align="right">472</td>
<td align="right">10.4%</td> <td align="right">10.8%</td>
<td align="right">4,424</td> <td align="right">4,387</td>
<td align="right">100.0%</td> <td align="right">100.0%</td>
</tr> </tr>
</tbody> </tbody>
@ -947,7 +956,7 @@ Longest: 24</p>
<a href="#resistance-percentages" class="anchor"></a>Resistance percentages</h2> <a href="#resistance-percentages" class="anchor"></a>Resistance percentages</h2>
<p>The functions <code>portion_R</code>, <code>portion_RI</code>, <code>portion_I</code>, <code>portion_IS</code> and <code>portion_S</code> can be used to determine the portion of a specific antimicrobial outcome. They can be used on their own:</p> <p>The functions <code>portion_R</code>, <code>portion_RI</code>, <code>portion_I</code>, <code>portion_IS</code> and <code>portion_S</code> can be used to determine the portion of a specific antimicrobial outcome. They can be used on their own:</p>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_IR</a></span>(amox)</a> <div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_IR</a></span>(amox)</a>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4622514</span></a></code></pre></div> <a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4700251</span></a></code></pre></div>
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p> <p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a> <div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a> <a class="sourceLine" id="cb26-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -960,19 +969,19 @@ Longest: 24</p>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">Hospital A</td> <td align="center">Hospital A</td>
<td align="center">0.4566642</td> <td align="center">0.4544765</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">0.4615894</td> <td align="center">0.4920107</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">Hospital C</td> <td align="center">Hospital C</td>
<td align="center">0.4807122</td> <td align="center">0.4686567</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Hospital D</td> <td align="center">Hospital D</td>
<td align="center">0.4579008</td> <td align="center">0.4570792</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
@ -990,23 +999,23 @@ Longest: 24</p>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">Hospital A</td> <td align="center">Hospital A</td>
<td align="center">0.4566642</td> <td align="center">0.4544765</td>
<td align="center">1373</td> <td align="center">1318</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">0.4615894</td> <td align="center">0.4920107</td>
<td align="center">1510</td> <td align="center">1502</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">Hospital C</td> <td align="center">Hospital C</td>
<td align="center">0.4807122</td> <td align="center">0.4686567</td>
<td align="center">674</td> <td align="center">670</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Hospital D</td> <td align="center">Hospital D</td>
<td align="center">0.4579008</td> <td align="center">0.4570792</td>
<td align="center">867</td> <td align="center">897</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
@ -1026,27 +1035,27 @@ Longest: 24</p>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">Escherichia</td> <td align="center">Escherichia</td>
<td align="center">0.7356376</td> <td align="center">0.7491780</td>
<td align="center">0.9033162</td> <td align="center">0.9074683</td>
<td align="center">0.9729099</td> <td align="center">0.9798027</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Klebsiella</td> <td align="center">Klebsiella</td>
<td align="center">0.7445415</td> <td align="center">0.7521186</td>
<td align="center">0.8930131</td> <td align="center">0.9067797</td>
<td align="center">0.9694323</td> <td align="center">0.9745763</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">Staphylococcus</td> <td align="center">Staphylococcus</td>
<td align="center">0.7566607</td> <td align="center">0.7349727</td>
<td align="center">0.9174067</td> <td align="center">0.9171220</td>
<td align="center">0.9760213</td> <td align="center">0.9708561</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Streptococcus</td> <td align="center">Streptococcus</td>
<td align="center">0.7668097</td> <td align="center">0.7398256</td>
<td align="center">0.0000000</td> <td align="center">0.0000000</td>
<td align="center">0.7668097</td> <td align="center">0.7398256</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>

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@ -40,7 +40,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9015</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span>
</span> </span>
</div> </div>
@ -185,7 +185,7 @@
<h1>How to apply EUCAST rules</h1> <h1>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4> <h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">29 January 2019</h4> <h4 class="date">08 February 2019</h4>
<div class="hidden name"><code>EUCAST.Rmd</code></div> <div class="hidden name"><code>EUCAST.Rmd</code></div>

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@ -40,7 +40,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9015</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span>
</span> </span>
</div> </div>
@ -185,7 +185,7 @@
<h1>How to use the <em>G</em>-test</h1> <h1>How to use the <em>G</em>-test</h1>
<h4 class="author">Matthijs S. Berends</h4> <h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">29 January 2019</h4> <h4 class="date">08 February 2019</h4>
<div class="hidden name"><code>G_test.Rmd</code></div> <div class="hidden name"><code>G_test.Rmd</code></div>

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@ -40,7 +40,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9015</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span>
</span> </span>
</div> </div>
@ -185,7 +185,7 @@
<h1>How to predict antimicrobial resistance</h1> <h1>How to predict antimicrobial resistance</h1>
<h4 class="author">Matthijs S. Berends</h4> <h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">29 January 2019</h4> <h4 class="date">08 February 2019</h4>
<div class="hidden name"><code>Predict.Rmd</code></div> <div class="hidden name"><code>Predict.Rmd</code></div>

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@ -185,7 +185,7 @@
<h1>How to work with WHONET data</h1> <h1>How to work with WHONET data</h1>
<h4 class="author">Matthijs S. Berends</h4> <h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">30 January 2019</h4> <h4 class="date">08 February 2019</h4>
<div class="hidden name"><code>WHONET.Rmd</code></div> <div class="hidden name"><code>WHONET.Rmd</code></div>
@ -212,20 +212,20 @@
<a class="sourceLine" id="cb2-3" data-line-number="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(AMR) <span class="co"># this package</span></a></code></pre></div> <a class="sourceLine" id="cb2-3" data-line-number="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(AMR) <span class="co"># this package</span></a></code></pre></div>
<p>We will have to transform some variables to simplify and automate the analysis:</p> <p>We will have to transform some variables to simplify and automate the analysis:</p>
<ul> <ul>
<li>Microorganisms should be transformed to our own microorganism IDs (called an <code>mo</code>) using <a href="./reference/ITIS.html">the ITIS reference data set</a>, which contains all ~20,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>.</li> <li>Microorganisms should be transformed to our own microorganism IDs (called an <code>mo</code>) using <a href="./reference/ITIS.html">the ITIS reference data set</a>, which contains all ~20,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>. This function also recognises almost all WHONET abbreviations of microorganisms.</li>
<li>Antimicrobial results or interpretations have to be clean and valid. In other words, they should only contain values <code>"S"</code>, <code>"I"</code> or <code>"R"</code>. That is exactly where the <code><a href="../reference/as.rsi.html">as.rsi()</a></code> function is for.</li> <li>Antimicrobial results or interpretations have to be clean and valid. In other words, they should only contain values <code>"S"</code>, <code>"I"</code> or <code>"R"</code>. That is exactly where the <code><a href="../reference/as.rsi.html">as.rsi()</a></code> function is for.</li>
</ul> </ul>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="co"># transform variables</span></a> <div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="co"># transform variables</span></a>
<a class="sourceLine" id="cb3-2" data-line-number="2">data &lt;-<span class="st"> </span>WHONET <span class="op">%&gt;%</span></a> <a class="sourceLine" id="cb3-2" data-line-number="2">data &lt;-<span class="st"> </span>WHONET <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="st"> </span><span class="co"># get microbial ID based on given organism</span></a> <a class="sourceLine" id="cb3-3" data-line-number="3"><span class="st"> </span><span class="co"># get microbial ID based on given organism</span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/mutate">mutate</a></span>(<span class="dt">mo =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(Organism)) <span class="op">%&gt;%</span><span class="st"> </span></a> <a class="sourceLine" id="cb3-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">mo =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(Organism)) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="st"> </span><span class="co"># transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class</span></a> <a class="sourceLine" id="cb3-5" data-line-number="5"><span class="st"> </span><span class="co"># transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class</span></a>
<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/summarise_all">mutate_at</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/vars">vars</a></span>(AMP_ND10<span class="op">:</span>CIP_EE), as.rsi)</a></code></pre></div> <a class="sourceLine" id="cb3-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html">mutate_at</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(AMP_ND10<span class="op">:</span>CIP_EE), as.rsi)</a></code></pre></div>
<p>No errors or warnings, so all values are transformed succesfully. Let’s check it though, with a couple of frequency tables:</p> <p>No errors or warnings, so all values are transformed succesfully. Let’s check it though, with a couple of frequency tables:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="co"># our newly created `mo` variable</span></a> <div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="co"># our newly created `mo` variable</span></a>
<a class="sourceLine" id="cb4-2" data-line-number="2">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(mo, <span class="dt">nmax =</span> <span class="dv">10</span>)</a></code></pre></div> <a class="sourceLine" id="cb4-2" data-line-number="2">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(mo, <span class="dt">nmax =</span> <span class="dv">10</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>mo</code> from a <code>data.frame</code> (500 x 54)</strong><br> <p><strong>Frequency table of <code>mo</code> from a <code>data.frame</code> (500 x 54)</strong><br>
Class: mo (character)<br> Class: <code>mo</code> (<code>character</code>)<br>
Length: 500 (of which NA: 0 = 0.00%)<br> Length: 500 (of which NA: 0 = 0.00%)<br>
Unique: 56</p> Unique: 56</p>
<p>Families: 14<br> <p>Families: 14<br>
@ -329,7 +329,7 @@ Species: 51</p>
<a class="sourceLine" id="cb5-3" data-line-number="3"><span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span></a> <a class="sourceLine" id="cb5-3" data-line-number="3"><span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span></a>
<a class="sourceLine" id="cb5-4" data-line-number="4">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(AMC_ND2)</a></code></pre></div> <a class="sourceLine" id="cb5-4" data-line-number="4">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(AMC_ND2)</a></code></pre></div>
<p><strong>Frequency table of <code>AMC_ND2</code> from a <code>data.frame</code> (500 x 54)</strong><br> <p><strong>Frequency table of <code>AMC_ND2</code> from a <code>data.frame</code> (500 x 54)</strong><br>
Class: factor &gt; ordered &gt; rsi (numeric)<br> Class: <code>factor</code> &gt; <code>ordered</code> &gt; <code>rsi</code> (<code>numeric</code>)<br>
Levels: S &lt; I &lt; R<br> Levels: S &lt; I &lt; R<br>
Length: 500 (of which NA: 41 = 8.20%)<br> Length: 500 (of which NA: 41 = 8.20%)<br>
Unique: 3</p> Unique: 3</p>

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@ -40,7 +40,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9015</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span>
</span> </span>
</div> </div>
@ -185,7 +185,7 @@
<h1>How to get properties of an antibiotic</h1> <h1>How to get properties of an antibiotic</h1>
<h4 class="author">Matthijs S. Berends</h4> <h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">29 January 2019</h4> <h4 class="date">08 February 2019</h4>
<div class="hidden name"><code>ab_property.Rmd</code></div> <div class="hidden name"><code>ab_property.Rmd</code></div>

4
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@ -40,7 +40,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9015</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span>
</span> </span>
</div> </div>
@ -185,7 +185,7 @@
<h1>Benchmarks</h1> <h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4> <h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">29 January 2019</h4> <h4 class="date">08 February 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div> <div class="hidden name"><code>benchmarks.Rmd</code></div>

61
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@ -40,7 +40,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9015</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span>
</span> </span>
</div> </div>
@ -185,7 +185,7 @@
<h1>How to create frequency tables</h1> <h1>How to create frequency tables</h1>
<h4 class="author">Matthijs S. Berends</h4> <h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">29 January 2019</h4> <h4 class="date">08 February 2019</h4>
<div class="hidden name"><code>freq.Rmd</code></div> <div class="hidden name"><code>freq.Rmd</code></div>
@ -204,7 +204,12 @@
<a href="#frequencies-of-one-variable" class="anchor"></a>Frequencies of one variable</h2> <a href="#frequencies-of-one-variable" class="anchor"></a>Frequencies of one variable</h2>
<p>To only show and quickly review the content of one variable, you can just select this variable in various ways. Let’s say we want to get the frequencies of the <code>gender</code> variable of the <code>septic_patients</code> dataset:</p> <p>To only show and quickly review the content of one variable, you can just select this variable in various ways. Let’s say we want to get the frequencies of the <code>gender</code> variable of the <code>septic_patients</code> dataset:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender)</a></code></pre></div> <div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender)</a></code></pre></div>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table of <code>gender</code> from a <code>data.frame</code> (2,000 x 49)</strong><br>
Class: <code>character</code> (<code>character</code>)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 2</p>
<p>Shortest: 1<br>
Longest: 1</p>
<table class="table"> <table class="table">
<thead><tr class="header"> <thead><tr class="header">
<th align="left"></th> <th align="left"></th>
@ -255,7 +260,12 @@
<p>So now the <code>genus</code> and <code>species</code> variables are available. A frequency table of these combined variables can be created like this:</p> <p>So now the <code>genus</code> and <code>species</code> variables are available. A frequency table of these combined variables can be created like this:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1">my_patients <span class="op">%&gt;%</span></a> <div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1">my_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb5-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species, <span class="dt">nmax =</span> <span class="dv">15</span>)</a></code></pre></div> <a class="sourceLine" id="cb5-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species, <span class="dt">nmax =</span> <span class="dv">15</span>)</a></code></pre></div>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (2,000 x 63)</strong><br>
Columns: 2<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 96</p>
<p>Shortest: 12<br>
Longest: 34</p>
<table class="table"> <table class="table">
<thead><tr class="header"> <thead><tr class="header">
<th align="left"></th> <th align="left"></th>
@ -399,8 +409,8 @@
<a class="sourceLine" id="cb6-2" data-line-number="2">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a> <a class="sourceLine" id="cb6-2" data-line-number="2">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="st"> </span><span class="kw">distinct</span>(patient_id, <span class="dt">.keep_all =</span> <span class="ot">TRUE</span>) <span class="op">%&gt;%</span><span class="st"> </span></a> <a class="sourceLine" id="cb6-3" data-line-number="3"><span class="st"> </span><span class="kw">distinct</span>(patient_id, <span class="dt">.keep_all =</span> <span class="ot">TRUE</span>) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb6-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(age, <span class="dt">nmax =</span> <span class="dv">5</span>, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div> <a class="sourceLine" id="cb6-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(age, <span class="dt">nmax =</span> <span class="dv">5</span>, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<p><strong>Frequency table</strong><br> <p><strong>Frequency table of <code>age</code> from a <code>data.frame</code> (981 x 49)</strong><br>
Class: numeric<br> Class: <code>numeric</code> (<code>numeric</code>)<br>
Length: 981 (of which NA: 0 = 0.00%)<br> Length: 981 (of which NA: 0 = 0.00%)<br>
Unique: 73</p> Unique: 73</p>
<p>Mean: 71.08<br> <p>Mean: 71.08<br>
@ -478,7 +488,11 @@ Outliers: 15 (unique count: 12)</p>
<p><code>sort.count</code> is <code>TRUE</code> by default. Compare this default behaviour…</p> <p><code>sort.count</code> is <code>TRUE</code> by default. Compare this default behaviour…</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a> <div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id)</a></code></pre></div> <a class="sourceLine" id="cb7-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id)</a></code></pre></div>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table of <code>hospital_id</code> from a <code>data.frame</code> (2,000 x 49)</strong><br>
Class: <code>factor</code> (<code>numeric</code>)<br>
Levels: A, B, C, D<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 4</p>
<table class="table"> <table class="table">
<thead><tr class="header"> <thead><tr class="header">
<th align="left"></th> <th align="left"></th>
@ -526,7 +540,11 @@ Outliers: 15 (unique count: 12)</p>
<p>… with this, where items are now sorted on count:</p> <p>… with this, where items are now sorted on count:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a> <div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb8-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">sort.count =</span> <span class="ot">FALSE</span>)</a></code></pre></div> <a class="sourceLine" id="cb8-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">sort.count =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table of <code>hospital_id</code> from a <code>data.frame</code> (2,000 x 49)</strong><br>
Class: <code>factor</code> (<code>numeric</code>)<br>
Levels: A, B, C, D<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 4</p>
<table class="table"> <table class="table">
<thead><tr class="header"> <thead><tr class="header">
<th align="left"></th> <th align="left"></th>
@ -574,8 +592,8 @@ Outliers: 15 (unique count: 12)</p>
<p>All classes will be printed into the header (default is <code>FALSE</code> when using markdown like this document). Variables with the new <code>rsi</code> class of this AMR package are actually ordered factors and have three classes (look at <code>Class</code> in the header):</p> <p>All classes will be printed into the header (default is <code>FALSE</code> when using markdown like this document). Variables with the new <code>rsi</code> class of this AMR package are actually ordered factors and have three classes (look at <code>Class</code> in the header):</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a> <div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb9-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(amox, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div> <a class="sourceLine" id="cb9-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(amox, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<p><strong>Frequency table</strong><br> <p><strong>Frequency table of <code>amox</code> from a <code>data.frame</code> (2,000 x 49)</strong><br>
Class: factor &gt; ordered &gt; rsi (numeric)<br> Class: <code>factor</code> &gt; <code>ordered</code> &gt; <code>rsi</code> (<code>numeric</code>)<br>
Levels: S &lt; I &lt; R<br> Levels: S &lt; I &lt; R<br>
Length: 2,000 (of which NA: 828 = 41.40%)<br> Length: 2,000 (of which NA: 828 = 41.40%)<br>
Unique: 3</p> Unique: 3</p>
@ -623,8 +641,8 @@ Unique: 3</p>
<p>Frequencies of dates will show the oldest and newest date in the data, and the amount of days between them:</p> <p>Frequencies of dates will show the oldest and newest date in the data, and the amount of days between them:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a> <div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb10-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(date, <span class="dt">nmax =</span> <span class="dv">5</span>, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div> <a class="sourceLine" id="cb10-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(date, <span class="dt">nmax =</span> <span class="dv">5</span>, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<p><strong>Frequency table</strong><br> <p><strong>Frequency table of <code>date</code> from a <code>data.frame</code> (2,000 x 49)</strong><br>
Class: Date (numeric)<br> Class: <code>Date</code> (<code>numeric</code>)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br> Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 1,140</p> Unique: 1,140</p>
<p>Oldest: 2 January 2002<br> <p>Oldest: 2 January 2002<br>
@ -705,7 +723,12 @@ Median: 31 July 2009 (47.39%)</p>
<p>With the <code>na.rm</code> parameter (defaults to <code>TRUE</code>, but they will always be shown into the header), you can include <code>NA</code> values in the frequency table:</p> <p>With the <code>na.rm</code> parameter (defaults to <code>TRUE</code>, but they will always be shown into the header), you can include <code>NA</code> values in the frequency table:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a> <div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb13-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(amox, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>)</a></code></pre></div> <a class="sourceLine" id="cb13-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(amox, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table of <code>amox</code> from a <code>data.frame</code> (2,000 x 49)</strong><br>
Class: <code>factor</code> &gt; <code>ordered</code> &gt; <code>rsi</code> (<code>numeric</code>)<br>
Levels: S &lt; I &lt; R<br>
Length: 2,828 (of which NA: 828 = 29.28%)<br>
Unique: 4</p>
<p>%IR: 34.30% (ratio S : IR = 1.0 : 1.4)</p>
<table class="table"> <table class="table">
<thead><tr class="header"> <thead><tr class="header">
<th align="left"></th> <th align="left"></th>
@ -758,7 +781,11 @@ Median: 31 July 2009 (47.39%)</p>
<p>The default frequency tables shows row indices. To remove them, use <code>row.names = FALSE</code>:</p> <p>The default frequency tables shows row indices. To remove them, use <code>row.names = FALSE</code>:</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a> <div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb14-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">row.names =</span> <span class="ot">FALSE</span>)</a></code></pre></div> <a class="sourceLine" id="cb14-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">row.names =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table of <code>hospital_id</code> from a <code>data.frame</code> (2,000 x 49)</strong><br>
Class: <code>factor</code> (<code>numeric</code>)<br>
Levels: A, B, C, D<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 4</p>
<table class="table"> <table class="table">
<thead><tr class="header"> <thead><tr class="header">
<th align="left">Item</th> <th align="left">Item</th>
@ -806,7 +833,11 @@ Median: 31 July 2009 (47.39%)</p>
<p>The <code>markdown</code> parameter is <code>TRUE</code> at default in non-interactive sessions, like in reports created with R Markdown. This will always print all rows, unless <code>nmax</code> is set.</p> <p>The <code>markdown</code> parameter is <code>TRUE</code> at default in non-interactive sessions, like in reports created with R Markdown. This will always print all rows, unless <code>nmax</code> is set.</p>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a> <div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">markdown =</span> <span class="ot">TRUE</span>)</a></code></pre></div> <a class="sourceLine" id="cb15-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">markdown =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table of <code>hospital_id</code> from a <code>data.frame</code> (2,000 x 49)</strong><br>
Class: <code>factor</code> (<code>numeric</code>)<br>
Levels: A, B, C, D<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 4</p>
<table class="table"> <table class="table">
<thead><tr class="header"> <thead><tr class="header">
<th align="left"></th> <th align="left"></th>

2
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@ -78,7 +78,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9017</span>
</span> </span>
</div> </div>

4
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@ -40,7 +40,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9015</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span>
</span> </span>
</div> </div>
@ -185,7 +185,7 @@
<h1>How to get properties of a microorganism</h1> <h1>How to get properties of a microorganism</h1>
<h4 class="author">Matthijs S. Berends</h4> <h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">29 January 2019</h4> <h4 class="date">08 February 2019</h4>
<div class="hidden name"><code>mo_property.Rmd</code></div> <div class="hidden name"><code>mo_property.Rmd</code></div>

2
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@ -78,7 +78,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a> <a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9017</span>
</span> </span>
</div> </div>

4
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@ -27,6 +27,10 @@
height: 43px; height: 43px;
margin-top: 2px; margin-top: 2px;
} }
.partner_logo {
width: 19%;
min-width: 125px;
}
@media only screen and (max-width: 992px) { @media only screen and (max-width: 992px) {
.footer_logo { .footer_logo {
float: left; float: left;

47
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@ -42,7 +42,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a> <a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9017</span>
</span> </span>
</div> </div>
@ -190,7 +190,7 @@
<p><em>(<help title="Too Long, Didn't Read">TLDR</help> - to find out how to conduct AMR analysis, please <a href="./articles/AMR.html">continue reading here to get started</a>.</em></p> <p><em>(<help title="Too Long, Didn't Read">TLDR</help> - to find out how to conduct AMR analysis, please <a href="./articles/AMR.html">continue reading here to get started</a>.</em></p>
<hr> <hr>
<p><code>AMR</code> is a free and open-source <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.</p> <p><code>AMR</code> is a free and open-source <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.</p>
<p>After installing this package, R knows almost all ~20.000 microorganisms and ~500 antibiotics by name and code, and knows all about valid RSI and MIC values.</p> <p>After installing this package, R knows almost all ~20,000 microorganisms and ~500 antibiotics by name and code, and knows all about valid RSI and MIC values.</p>
<p>We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology &amp; Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but <strong>not</strong> patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. Read the full license <a href="./LICENSE-text.html">here</a>.</p> <p>We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology &amp; Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but <strong>not</strong> patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. Read the full license <a href="./LICENSE-text.html">here</a>.</p>
<p>This package can be used for:</p> <p>This package can be used for:</p>
<ul> <ul>
@ -238,15 +238,15 @@
<h4 class="hasAnchor"> <h4 class="hasAnchor">
<a href="#latest-released-version" class="anchor"></a>Latest released version</h4> <a href="#latest-released-version" class="anchor"></a>Latest released version</h4>
<p>This package is available <a href="https://cran.r-project.org/package=AMR">on the official R network (CRAN)</a>, which has a peer-reviewed submission process. Install this package in R with:</p> <p>This package is available <a href="https://cran.r-project.org/package=AMR">on the official R network (CRAN)</a>, which has a peer-reviewed submission process. Install this package in R with:</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="st">"AMR"</span>)</code></pre></div> <div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="st">"AMR"</span>)</a></code></pre></div>
<p>It will be downloaded and installed automatically. For RStudio, click on the menu <em>Tools</em> &gt; <em>Install Packages…</em> and then type in “AMR” and press <kbd>Install</kbd>.</p> <p>It will be downloaded and installed automatically. For RStudio, click on the menu <em>Tools</em> &gt; <em>Install Packages…</em> and then type in “AMR” and press <kbd>Install</kbd>.</p>
</div> </div>
<div id="latest-development-version" class="section level4"> <div id="latest-development-version" class="section level4">
<h4 class="hasAnchor"> <h4 class="hasAnchor">
<a href="#latest-development-version" class="anchor"></a>Latest development version</h4> <a href="#latest-development-version" class="anchor"></a>Latest development version</h4>
<p>The latest and unpublished development version can be installed with (precaution: may be unstable):</p> <p>The latest and unpublished development version can be installed with (precaution: may be unstable):</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="st">"devtools"</span>) <div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="st">"devtools"</span>)</a>
devtools::<span class="kw">install_gitlab</span>(<span class="st">"msberends/AMR"</span>)</code></pre></div> <a class="sourceLine" id="cb2-2" data-line-number="2">devtools<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/devtools/topics/reexports">install_gitlab</a></span>(<span class="st">"msberends/AMR"</span>)</a></code></pre></div>
</div> </div>
</div> </div>
<div id="get-started" class="section level2"> <div id="get-started" class="section level2">
@ -261,7 +261,7 @@ devtools::<span class="kw">install_gitlab</span>(<span class="st">"msberends/AMR
<h4 class="hasAnchor"> <h4 class="hasAnchor">
<a href="#whonet-ears-net" class="anchor"></a>WHONET / EARS-Net</h4> <a href="#whonet-ears-net" class="anchor"></a>WHONET / EARS-Net</h4>
<p><img src="./whonet.png"></p> <p><img src="./whonet.png"></p>
<p>We support WHONET and EARS-Net data. Exported files from WHONET can be imported into R and can be analysed easily using this package. For education purposes, we created an <a href="./reference/WHONET.html">example data set <code>WHONET</code></a> with the exact same structure and a WHONET export file. Furthermore, this package also contains a <a href="./reference/antibiotics.html">data set <code>antibiotics</code></a> with all EARS-Net antibiotic abbreviations. When using WHONET data as input for analysis, all input parameters will be set automatically.</p> <p>We support WHONET and EARS-Net data. Exported files from WHONET can be imported into R and can be analysed easily using this package. For education purposes, we created an <a href="./reference/WHONET.html">example data set <code>WHONET</code></a> with the exact same structure and a WHONET export file. Furthermore, this package also contains a <a href="./reference/antibiotics.html">data set <code>antibiotics</code></a> with all EARS-Net antibiotic abbreviations, and knows almost all WHONET abbreviations for microorganisms. When using WHONET data as input for analysis, all input parameters will be set automatically.</p>
<p>Read our tutorial about <a href="./articles/WHONET.html">how to work with WHONET data here</a>.</p> <p>Read our tutorial about <a href="./articles/WHONET.html">how to work with WHONET data here</a>.</p>
</div> </div>
<div id="antimicrobial-reference-data" class="section level4"> <div id="antimicrobial-reference-data" class="section level4">
@ -286,17 +286,17 @@ devtools::<span class="kw">install_gitlab</span>(<span class="st">"msberends/AMR
<a href="#overview-of-functions" class="anchor"></a>Overview of functions</h4> <a href="#overview-of-functions" class="anchor"></a>Overview of functions</h4>
<p>The <code>AMR</code> package basically does four important things:</p> <p>The <code>AMR</code> package basically does four important things:</p>
<ol> <ol>
<li>It <strong>cleanses existing data</strong> by providing new <em>classes</em> for microoganisms, antibiotics and antimicrobial results (both S/I/R and MIC). By installing this package, you teach R everything about microbiology that is needed for analysis. These functions all use artificial intelligence to guess results that you would expect:</li> <li>
</ol> <p>It <strong>cleanses existing data</strong> by providing new <em>classes</em> for microoganisms, antibiotics and antimicrobial results (both S/I/R and MIC). By installing this package, you teach R everything about microbiology that is needed for analysis. These functions all use artificial intelligence to guess results that you would expect:</p>
<ul> <ul>
<li>Use <code><a href="reference/as.mo.html">as.mo()</a></code> to get an ID of a microorganism. The IDs are human readable for the trained eye - the ID of <em>Klebsiella pneumoniae</em> is “B_KLBSL_PNE” (B stands for Bacteria) and the ID of <em>S. aureus</em> is “B_STPHY_AUR”. The function takes almost any text as input that looks like the name or code of a microorganism like “E. coli”, “esco” or “esccol” and tries to find expected results using artificial intelligence (AI) on the included ITIS data set, consisting of almost 20,000 microorganisms. It is <em>very</em> fast, please see our <a href="./articles/benchmarks.html">benchmarks</a>. Moreover, it can group <em>Staphylococci</em> into coagulase negative and positive (CoNS and CoPS, see <a href="./reference/as.mo.html#source">source</a>) and can categorise <em>Streptococci</em> into Lancefield groups (like beta-haemolytic <em>Streptococcus</em> Group B, <a href="./reference/as.mo.html#source">source</a>).</li> <li>Use <code><a href="reference/as.mo.html">as.mo()</a></code> to get an ID of a microorganism. The IDs are human readable for the trained eye - the ID of <em>Klebsiella pneumoniae</em> is “B_KLBSL_PNE” (B stands for Bacteria) and the ID of <em>S. aureus</em> is “B_STPHY_AUR”. The function takes almost any text as input that looks like the name or code of a microorganism like “E. coli”, “esco” or “esccol” and tries to find expected results using artificial intelligence (AI) on the included ITIS data set, consisting of almost 20,000 microorganisms. It is <em>very</em> fast, please see our <a href="./articles/benchmarks.html">benchmarks</a>. Moreover, it can group <em>Staphylococci</em> into coagulase negative and positive (CoNS and CoPS, see <a href="./reference/as.mo.html#source">source</a>) and can categorise <em>Streptococci</em> into Lancefield groups (like beta-haemolytic <em>Streptococcus</em> Group B, <a href="./reference/as.mo.html#source">source</a>).</li>
<li>Use <code><a href="reference/as.rsi.html">as.rsi()</a></code> to transform values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like “&lt;=0.002; S” (combined MIC/RSI) will result in “S”.</li> <li>Use <code><a href="reference/as.rsi.html">as.rsi()</a></code> to transform values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like “&lt;=0.002; S” (combined MIC/RSI) will result in “S”.</li>
<li>Use <code><a href="reference/as.mic.html">as.mic()</a></code> to cleanse your MIC values. It produces a so-called factor (called <em>ordinal</em> in SPSS) with valid MIC values as levels. A value like “&lt;=0.002; S” (combined MIC/RSI) will result in “&lt;=0.002”.</li> <li>Use <code><a href="reference/as.mic.html">as.mic()</a></code> to cleanse your MIC values. It produces a so-called factor (called <em>ordinal</em> in SPSS) with valid MIC values as levels. A value like “&lt;=0.002; S” (combined MIC/RSI) will result in “&lt;=0.002”.</li>
<li>Use <code><a href="reference/as.atc.html">as.atc()</a></code> to get the ATC code of an antibiotic as defined by the WHO. This package contains a database with most LIS codes, official names, DDDs and even trade names of antibiotics. For example, the values “Furabid”, “Furadantin”, “nitro” all return the ATC code of Nitrofurantoine.</li> <li>Use <code><a href="reference/as.atc.html">as.atc()</a></code> to get the ATC code of an antibiotic as defined by the WHO. This package contains a database with most LIS codes, official names, DDDs and even trade names of antibiotics. For example, the values “Furabid”, “Furadantin”, “nitro” all return the ATC code of Nitrofurantoine.</li>
</ul> </ul>
<ol> </li>
<li>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</li> <li>
</ol> <p>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</p>
<ul> <ul>
<li>Use <code><a href="reference/eucast_rules.html">eucast_rules()</a></code> to apply <a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST expert rules to isolates</a>.</li> <li>Use <code><a href="reference/eucast_rules.html">eucast_rules()</a></code> to apply <a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST expert rules to isolates</a>.</li>
<li>Use <code><a href="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of every patient <a href="https://clsi.org/standards/products/microbiology/documents/m39/">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute). <li>Use <code><a href="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of every patient <a href="https://clsi.org/standards/products/microbiology/documents/m39/">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
@ -308,9 +308,9 @@ devtools::<span class="kw">install_gitlab</span>(<span class="st">"msberends/AMR
<li>The <a href="./reference/microorganisms.html">data set <code>microorganisms</code></a> contains the complete taxonomic tree of almost 20,000 microorganisms (bacteria, fungi/yeasts and protozoa). Furthermore, the colloquial name and Gram stain are available, which enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like <code><a href="reference/mo_property.html">mo_genus()</a></code>, <code><a href="reference/mo_property.html">mo_family()</a></code>, <code><a href="reference/mo_property.html">mo_gramstain()</a></code> or even <code><a href="reference/mo_property.html">mo_phylum()</a></code>. As they use <code><a href="reference/as.mo.html">as.mo()</a></code> internally, they also use artificial intelligence. For example, <code><a href="reference/mo_property.html">mo_genus("MRSA")</a></code> and <code><a href="reference/mo_property.html">mo_genus("S. aureus")</a></code> will both return <code>"Staphylococcus"</code>. They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.</li> <li>The <a href="./reference/microorganisms.html">data set <code>microorganisms</code></a> contains the complete taxonomic tree of almost 20,000 microorganisms (bacteria, fungi/yeasts and protozoa). Furthermore, the colloquial name and Gram stain are available, which enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like <code><a href="reference/mo_property.html">mo_genus()</a></code>, <code><a href="reference/mo_property.html">mo_family()</a></code>, <code><a href="reference/mo_property.html">mo_gramstain()</a></code> or even <code><a href="reference/mo_property.html">mo_phylum()</a></code>. As they use <code><a href="reference/as.mo.html">as.mo()</a></code> internally, they also use artificial intelligence. For example, <code><a href="reference/mo_property.html">mo_genus("MRSA")</a></code> and <code><a href="reference/mo_property.html">mo_genus("S. aureus")</a></code> will both return <code>"Staphylococcus"</code>. They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.</li>
<li>The <a href="./reference/antibiotics.html">data set <code>antibiotics</code></a> contains almost 500 antimicrobial drugs with their ATC code, EARS-Net code, common LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains hundreds of trade names. Use functions like <code><a href="reference/atc_property.html">atc_name()</a></code> and <code><a href="reference/atc_property.html">atc_tradenames()</a></code> to look up values. The <code>atc_*</code> functions use <code><a href="reference/as.atc.html">as.atc()</a></code> internally so they support AI to guess your expected result. For example, <code><a href="reference/atc_property.html">atc_name("Fluclox")</a></code>, <code><a href="reference/atc_property.html">atc_name("Floxapen")</a></code> and <code><a href="reference/atc_property.html">atc_name("J01CF05")</a></code> will all return <code>"Flucloxacillin"</code>. These functions can again be used to add new variables to your data.</li> <li>The <a href="./reference/antibiotics.html">data set <code>antibiotics</code></a> contains almost 500 antimicrobial drugs with their ATC code, EARS-Net code, common LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains hundreds of trade names. Use functions like <code><a href="reference/atc_property.html">atc_name()</a></code> and <code><a href="reference/atc_property.html">atc_tradenames()</a></code> to look up values. The <code>atc_*</code> functions use <code><a href="reference/as.atc.html">as.atc()</a></code> internally so they support AI to guess your expected result. For example, <code><a href="reference/atc_property.html">atc_name("Fluclox")</a></code>, <code><a href="reference/atc_property.html">atc_name("Floxapen")</a></code> and <code><a href="reference/atc_property.html">atc_name("J01CF05")</a></code> will all return <code>"Flucloxacillin"</code>. These functions can again be used to add new variables to your data.</li>
</ul> </ul>
<ol> </li>
<li>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</li> <li>
</ol> <p>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</p>
<ul> <ul>
<li>Calculate the resistance (and even co-resistance) of microbial isolates with the <code><a href="reference/portion.html">portion_R()</a></code>, <code><a href="reference/portion.html">portion_IR()</a></code>, <code><a href="reference/portion.html">portion_I()</a></code>, <code><a href="reference/portion.html">portion_SI()</a></code> and <code><a href="reference/portion.html">portion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><a href="reference/count.html">count_R()</a></code>, <code><a href="reference/count.html">count_IR()</a></code>, <code><a href="reference/count.html">count_I()</a></code>, <code><a href="reference/count.html">count_SI()</a></code> and <code><a href="reference/count.html">count_S()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g. in conjunction with <code>summarise()</code>)</li> <li>Calculate the resistance (and even co-resistance) of microbial isolates with the <code><a href="reference/portion.html">portion_R()</a></code>, <code><a href="reference/portion.html">portion_IR()</a></code>, <code><a href="reference/portion.html">portion_I()</a></code>, <code><a href="reference/portion.html">portion_SI()</a></code> and <code><a href="reference/portion.html">portion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><a href="reference/count.html">count_R()</a></code>, <code><a href="reference/count.html">count_IR()</a></code>, <code><a href="reference/count.html">count_I()</a></code>, <code><a href="reference/count.html">count_SI()</a></code> and <code><a href="reference/count.html">count_S()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g. in conjunction with <code>summarise()</code>)</li>
<li>Plot AMR results with <code><a href="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for the <code>ggplot2</code> package</li> <li>Plot AMR results with <code><a href="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for the <code>ggplot2</code> package</li>
@ -318,25 +318,32 @@ devtools::<span class="kw">install_gitlab</span>(<span class="st">"msberends/AMR
<li>Conduct descriptive statistics to enhance base R: calculate <code><a href="reference/kurtosis.html">kurtosis()</a></code>, <code><a href="reference/skewness.html">skewness()</a></code> and create frequency tables with <code><a href="reference/freq.html">freq()</a></code> <li>Conduct descriptive statistics to enhance base R: calculate <code><a href="reference/kurtosis.html">kurtosis()</a></code>, <code><a href="reference/skewness.html">skewness()</a></code> and create frequency tables with <code><a href="reference/freq.html">freq()</a></code>
</li> </li>
</ul> </ul>
<ol> </li>
<li>It <strong>teaches the user</strong> how to use all the above actions.</li> <li>
</ol> <p>It <strong>teaches the user</strong> how to use all the above actions.</p>
<ul> <ul>
<li>Aside from this website with many tutorials, the package itself contains extensive help pages with many examples for all functions.</li> <li>Aside from this website with many tutorials, the package itself contains extensive help pages with many examples for all functions.</li>
<li>It also contains an <a href=".reference/septic_patients.html">example data set called <code>septic_patients</code></a>. This data set contains: <li>The package also contains example data sets:
<ul>
<li>The <a href=".reference/septic_patients.html"><code>septic_patients</code> data set</a>. This data set contains:
<ul> <ul>
<li>2,000 blood culture isolates from anonymised septic patients between 2001 and 2017 in the Northern Netherlands</li> <li>2,000 blood culture isolates from anonymised septic patients between 2001 and 2017 in the Northern Netherlands</li>
<li>Results of 40 antibiotics (each antibiotic in its own column) with a total of 38,414 antimicrobial results</li> <li>Results of 40 antibiotics (each antibiotic in its own column) with a total ~40,000 antimicrobial results</li>
<li>Real and genuine data</li> <li>Real and genuine data</li>
</ul> </ul>
</li> </li>
<li>The <a href=".reference/WHONET.html"><code>WHONET</code> data set</a>. This data set only contains fake data, but with the exact same structure as files exported by WHONET. Read more about WHONET <a href="./articles/WHONET.html">on its tutorial page</a>.</li>
</ul> </ul>
</li>
</ul>
</li>
</ol>
</div> </div>
<div id="partners" class="section level4"> <div id="partners" class="section level4">
<h4 class="hasAnchor"> <h4 class="hasAnchor">
<a href="#partners" class="anchor"></a>Partners</h4> <a href="#partners" class="anchor"></a>Partners</h4>
<p>The development of this package is part of, related to, or made possible by:</p> <p>The development of this package is part of, related to, or made possible by:</p>
<p><a href="https://www.rug.nl"><img src="./logo_rug.png" height="50px"></a> <a href="https://www.umcg.nl"><img src="./logo_umcg.png" height="50px"></a> <a href="https://www.certe.nl"><img src="./logo_certe.png" height="50px"></a> <a href="http://www.eurhealth-1health.eu"><img src="./logo_eh1h.png" height="50px"></a> <a href="http://www.eurhealth-1health.eu"><img src="./logo_interreg.png" height="50px"></a></p> <p><a href="https://www.rug.nl"><img src="./logo_rug.png" class="partner_logo"></a> <a href="https://www.umcg.nl"><img src="./logo_umcg.png" class="partner_logo"></a> <a href="https://www.certe.nl"><img src="./logo_certe.png" class="partner_logo"></a> <a href="http://www.eurhealth-1health.eu"><img src="./logo_eh1h.png" class="partner_logo"></a> <a href="http://www.eurhealth-1health.eu"><img src="./logo_interreg.png" class="partner_logo"></a></p>
</div> </div>
</div> </div>
</div> </div>

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@ -78,7 +78,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9017</span>
</span> </span>
</div> </div>
@ -236,58 +236,101 @@
<ul> <ul>
<li> <li>
<strong>BREAKING</strong>: removed deprecated functions, parameters and references to ‘bactid’. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> to identify an MO code.</li> <strong>BREAKING</strong>: removed deprecated functions, parameters and references to ‘bactid’. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> to identify an MO code.</li>
<li>Support for data from <a href="https://whonet.org/">WHONET</a> and <a href="https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net">EARS-Net</a> (European Antimicrobial Resistance Surveillance Network):</li> <li>Support for data from <a href="https://whonet.org/">WHONET</a> and <a href="https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net">EARS-Net</a> (European Antimicrobial Resistance Surveillance Network):
<ul>
<li>Exported files from WHONET can be read and used in this package. For functions like <code><a href="../reference/first_isolate.html">first_isolate()</a></code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>, all parameters will be filled in automatically.</li> <li>Exported files from WHONET can be read and used in this package. For functions like <code><a href="../reference/first_isolate.html">first_isolate()</a></code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>, all parameters will be filled in automatically.</li>
<li>This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the <code>antibiotics</code> data set now contains a column <code>ears_net</code>.</li> <li>This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the <code>antibiotics</code> data set now contains a column <code>ears_net</code>.</li>
<li>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions: <code>r ab_property -&gt; atc_property() ab_name -&gt; atc_name() ab_official -&gt; atc_official() ab_trivial_nl -&gt; atc_trivial_nl() ab_certe -&gt; atc_certe() ab_umcg -&gt; atc_umcg() ab_tradenames -&gt; atc_tradenames()</code> These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code> internally. The old <code>atc_property</code> has been renamed <code><a href="../reference/atc_online.html">atc_online_property()</a></code>. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class <code>atc</code> or must be coerable to this class. Properties of these classes should start with the same class name, analogous to <code><a href="../reference/as.mo.html">as.mo()</a></code> and e.g. <code>mo_genus</code>.</li> <li>The function <code><a href="../reference/as.mo.html">as.mo()</a></code> now knows all WHONET species abbreviations too, because more than 1,600 microbial abbreviations were added to the <code>microorganisms.codes</code> data set.</li>
<li>New website: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a> (built with the great <a href="https://pkgdown.r-lib.org/"><code>pkgdown</code></a>)</li> </ul>
</li>
<li>
<p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1">ab_property -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_property</a></span>()</a>
<a class="sourceLine" id="cb1-2" data-line-number="2">ab_name -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_name</a></span>()</a>
<a class="sourceLine" id="cb1-3" data-line-number="3">ab_official -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_official</a></span>()</a>
<a class="sourceLine" id="cb1-4" data-line-number="4">ab_trivial_nl -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_trivial_nl</a></span>()</a>
<a class="sourceLine" id="cb1-5" data-line-number="5">ab_certe -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_certe</a></span>()</a>
<a class="sourceLine" id="cb1-6" data-line-number="6">ab_umcg -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_umcg</a></span>()</a>
<a class="sourceLine" id="cb1-7" data-line-number="7">ab_tradenames -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_tradenames</a></span>()</a></code></pre></div>
These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code> internally. The old <code>atc_property</code> has been renamed <code><a href="../reference/atc_online.html">atc_online_property()</a></code>. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class <code>atc</code> or must be coerable to this class. Properties of these classes should start with the same class name, analogous to <code><a href="../reference/as.mo.html">as.mo()</a></code> and e.g. <code>mo_genus</code>.</li>
<li>New website: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a> (built with the great <a href="https://pkgdown.r-lib.org/"><code>pkgdown</code></a>)
<ul>
<li>Contains the complete manual of this package and all of its functions with an explanation of their parameters</li> <li>Contains the complete manual of this package and all of its functions with an explanation of their parameters</li>
<li>Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis</li> <li>Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis</li>
</ul>
</li>
<li>New functions <code><a href="../reference/mo_source.html">set_mo_source()</a></code> and <code><a href="../reference/mo_source.html">get_mo_source()</a></code> to use your own predefined MO codes as input for <code><a href="../reference/as.mo.html">as.mo()</a></code> and consequently all <code>mo_*</code> functions</li> <li>New functions <code><a href="../reference/mo_source.html">set_mo_source()</a></code> and <code><a href="../reference/mo_source.html">get_mo_source()</a></code> to use your own predefined MO codes as input for <code><a href="../reference/as.mo.html">as.mo()</a></code> and consequently all <code>mo_*</code> functions</li>
<li>Support for the upcoming <a href="https://dplyr.tidyverse.org"><code>dplyr</code></a> version 0.8.0</li> <li>Support for the upcoming <a href="https://dplyr.tidyverse.org"><code>dplyr</code></a> version 0.8.0</li>
<li>New function <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code> to find an antibiotic column in a table</li> <li>New function <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code> to find an antibiotic column in a table</li>
<li>New function <code><a href="../reference/mo_failures.html">mo_failures()</a></code> to review values that could not be coerced to a valid MO code, using <code><a href="../reference/as.mo.html">as.mo()</a></code>. This latter function will now only show a maximum of 10 uncoerced values and will refer to <code><a href="../reference/mo_failures.html">mo_failures()</a></code>.</li> <li>New function <code><a href="../reference/as.mo.html">mo_failures()</a></code> to review values that could not be coerced to a valid MO code, using <code><a href="../reference/as.mo.html">as.mo()</a></code>. This latter function will now only show a maximum of 10 uncoerced values and will refer to <code><a href="../reference/as.mo.html">mo_failures()</a></code>.</li>
<li>New function <code><a href="../reference/mo_renamed.html">mo_renamed()</a></code> to get a list of all returned values from <code><a href="../reference/as.mo.html">as.mo()</a></code> that have had taxonomic renaming</li> <li>New function <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code> to review values that could be coerced to a valid MO code using <code><a href="../reference/as.mo.html">as.mo()</a></code>, but with uncertainty.</li>
<li>New function <code><a href="../reference/as.mo.html">mo_renamed()</a></code> to get a list of all returned values from <code><a href="../reference/as.mo.html">as.mo()</a></code> that have had taxonomic renaming</li>
<li>New function <code><a href="../reference/age.html">age()</a></code> to calculate the (patients) age in years</li> <li>New function <code><a href="../reference/age.html">age()</a></code> to calculate the (patients) age in years</li>
<li>New function <code><a href="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</li> <li>New function <code><a href="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</li>
<li>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>: <code>r x &lt;- resistance_predict(septic_patients, col_ab = "amox") plot(x) ggplot_rsi_predict(x)</code> <li>
<p>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(septic_patients, <span class="dt">col_ab =</span> <span class="st">"amox"</span>)</a>
<a class="sourceLine" id="cb2-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot</a></span>(x)</a>
<a class="sourceLine" id="cb2-3" data-line-number="3"><span class="kw"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(x)</a></code></pre></div>
</li> </li>
<li>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.: <code>r septic_patients %&gt;% filter_first_isolate(...) # or filter_first_isolate(septic_patients, ...)</code> is equal to: <code>r septic_patients %&gt;% mutate(only_firsts = first_isolate(septic_patients, ...)) %&gt;% filter(only_firsts == TRUE) %&gt;% select(-only_firsts)</code> <li>
<p>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(...)</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="co"># or</span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(septic_patients, ...)</a></code></pre></div>
<p>is equal to:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="st"> </span><span class="kw">mutate</span>(<span class="dt">only_firsts =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(septic_patients, ...)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/stats/topics/filter">filter</a></span>(only_firsts <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="st"> </span><span class="kw">select</span>(<span class="op">-</span>only_firsts)</a></code></pre></div>
</li> </li>
<li>New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the <em>G</em>-test and more. These are also available (and even easier readable) on our website: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a>.</li> <li>New function <code><a href="../reference/availability.html">availability()</a></code> to check the number of available (non-empty) results in a <code>data.frame</code>
</li>
<li><p>New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the <em>G</em>-test and more. These are also available (and even easier readable) on our website: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a>.</p></li>
</ul> </ul>
</div> </div>
<div id="changed" class="section level4"> <div id="changed" class="section level4">
<h4 class="hasAnchor"> <h4 class="hasAnchor">
<a href="#changed" class="anchor"></a>Changed</h4> <a href="#changed" class="anchor"></a>Changed</h4>
<ul> <ul>
<li>Function <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:
<ul>
<li>Updated EUCAST Clinical breakpoints to <a href="http://www.eucast.org/clinical_breakpoints/">version 9.0 of 1 January 2019</a>, the data set <code>septic_patients</code> now reflects these changes</li>
<li>Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately</li>
<li>Emphasised in manual that penicillin is meant as benzylpenicillin (ATC <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE01">J01CE01</a>)</li>
<li>New info is returned when running this function, stating exactly what has been changed or added. Use <code><a href="../reference/eucast_rules.html">eucast_rules(..., verbose = TRUE)</a></code> to get a data set with all changed per bug and drug combination.</li>
</ul>
</li>
<li>Added 605 <em>Aspergillus</em> species and 23 <em>Trichophyton</em> species to the <code>microorganisms</code> data set</li>
<li>Added 65 antibiotics to the <code>antibiotics</code> data set, from the <a href="http://ec.europa.eu/health/documents/community-register/html/atc.htm">Pharmaceuticals Community Register</a> of the European Commission</li> <li>Added 65 antibiotics to the <code>antibiotics</code> data set, from the <a href="http://ec.europa.eu/health/documents/community-register/html/atc.htm">Pharmaceuticals Community Register</a> of the European Commission</li>
<li>Removed columns <code>atc_group1_nl</code> and <code>atc_group2_nl</code> from the <code>antibiotics</code> data set</li> <li>Removed columns <code>atc_group1_nl</code> and <code>atc_group2_nl</code> from the <code>antibiotics</code> data set</li>
<li>Functions <code><a href="../reference/AMR-deprecated.html">atc_ddd()</a></code> and <code><a href="../reference/AMR-deprecated.html">atc_groups()</a></code> have been renamed <code><a href="../reference/atc_online.html">atc_online_ddd()</a></code> and <code><a href="../reference/atc_online.html">atc_online_groups()</a></code>. The old functions are deprecated and will be removed in a future version.</li> <li>Functions <code><a href="../reference/AMR-deprecated.html">atc_ddd()</a></code> and <code><a href="../reference/AMR-deprecated.html">atc_groups()</a></code> have been renamed <code><a href="../reference/atc_online.html">atc_online_ddd()</a></code> and <code><a href="../reference/atc_online.html">atc_online_groups()</a></code>. The old functions are deprecated and will be removed in a future version.</li>
<li>Function <code><a href="../reference/AMR-deprecated.html">guess_mo()</a></code> is now deprecated in favour of <code><a href="../reference/as.mo.html">as.mo()</a></code> and will be removed in future versions</li> <li>Function <code><a href="../reference/AMR-deprecated.html">guess_mo()</a></code> is now deprecated in favour of <code><a href="../reference/as.mo.html">as.mo()</a></code> and will be removed in future versions</li>
<li>Function <code><a href="../reference/AMR-deprecated.html">guess_atc()</a></code> is now deprecated in favour of <code><a href="../reference/as.atc.html">as.atc()</a></code> and will be removed in future versions</li> <li>Function <code><a href="../reference/AMR-deprecated.html">guess_atc()</a></code> is now deprecated in favour of <code><a href="../reference/as.atc.html">as.atc()</a></code> and will be removed in future versions</li>
<li>Function <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</li> <li>Improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code>:
<li>Updated EUCAST Clinical breakpoints to <a href="http://www.eucast.org/clinical_breakpoints/">version 9.0 of 1 January 2019</a> <ul>
</li>
<li>Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately</li>
<li>Emphasised in manual that penicillin is meant as benzylpenicillin (ATC <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE01">J01CE01</a>)</li>
<li>Improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code>:</li>
<li>Fix for vector containing only empty values</li> <li>Fix for vector containing only empty values</li>
<li>Finds better results when input is in other languages</li> <li>Finds better results when input is in other languages</li>
<li>Better handling for subspecies</li> <li>Better handling for subspecies</li>
<li>Better handling for <em>Salmonellae</em> <li>Better handling for <em>Salmonellae</em>
</li> </li>
<li>Understanding of highly virulent <em>E. coli</em> strains like EIEC, EPEC and STEC</li>
<li>There will be looked for uncertain results at default - these results will be returned with an informative warning</li> <li>There will be looked for uncertain results at default - these results will be returned with an informative warning</li>
<li>Manual now contains more info about the algorithms</li> <li>Manual now contains more info about the algorithms</li>
<li>Progress bar will be shown when it takes more than 3 seconds to get results</li> <li>Progress bar will be shown when it takes more than 3 seconds to get results</li>
<li>Support for formatted console text</li> <li>Support for formatted console text</li>
<li>Console will return the percentage of uncoercable input</li> <li>Console will return the percentage of uncoercable input</li>
<li>Function <code><a href="../reference/first_isolate.html">first_isolate()</a></code>:</li> </ul>
</li>
<li>Function <code><a href="../reference/first_isolate.html">first_isolate()</a></code>:
<ul>
<li>Fixed a bug where distances between dates would not be calculated right - in the <code>septic_patients</code> data set this yielded a difference of 0.15% more isolates</li> <li>Fixed a bug where distances between dates would not be calculated right - in the <code>septic_patients</code> data set this yielded a difference of 0.15% more isolates</li>
<li>Will now use a column named like “patid” for the patient ID (parameter <code>col_patientid</code>), when this parameter was left blank</li> <li>Will now use a column named like “patid” for the patient ID (parameter <code>col_patientid</code>), when this parameter was left blank</li>
<li>Will now use a column named like “key(…)ab” or “key(…)antibiotics” for the key antibiotics (parameter <code>col_keyantibiotics()</code>), when this parameter was left blank</li> <li>Will now use a column named like “key(…)ab” or “key(…)antibiotics” for the key antibiotics (parameter <code>col_keyantibiotics()</code>), when this parameter was left blank</li>
<li>Removed parameter <code>output_logical</code>, the function will now always return a logical value</li> <li>Removed parameter <code>output_logical</code>, the function will now always return a logical value</li>
<li>Renamed parameter <code>filter_specimen</code> to <code>specimen_group</code>, although using <code>filter_specimen</code> will still work</li> <li>Renamed parameter <code>filter_specimen</code> to <code>specimen_group</code>, although using <code>filter_specimen</code> will still work</li>
</ul>
</li>
<li>A note to the manual pages of the <code>portion</code> functions, that low counts can influence the outcome and that the <code>portion</code> functions may camouflage this, since they only return the portion (albeit being dependent on the <code>minimum</code> parameter)</li> <li>A note to the manual pages of the <code>portion</code> functions, that low counts can influence the outcome and that the <code>portion</code> functions may camouflage this, since they only return the portion (albeit being dependent on the <code>minimum</code> parameter)</li>
<li>Merged data sets <code>microorganisms.certe</code> and <code>microorganisms.umcg</code> into <code>microorganisms.codes</code> <li>Merged data sets <code>microorganisms.certe</code> and <code>microorganisms.umcg</code> into <code>microorganisms.codes</code>
</li> </li>
@ -299,22 +342,23 @@
</li> </li>
<li>Small text updates to summaries of class <code>rsi</code> and <code>mic</code> <li>Small text updates to summaries of class <code>rsi</code> and <code>mic</code>
</li> </li>
<li>Frequency tables (<code><a href="../reference/freq.html">freq()</a></code> function):</li> <li>Frequency tables (<code><a href="../reference/freq.html">freq()</a></code> function):
<ul>
<li> <li>
<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p> <p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span> <div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span></a>
<span class="co"># OLD WAY</span> <a class="sourceLine" id="cb5-2" data-line-number="2"><span class="co"># OLD WAY</span></a>
septic_patients %&gt;% <a class="sourceLine" id="cb5-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span></a>
<span class="st"> </span><span class="kw">mutate</span>(<span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) %&gt;% <a class="sourceLine" id="cb5-4" data-line-number="4"><span class="st"> </span><span class="kw">mutate</span>(<span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) <span class="op">%&gt;%</span></a>
<span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus) <a class="sourceLine" id="cb5-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus)</a>
<span class="co"># NEW WAY</span> <a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># NEW WAY</span></a>
septic_patients %&gt;%<span class="st"> </span> <a class="sourceLine" id="cb5-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) <a class="sourceLine" id="cb5-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a>
<a class="sourceLine" id="cb5-9" data-line-number="9"></a>
<span class="co"># Even supports grouping variables:</span> <a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># Even supports grouping variables:</span></a>
septic_patients %&gt;% <a class="sourceLine" id="cb5-11" data-line-number="11">septic_patients <span class="op">%&gt;%</span></a>
<span class="st"> </span><span class="kw">group_by</span>(gender) %&gt;%<span class="st"> </span> <a class="sourceLine" id="cb5-12" data-line-number="12"><span class="st"> </span><span class="kw">group_by</span>(gender) <span class="op">%&gt;%</span><span class="st"> </span></a>
<span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</code></pre></div> <a class="sourceLine" id="cb5-13" data-line-number="13"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a></code></pre></div>
</li> </li>
<li>Header info is now available as a list, with the <code>header</code> function</li> <li>Header info is now available as a list, with the <code>header</code> function</li>
<li>The parameter <code>header</code> is now set to <code>TRUE</code> at default, even for markdown</li> <li>The parameter <code>header</code> is now set to <code>TRUE</code> at default, even for markdown</li>
@ -327,11 +371,13 @@ septic_patients %&gt;%
<li>New parameter <code>droplevels</code> to exclude empty factor levels when input is a factor</li> <li>New parameter <code>droplevels</code> to exclude empty factor levels when input is a factor</li>
<li>Factor levels will be in header when present in input data (maximum of 5)</li> <li>Factor levels will be in header when present in input data (maximum of 5)</li>
<li>Fix for using <code>select()</code> on frequency tables</li> <li>Fix for using <code>select()</code> on frequency tables</li>
</ul>
</li>
<li>Function <code><a href="../reference/ggplot_rsi.html">scale_y_percent()</a></code> now contains the <code>limits</code> parameter</li> <li>Function <code><a href="../reference/ggplot_rsi.html">scale_y_percent()</a></code> now contains the <code>limits</code> parameter</li>
<li>Automatic parameter filling for <code><a href="../reference/mdro.html">mdro()</a></code>, <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> <li>Automatic parameter filling for <code><a href="../reference/mdro.html">mdro()</a></code>, <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
</li> </li>
<li>Updated examples for resistance prediction (<code><a href="../reference/resistance_predict.html">resistance_predict()</a></code> function)</li> <li>Updated examples for resistance prediction (<code><a href="../reference/resistance_predict.html">resistance_predict()</a></code> function)</li>
<li><p>Fix for <code><a href="../reference/as.mic.html">as.mic()</a></code> to support more values ending in (several) zeroes</p></li> <li>Fix for <code><a href="../reference/as.mic.html">as.mic()</a></code> to support more values ending in (several) zeroes</li>
</ul> </ul>
</div> </div>
<div id="other" class="section level4"> <div id="other" class="section level4">
@ -368,7 +414,8 @@ septic_patients %&gt;%
</li> </li>
<li> <li>
<code>EUCAST_rules</code> was renamed to <code>eucast_rules</code>, the old function still exists as a deprecated function</li> <code>EUCAST_rules</code> was renamed to <code>eucast_rules</code>, the old function still exists as a deprecated function</li>
<li>Big changes to the <code>eucast_rules</code> function:</li> <li>Big changes to the <code>eucast_rules</code> function:
<ul>
<li>Now also applies rules from the EUCAST ‘Breakpoint tables for bacteria’, version 8.1, 2018, <a href="http://www.eucast.org/clinical_breakpoints/" class="uri">http://www.eucast.org/clinical_breakpoints/</a> (see Source of the function)</li> <li>Now also applies rules from the EUCAST ‘Breakpoint tables for bacteria’, version 8.1, 2018, <a href="http://www.eucast.org/clinical_breakpoints/" class="uri">http://www.eucast.org/clinical_breakpoints/</a> (see Source of the function)</li>
<li>New parameter <code>rules</code> to specify which rules should be applied (expert rules, breakpoints, others or all)</li> <li>New parameter <code>rules</code> to specify which rules should be applied (expert rules, breakpoints, others or all)</li>
<li>New parameter <code>verbose</code> which can be set to <code>TRUE</code> to get very specific messages about which columns and rows were affected</li> <li>New parameter <code>verbose</code> which can be set to <code>TRUE</code> to get very specific messages about which columns and rows were affected</li>
@ -377,11 +424,18 @@ septic_patients %&gt;%
<li>Data set <code>septic_patients</code> now reflects these changes</li> <li>Data set <code>septic_patients</code> now reflects these changes</li>
<li>Added parameter <code>pipe</code> for piperacillin (J01CA12), also to the <code>mdro</code> function</li> <li>Added parameter <code>pipe</code> for piperacillin (J01CA12), also to the <code>mdro</code> function</li>
<li>Small fixes to EUCAST clinical breakpoint rules</li> <li>Small fixes to EUCAST clinical breakpoint rules</li>
</ul>
</li>
<li>Added column <code>kingdom</code> to the microorganisms data set, and function <code>mo_kingdom</code> to look up values</li> <li>Added column <code>kingdom</code> to the microorganisms data set, and function <code>mo_kingdom</code> to look up values</li>
<li>Tremendous speed improvement for <code>as.mo</code> (and subsequently all <code>mo_*</code> functions), as empty values wil be ignored <em>a priori</em> <li>Tremendous speed improvement for <code>as.mo</code> (and subsequently all <code>mo_*</code> functions), as empty values wil be ignored <em>a priori</em>
</li> </li>
<li>Fewer than 3 characters as input for <code>as.mo</code> will return NA</li> <li>Fewer than 3 characters as input for <code>as.mo</code> will return NA</li>
<li>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached <code>r as.mo("E. species") # B_ESCHR mo_fullname("E. spp.") # "Escherichia species" as.mo("S. spp") # B_STPHY mo_fullname("S. species") # "Staphylococcus species"</code> <li>
<p>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. species"</span>) <span class="co"># B_ESCHR</span></a>
<a class="sourceLine" id="cb6-2" data-line-number="2"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"E. spp."</span>) <span class="co"># "Escherichia species"</span></a>
<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. spp"</span>) <span class="co"># B_STPHY</span></a>
<a class="sourceLine" id="cb6-4" data-line-number="4"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. species"</span>) <span class="co"># "Staphylococcus species"</span></a></code></pre></div>
</li> </li>
<li>Added parameter <code>combine_IR</code> (TRUE/FALSE) to functions <code>portion_df</code> and <code>count_df</code>, to indicate that all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)</li> <li>Added parameter <code>combine_IR</code> (TRUE/FALSE) to functions <code>portion_df</code> and <code>count_df</code>, to indicate that all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)</li>
<li>Fix for <code>portion_*(..., as_percent = TRUE)</code> when minimal number of isolates would not be met</li> <li>Fix for <code>portion_*(..., as_percent = TRUE)</code> when minimal number of isolates would not be met</li>
@ -390,18 +444,19 @@ septic_patients %&gt;%
<li>Using <code>portion_*</code> functions now throws a warning when total available isolate is below parameter <code>minimum</code> <li>Using <code>portion_*</code> functions now throws a warning when total available isolate is below parameter <code>minimum</code>
</li> </li>
<li>Functions <code>as.mo</code>, <code>as.rsi</code>, <code>as.mic</code>, <code>as.atc</code> and <code>freq</code> will not set package name as attribute anymore</li> <li>Functions <code>as.mo</code>, <code>as.rsi</code>, <code>as.mic</code>, <code>as.atc</code> and <code>freq</code> will not set package name as attribute anymore</li>
<li>Frequency tables - <code><a href="../reference/freq.html">freq()</a></code>:</li> <li>Frequency tables - <code><a href="../reference/freq.html">freq()</a></code>:
<ul>
<li> <li>
<p>Support for grouping variables, test with:</p> <p>Support for grouping variables, test with:</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">septic_patients %&gt;%<span class="st"> </span> <div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<span class="st"> </span><span class="kw">group_by</span>(hospital_id) %&gt;%<span class="st"> </span> <a class="sourceLine" id="cb7-2" data-line-number="2"><span class="st"> </span><span class="kw">group_by</span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender)</code></pre></div> <a class="sourceLine" id="cb7-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender)</a></code></pre></div>
</li> </li>
<li> <li>
<p>Support for (un)selecting columns:</p> <p>Support for (un)selecting columns:</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">septic_patients %&gt;%<span class="st"> </span> <div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id) %&gt;%<span class="st"> </span> <a class="sourceLine" id="cb8-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<span class="st"> </span><span class="kw">select</span>(-count, -cum_count) <span class="co"># only get item, percent, cum_percent</span></code></pre></div> <a class="sourceLine" id="cb8-3" data-line-number="3"><span class="st"> </span><span class="kw">select</span>(<span class="op">-</span>count, <span class="op">-</span>cum_count) <span class="co"># only get item, percent, cum_percent</span></a></code></pre></div>
</li> </li>
<li>Check for <code><a href="https://www.rdocumentation.org/packages/hms/topics/hms">hms::is.hms</a></code> <li>Check for <code><a href="https://www.rdocumentation.org/packages/hms/topics/hms">hms::is.hms</a></code>
</li> </li>
@ -412,6 +467,8 @@ septic_patients %&gt;%
<li>New parameter <code>na</code>, to choose which character to print for empty values</li> <li>New parameter <code>na</code>, to choose which character to print for empty values</li>
<li>New parameter <code>header</code> to turn the header info off (default when <code>markdown = TRUE</code>)</li> <li>New parameter <code>header</code> to turn the header info off (default when <code>markdown = TRUE</code>)</li>
<li>New parameter <code>title</code> to manually setbthe title of the frequency table</li> <li>New parameter <code>title</code> to manually setbthe title of the frequency table</li>
</ul>
</li>
<li> <li>
<code>first_isolate</code> now tries to find columns to use as input when parameters are left blank</li> <code>first_isolate</code> now tries to find columns to use as input when parameters are left blank</li>
<li>Improvements for MDRO algorithm (function <code>mdro</code>)</li> <li>Improvements for MDRO algorithm (function <code>mdro</code>)</li>
@ -423,7 +480,8 @@ septic_patients %&gt;%
</li> </li>
<li> <li>
<code>ggplot_rsi</code> and <code>scale_y_percent</code> have <code>breaks</code> parameter</li> <code>ggplot_rsi</code> and <code>scale_y_percent</code> have <code>breaks</code> parameter</li>
<li>AI improvements for <code>as.mo</code>:</li> <li>AI improvements for <code>as.mo</code>:
<ul>
<li> <li>
<code>"CRS"</code> -&gt; <em>Stenotrophomonas maltophilia</em> <code>"CRS"</code> -&gt; <em>Stenotrophomonas maltophilia</em>
</li> </li>
@ -436,6 +494,8 @@ septic_patients %&gt;%
<li> <li>
<code>"MSSE"</code> -&gt; <em>Staphylococcus epidermidis</em> <code>"MSSE"</code> -&gt; <em>Staphylococcus epidermidis</em>
</li> </li>
</ul>
</li>
<li>Fix for <code>join</code> functions</li> <li>Fix for <code>join</code> functions</li>
<li>Speed improvement for <code>is.rsi.eligible</code>, now 15-20 times faster</li> <li>Speed improvement for <code>is.rsi.eligible</code>, now 15-20 times faster</li>
<li>In <code>g.test</code>, when <code><a href="https://www.rdocumentation.org/packages/base/topics/sum">sum(x)</a></code> is below 1000 or any of the expected values is below 5, Fisher’s Exact Test will be suggested</li> <li>In <code>g.test</code>, when <code><a href="https://www.rdocumentation.org/packages/base/topics/sum">sum(x)</a></code> is below 1000 or any of the expected values is below 5, Fisher’s Exact Test will be suggested</li>
@ -464,7 +524,8 @@ septic_patients %&gt;%
<a href="#new-2" class="anchor"></a>New</h4> <a href="#new-2" class="anchor"></a>New</h4>
<ul> <ul>
<li>The data set <code>microorganisms</code> now contains <strong>all microbial taxonomic data from ITIS</strong> (kingdoms Bacteria, Fungi and Protozoa), the Integrated Taxonomy Information System, available via <a href="https://itis.gov" class="uri">https://itis.gov</a>. The data set now contains more than 18,000 microorganisms with all known bacteria, fungi and protozoa according ITIS with genus, species, subspecies, family, order, class, phylum and subkingdom. The new data set <code>microorganisms.old</code> contains all previously known taxonomic names from those kingdoms.</li> <li>The data set <code>microorganisms</code> now contains <strong>all microbial taxonomic data from ITIS</strong> (kingdoms Bacteria, Fungi and Protozoa), the Integrated Taxonomy Information System, available via <a href="https://itis.gov" class="uri">https://itis.gov</a>. The data set now contains more than 18,000 microorganisms with all known bacteria, fungi and protozoa according ITIS with genus, species, subspecies, family, order, class, phylum and subkingdom. The new data set <code>microorganisms.old</code> contains all previously known taxonomic names from those kingdoms.</li>
<li>New functions based on the existing function <code>mo_property</code>:</li> <li>New functions based on the existing function <code>mo_property</code>:
<ul>
<li>Taxonomic names: <code>mo_phylum</code>, <code>mo_class</code>, <code>mo_order</code>, <code>mo_family</code>, <code>mo_genus</code>, <code>mo_species</code>, <code>mo_subspecies</code> <li>Taxonomic names: <code>mo_phylum</code>, <code>mo_class</code>, <code>mo_order</code>, <code>mo_family</code>, <code>mo_genus</code>, <code>mo_species</code>, <code>mo_subspecies</code>
</li> </li>
<li>Semantic names: <code>mo_fullname</code>, <code>mo_shortname</code> <li>Semantic names: <code>mo_fullname</code>, <code>mo_shortname</code>
@ -474,22 +535,52 @@ septic_patients %&gt;%
<li>Author and year: <code>mo_ref</code> <li>Author and year: <code>mo_ref</code>
</li> </li>
</ul> </ul>
<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese: <code>r mo_gramstain("E. coli") # [1] "Gram negative" mo_gramstain("E. coli", language = "de") # German # [1] "Gramnegativ" mo_gramstain("E. coli", language = "es") # Spanish # [1] "Gram negativo" mo_fullname("S. group A", language = "pt") # Portuguese # [1] "Streptococcus grupo A"</code></p> <p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
<p>Furthermore, former taxonomic names will give a note about the current taxonomic name: <code>r mo_gramstain("Esc blattae") # Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010) # [1] "Gram negative"</code></p> <div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb9-2" data-line-number="2"><span class="co"># [1] "Gram negative"</span></a>
<a class="sourceLine" id="cb9-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"de"</span>) <span class="co"># German</span></a>
<a class="sourceLine" id="cb9-4" data-line-number="4"><span class="co"># [1] "Gramnegativ"</span></a>
<a class="sourceLine" id="cb9-5" data-line-number="5"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"es"</span>) <span class="co"># Spanish</span></a>
<a class="sourceLine" id="cb9-6" data-line-number="6"><span class="co"># [1] "Gram negativo"</span></a>
<a class="sourceLine" id="cb9-7" data-line-number="7"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. group A"</span>, <span class="dt">language =</span> <span class="st">"pt"</span>) <span class="co"># Portuguese</span></a>
<a class="sourceLine" id="cb9-8" data-line-number="8"><span class="co"># [1] "Streptococcus grupo A"</span></a></code></pre></div>
<p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"Esc blattae"</span>)</a>
<a class="sourceLine" id="cb10-2" data-line-number="2"><span class="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span></a>
<a class="sourceLine" id="cb10-3" data-line-number="3"><span class="co"># [1] "Gram negative"</span></a></code></pre></div>
</li>
<li>Functions <code>count_R</code>, <code>count_IR</code>, <code>count_I</code>, <code>count_SI</code> and <code>count_S</code> to selectively count resistant or susceptible isolates
<ul> <ul>
<li>Functions <code>count_R</code>, <code>count_IR</code>, <code>count_I</code>, <code>count_SI</code> and <code>count_S</code> to selectively count resistant or susceptible isolates</li>
<li>Extra function <code>count_df</code> (which works like <code>portion_df</code>) to get all counts of S, I and R of a data set with antibiotic columns, with support for grouped variables</li> <li>Extra function <code>count_df</code> (which works like <code>portion_df</code>) to get all counts of S, I and R of a data set with antibiotic columns, with support for grouped variables</li>
</ul>
</li>
<li>Function <code>is.rsi.eligible</code> to check for columns that have valid antimicrobial results, but do not have the <code>rsi</code> class yet. Transform the columns of your raw data with: <code>data %&gt;% mutate_if(is.rsi.eligible, as.rsi)</code> <li>Function <code>is.rsi.eligible</code> to check for columns that have valid antimicrobial results, but do not have the <code>rsi</code> class yet. Transform the columns of your raw data with: <code>data %&gt;% mutate_if(is.rsi.eligible, as.rsi)</code>
</li> </li>
<li>Functions <code>as.mo</code> and <code>is.mo</code> as replacements for <code>as.bactid</code> and <code>is.bactid</code> (since the <code>microoganisms</code> data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The <code>as.mo</code> function determines microbial IDs using Artificial Intelligence (AI): <code>r as.mo("E. coli") # [1] B_ESCHR_COL as.mo("MRSA") # [1] B_STPHY_AUR as.mo("S group A") # [1] B_STRPTC_GRA</code> And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items: <code>r thousands_of_E_colis &lt;- rep("E. coli", 25000) microbenchmark::microbenchmark(as.mo(thousands_of_E_colis), unit = "s") # Unit: seconds # min median max neval # 0.01817717 0.01843957 0.03878077 100</code> <li>
<p>Functions <code>as.mo</code> and <code>is.mo</code> as replacements for <code>as.bactid</code> and <code>is.bactid</code> (since the <code>microoganisms</code> data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The <code>as.mo</code> function determines microbial IDs using Artificial Intelligence (AI):</p>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb11-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb11-2" data-line-number="2"><span class="co"># [1] B_ESCHR_COL</span></a>
<a class="sourceLine" id="cb11-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"MRSA"</span>)</a>
<a class="sourceLine" id="cb11-4" data-line-number="4"><span class="co"># [1] B_STPHY_AUR</span></a>
<a class="sourceLine" id="cb11-5" data-line-number="5"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S group A"</span>)</a>
<a class="sourceLine" id="cb11-6" data-line-number="6"><span class="co"># [1] B_STRPTC_GRA</span></a></code></pre></div>
<p>And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">thousands_of_E_colis &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/rep">rep</a></span>(<span class="st">"E. coli"</span>, <span class="dv">25000</span>)</a>
<a class="sourceLine" id="cb12-2" data-line-number="2">microbenchmark<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(thousands_of_E_colis), <span class="dt">unit =</span> <span class="st">"s"</span>)</a>
<a class="sourceLine" id="cb12-3" data-line-number="3"><span class="co"># Unit: seconds</span></a>
<a class="sourceLine" id="cb12-4" data-line-number="4"><span class="co"># min median max neval</span></a>
<a class="sourceLine" id="cb12-5" data-line-number="5"><span class="co"># 0.01817717 0.01843957 0.03878077 100</span></a></code></pre></div>
</li> </li>
<li>Added parameter <code>reference_df</code> for <code>as.mo</code>, so users can supply their own microbial IDs, name or codes as a reference table</li> <li>Added parameter <code>reference_df</code> for <code>as.mo</code>, so users can supply their own microbial IDs, name or codes as a reference table</li>
<li>Renamed all previous references to <code>bactid</code> to <code>mo</code>, like:</li> <li>Renamed all previous references to <code>bactid</code> to <code>mo</code>, like:
<ul>
<li>Column names inputs of <code>EUCAST_rules</code>, <code>first_isolate</code> and <code>key_antibiotics</code> <li>Column names inputs of <code>EUCAST_rules</code>, <code>first_isolate</code> and <code>key_antibiotics</code>
</li> </li>
<li>Column names of datasets <code>microorganisms</code> and <code>septic_patients</code> <li>Column names of datasets <code>microorganisms</code> and <code>septic_patients</code>
</li> </li>
<li>All old syntaxes will still work with this version, but will throw warnings</li> <li>All old syntaxes will still work with this version, but will throw warnings</li>
</ul>
</li>
<li>Function <code>labels_rsi_count</code> to print datalabels on a RSI <code>ggplot2</code> model</li> <li>Function <code>labels_rsi_count</code> to print datalabels on a RSI <code>ggplot2</code> model</li>
<li><p>Functions <code>as.atc</code> and <code>is.atc</code> to transform/look up antibiotic ATC codes as defined by the WHO. The existing function <code>guess_atc</code> is now an alias of <code>as.atc</code>.</p></li> <li><p>Functions <code>as.atc</code> and <code>is.atc</code> to transform/look up antibiotic ATC codes as defined by the WHO. The existing function <code>guess_atc</code> is now an alias of <code>as.atc</code>.</p></li>
<li>Function <code>ab_property</code> and its aliases: <code>ab_name</code>, <code>ab_tradenames</code>, <code>ab_certe</code>, <code>ab_umcg</code> and <code>ab_trivial_nl</code> <li>Function <code>ab_property</code> and its aliases: <code>ab_name</code>, <code>ab_tradenames</code>, <code>ab_certe</code>, <code>ab_umcg</code> and <code>ab_trivial_nl</code>
@ -504,7 +595,14 @@ septic_patients %&gt;%
<a href="#changed-2" class="anchor"></a>Changed</h4> <a href="#changed-2" class="anchor"></a>Changed</h4>
<ul> <ul>
<li>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</li> <li>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</li>
<li>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.: <code>r ab_official("Bactroban") # [1] "Mupirocin" ab_name(c("Bactroban", "Amoxil", "Zithromax", "Floxapen")) # [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin" ab_atc(c("Bactroban", "Amoxil", "Zithromax", "Floxapen")) # [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"</code> <li>
<p>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1"><span class="kw"><a href="../reference/AMR-deprecated.html">ab_official</a></span>(<span class="st">"Bactroban"</span>)</a>
<a class="sourceLine" id="cb13-2" data-line-number="2"><span class="co"># [1] "Mupirocin"</span></a>
<a class="sourceLine" id="cb13-3" data-line-number="3"><span class="kw"><a href="../reference/AMR-deprecated.html">ab_name</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb13-4" data-line-number="4"><span class="co"># [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin"</span></a>
<a class="sourceLine" id="cb13-5" data-line-number="5"><span class="kw"><a href="../reference/AMR-deprecated.html">ab_atc</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb13-6" data-line-number="6"><span class="co"># [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"</span></a></code></pre></div>
</li> </li>
<li>For <code>first_isolate</code>, rows will be ignored when there’s no species available</li> <li>For <code>first_isolate</code>, rows will be ignored when there’s no species available</li>
<li>Function <code>ratio</code> is now deprecated and will be removed in a future release, as it is not really the scope of this package</li> <li>Function <code>ratio</code> is now deprecated and will be removed in a future release, as it is not really the scope of this package</li>
@ -513,9 +611,36 @@ septic_patients %&gt;%
<li>Added <code>prevalence</code> column to the <code>microorganisms</code> data set</li> <li>Added <code>prevalence</code> column to the <code>microorganisms</code> data set</li>
<li>Added parameters <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code> <li>Added parameters <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code>
</li> </li>
<li>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns. ```r septic_patients %&gt;% select(amox, cipr) %&gt;% count_IR() # which is the same as: septic_patients %&gt;% count_IR(amox, cipr)</li> <li>
<p>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns.</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">select</span>(amox, cipr) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>()</a>
<a class="sourceLine" id="cb14-2" data-line-number="2"><span class="co"># which is the same as:</span></a>
<a class="sourceLine" id="cb14-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>(amox, cipr)</a>
<a class="sourceLine" id="cb14-4" data-line-number="4"></a>
<a class="sourceLine" id="cb14-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl)</a>
<a class="sourceLine" id="cb14-6" data-line-number="6">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl, gent)</a>
<a class="sourceLine" id="cb14-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl, gent, pita)</a></code></pre></div>
</li>
<li>Edited <code>ggplot_rsi</code> and <code>geom_rsi</code> so they can cope with <code>count_df</code>. The new <code>fun</code> parameter has value <code>portion_df</code> at default, but can be set to <code>count_df</code>.</li>
<li>Fix for <code>ggplot_rsi</code> when the <code>ggplot2</code> package was not loaded</li>
<li>Added datalabels function <code>labels_rsi_count</code> to <code>ggplot_rsi</code>
</li>
<li>Added possibility to set any parameter to <code>geom_rsi</code> (and <code>ggplot_rsi</code>) so you can set your own preferences</li>
<li>Fix for joins, where predefined suffices would not be honoured</li>
<li>Added parameter <code>quote</code> to the <code>freq</code> function</li>
<li>Added generic function <code>diff</code> for frequency tables</li>
<li>Added longest en shortest character length in the frequency table (<code>freq</code>) header of class <code>character</code>
</li>
<li>
<p>Support for types (classes) list and matrix for <code>freq</code></p>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" data-line-number="1">my_matrix =<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/with">with</a></span>(septic_patients, <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/matrix">matrix</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(age, gender), <span class="dt">ncol =</span> <span class="dv">2</span>))</a>
<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="kw"><a href="../reference/freq.html">freq</a></span>(my_matrix)</a></code></pre></div>
<p>For lists, subsetting is possible:</p>
<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb16-1" data-line-number="1">my_list =<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/list">list</a></span>(<span class="dt">age =</span> septic_patients<span class="op">$</span>age, <span class="dt">gender =</span> septic_patients<span class="op">$</span>gender)</a>
<a class="sourceLine" id="cb16-2" data-line-number="2">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(age)</a>
<a class="sourceLine" id="cb16-3" data-line-number="3">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender)</a></code></pre></div>
</li>
</ul> </ul>
<p>septic_patients %&gt;% portion_S(amcl) septic_patients %&gt;% portion_S(amcl, gent) septic_patients %&gt;% portion_S(amcl, gent, pita) <code>* Edited `ggplot_rsi` and `geom_rsi` so they can cope with `count_df`. The new `fun` parameter has value `portion_df` at default, but can be set to `count_df`. * Fix for `ggplot_rsi` when the `ggplot2` package was not loaded * Added datalabels function `labels_rsi_count` to `ggplot_rsi` * Added possibility to set any parameter to `geom_rsi` (and `ggplot_rsi`) so you can set your own preferences * Fix for joins, where predefined suffices would not be honoured * Added parameter `quote` to the `freq` function * Added generic function `diff` for frequency tables * Added longest en shortest character length in the frequency table (`freq`) header of class `character` * Support for types (classes) list and matrix for `freq`</code>r my_matrix = with(septic_patients, matrix(c(age, gender), ncol = 2)) freq(my_matrix) <code>For lists, subsetting is possible:</code>r my_list = list(age = septic_patients$age, gender = septic_patients$gender) my_list %&gt;% freq(age) my_list %&gt;% freq(gender) ```</p>
</div> </div>
<div id="other-2" class="section level4"> <div id="other-2" class="section level4">
<h4 class="hasAnchor"> <h4 class="hasAnchor">
@ -534,15 +659,21 @@ septic_patients %&gt;%
<a href="#new-3" class="anchor"></a>New</h4> <a href="#new-3" class="anchor"></a>New</h4>
<ul> <ul>
<li> <li>
<strong>BREAKING</strong>: <code>rsi_df</code> was removed in favour of new functions <code>portion_R</code>, <code>portion_IR</code>, <code>portion_I</code>, <code>portion_SI</code> and <code>portion_S</code> to selectively calculate resistance or susceptibility. These functions are 20 to 30 times faster than the old <code>rsi</code> function. The old function still works, but is deprecated.</li> <strong>BREAKING</strong>: <code>rsi_df</code> was removed in favour of new functions <code>portion_R</code>, <code>portion_IR</code>, <code>portion_I</code>, <code>portion_SI</code> and <code>portion_S</code> to selectively calculate resistance or susceptibility. These functions are 20 to 30 times faster than the old <code>rsi</code> function. The old function still works, but is deprecated.
<ul>
<li>New function <code>portion_df</code> to get all portions of S, I and R of a data set with antibiotic columns, with support for grouped variables</li> <li>New function <code>portion_df</code> to get all portions of S, I and R of a data set with antibiotic columns, with support for grouped variables</li>
</ul>
</li>
<li> <li>
<strong>BREAKING</strong>: the methodology for determining first weighted isolates was changed. The antibiotics that are compared between isolates (call <em>key antibiotics</em>) to include more first isolates (afterwards called first <em>weighted</em> isolates) are now as follows:</li> <strong>BREAKING</strong>: the methodology for determining first weighted isolates was changed. The antibiotics that are compared between isolates (call <em>key antibiotics</em>) to include more first isolates (afterwards called first <em>weighted</em> isolates) are now as follows:
<ul>
<li>Universal: amoxicillin, amoxicillin/clavlanic acid, cefuroxime, piperacillin/tazobactam, ciprofloxacin, trimethoprim/sulfamethoxazole</li> <li>Universal: amoxicillin, amoxicillin/clavlanic acid, cefuroxime, piperacillin/tazobactam, ciprofloxacin, trimethoprim/sulfamethoxazole</li>
<li>Gram-positive: vancomycin, teicoplanin, tetracycline, erythromycin, oxacillin, rifampicin</li> <li>Gram-positive: vancomycin, teicoplanin, tetracycline, erythromycin, oxacillin, rifampicin</li>
<li>Gram-negative: gentamicin, tobramycin, colistin, cefotaxime, ceftazidime, meropenem</li> <li>Gram-negative: gentamicin, tobramycin, colistin, cefotaxime, ceftazidime, meropenem</li>
<li>Support for <code>ggplot2</code> </ul>
</li> </li>
<li>Support for <code>ggplot2</code>
<ul>
<li>New functions <code>geom_rsi</code>, <code>facet_rsi</code>, <code>scale_y_percent</code>, <code>scale_rsi_colours</code> and <code>theme_rsi</code> <li>New functions <code>geom_rsi</code>, <code>facet_rsi</code>, <code>scale_y_percent</code>, <code>scale_rsi_colours</code> and <code>theme_rsi</code>
</li> </li>
<li>New wrapper function <code>ggplot_rsi</code> to apply all above functions on a data set: <li>New wrapper function <code>ggplot_rsi</code> to apply all above functions on a data set:
@ -553,22 +684,32 @@ septic_patients %&gt;%
</li> </li>
</ul> </ul>
</li> </li>
<li>Determining bacterial ID:</li> </ul>
</li>
<li>Determining bacterial ID:
<ul>
<li>New functions <code>as.bactid</code> and <code>is.bactid</code> to transform/ look up microbial ID’s.</li> <li>New functions <code>as.bactid</code> and <code>is.bactid</code> to transform/ look up microbial ID’s.</li>
<li>The existing function <code>guess_bactid</code> is now an alias of <code>as.bactid</code> <li>The existing function <code>guess_bactid</code> is now an alias of <code>as.bactid</code>
</li> </li>
<li>New Becker classification for <em>Staphylococcus</em> to categorise them into Coagulase Negative <em>Staphylococci</em> (CoNS) and Coagulase Positve <em>Staphylococci</em> (CoPS)</li> <li>New Becker classification for <em>Staphylococcus</em> to categorise them into Coagulase Negative <em>Staphylococci</em> (CoNS) and Coagulase Positve <em>Staphylococci</em> (CoPS)</li>
<li>New Lancefield classification for <em>Streptococcus</em> to categorise them into Lancefield groups</li> <li>New Lancefield classification for <em>Streptococcus</em> to categorise them into Lancefield groups</li>
</ul>
</li>
<li>For convience, new descriptive statistical functions <code>kurtosis</code> and <code>skewness</code> that are lacking in base R - they are generic functions and have support for vectors, data.frames and matrices</li> <li>For convience, new descriptive statistical functions <code>kurtosis</code> and <code>skewness</code> that are lacking in base R - they are generic functions and have support for vectors, data.frames and matrices</li>
<li>Function <code>g.test</code> to perform the Χ<sup>2</sup> distributed <a href="https://en.wikipedia.org/wiki/G-test"><em>G</em>-test</a>, which use is the same as <code>chisq.test</code> <li>Function <code>g.test</code> to perform the Χ<sup>2</sup> distributed <a href="https://en.wikipedia.org/wiki/G-test"><em>G</em>-test</a>, which use is the same as <code>chisq.test</code>
</li> </li>
<li><del>Function <code>ratio</code> to transform a vector of values to a preset ratio</del></li> <li>
<del>Function <code>ratio</code> to transform a vector of values to a preset ratio</del>
<ul>
<li><del>For example: <code><a href="../reference/AMR-deprecated.html">ratio(c(10, 500, 10), ratio = "1:2:1")</a></code> would return <code>130, 260, 130</code></del></li> <li><del>For example: <code><a href="../reference/AMR-deprecated.html">ratio(c(10, 500, 10), ratio = "1:2:1")</a></code> would return <code>130, 260, 130</code></del></li>
</ul>
</li>
<li>Support for Addins menu in RStudio to quickly insert <code>%in%</code> or <code>%like%</code> (and give them keyboard shortcuts), or to view the datasets that come with this package</li> <li>Support for Addins menu in RStudio to quickly insert <code>%in%</code> or <code>%like%</code> (and give them keyboard shortcuts), or to view the datasets that come with this package</li>
<li>Function <code>p.symbol</code> to transform p values to their related symbols: <code>0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code> <li>Function <code>p.symbol</code> to transform p values to their related symbols: <code>0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code>
</li> </li>
<li>Functions <code>clipboard_import</code> and <code>clipboard_export</code> as helper functions to quickly copy and paste from/to software like Excel and SPSS. These functions use the <code>clipr</code> package, but are a little altered to also support headless Linux servers (so you can use it in RStudio Server)</li> <li>Functions <code>clipboard_import</code> and <code>clipboard_export</code> as helper functions to quickly copy and paste from/to software like Excel and SPSS. These functions use the <code>clipr</code> package, but are a little altered to also support headless Linux servers (so you can use it in RStudio Server)</li>
<li>New for frequency tables (function <code>freq</code>):</li> <li>New for frequency tables (function <code>freq</code>):
<ul>
<li>A vignette to explain its usage</li> <li>A vignette to explain its usage</li>
<li>Support for <code>rsi</code> (antimicrobial resistance) to use as input</li> <li>Support for <code>rsi</code> (antimicrobial resistance) to use as input</li>
<li>Support for <code>table</code> to use as input: <code><a href="../reference/freq.html">freq(table(x, y))</a></code> <li>Support for <code>table</code> to use as input: <code><a href="../reference/freq.html">freq(table(x, y))</a></code>
@ -583,6 +724,8 @@ septic_patients %&gt;%
<li>Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR)</li> <li>Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR)</li>
<li>Possibility to globally set the default for the amount of items to print, with <code><a href="https://www.rdocumentation.org/packages/base/topics/options">options(max.print.freq = n)</a></code> where <em>n</em> is your preset value</li> <li>Possibility to globally set the default for the amount of items to print, with <code><a href="https://www.rdocumentation.org/packages/base/topics/options">options(max.print.freq = n)</a></code> where <em>n</em> is your preset value</li>
</ul> </ul>
</li>
</ul>
</div> </div>
<div id="changed-3" class="section level4"> <div id="changed-3" class="section level4">
<h4 class="hasAnchor"> <h4 class="hasAnchor">
@ -604,21 +747,27 @@ septic_patients %&gt;%
</li> </li>
<li>Small improvements to the <code>microorganisms</code> dataset (especially for <em>Salmonella</em>) and the column <code>bactid</code> now has the new class <code>"bactid"</code> <li>Small improvements to the <code>microorganisms</code> dataset (especially for <em>Salmonella</em>) and the column <code>bactid</code> now has the new class <code>"bactid"</code>
</li> </li>
<li>Combined MIC/RSI values will now be coerced by the <code>rsi</code> and <code>mic</code> functions:</li> <li>Combined MIC/RSI values will now be coerced by the <code>rsi</code> and <code>mic</code> functions:
<ul>
<li> <li>
<code><a href="../reference/as.rsi.html">as.rsi("&lt;=0.002; S")</a></code> will return <code>S</code> <code><a href="../reference/as.rsi.html">as.rsi("&lt;=0.002; S")</a></code> will return <code>S</code>
</li> </li>
<li> <li>
<code><a href="../reference/as.mic.html">as.mic("&lt;=0.002; S")</a></code> will return <code>&lt;=0.002</code> <code><a href="../reference/as.mic.html">as.mic("&lt;=0.002; S")</a></code> will return <code>&lt;=0.002</code>
</li> </li>
</ul>
</li>
<li>Now possible to coerce MIC values with a space between operator and value, i.e. <code><a href="../reference/as.mic.html">as.mic("&lt;= 0.002")</a></code> now works</li> <li>Now possible to coerce MIC values with a space between operator and value, i.e. <code><a href="../reference/as.mic.html">as.mic("&lt;= 0.002")</a></code> now works</li>
<li>Classes <code>rsi</code> and <code>mic</code> do not add the attribute <code>package.version</code> anymore</li> <li>Classes <code>rsi</code> and <code>mic</code> do not add the attribute <code>package.version</code> anymore</li>
<li>Added <code>"groups"</code> option for <code><a href="../reference/atc_property.html">atc_property(..., property)</a></code>. It will return a vector of the ATC hierarchy as defined by the <a href="https://www.whocc.no/atc/structure_and_principles/">WHO</a>. The new function <code>atc_groups</code> is a convenient wrapper around this.</li> <li>Added <code>"groups"</code> option for <code><a href="../reference/atc_property.html">atc_property(..., property)</a></code>. It will return a vector of the ATC hierarchy as defined by the <a href="https://www.whocc.no/atc/structure_and_principles/">WHO</a>. The new function <code>atc_groups</code> is a convenient wrapper around this.</li>
<li>Build-in host check for <code>atc_property</code> as it requires the host set by <code>url</code> to be responsive</li> <li>Build-in host check for <code>atc_property</code> as it requires the host set by <code>url</code> to be responsive</li>
<li>Improved <code>first_isolate</code> algorithm to exclude isolates where bacteria ID or genus is unavailable</li> <li>Improved <code>first_isolate</code> algorithm to exclude isolates where bacteria ID or genus is unavailable</li>
<li>Fix for warning <em>hybrid evaluation forced for row_number</em> (<a href="https://github.com/tidyverse/dplyr/commit/924b62"><code>924b62</code></a>) from the <code>dplyr</code> package v0.7.5 and above</li> <li>Fix for warning <em>hybrid evaluation forced for row_number</em> (<a href="https://github.com/tidyverse/dplyr/commit/924b62"><code>924b62</code></a>) from the <code>dplyr</code> package v0.7.5 and above</li>
<li>Support for empty values and for 1 or 2 columns as input for <code>guess_bactid</code> (now called <code>as.bactid</code>)</li> <li>Support for empty values and for 1 or 2 columns as input for <code>guess_bactid</code> (now called <code>as.bactid</code>)
<ul>
<li>So <code>yourdata %&gt;% select(genus, species) %&gt;% as.bactid()</code> now also works</li> <li>So <code>yourdata %&gt;% select(genus, species) %&gt;% as.bactid()</code> now also works</li>
</ul>
</li>
<li>Other small fixes</li> <li>Other small fixes</li>
</ul> </ul>
</div> </div>
@ -626,11 +775,14 @@ septic_patients %&gt;%
<h4 class="hasAnchor"> <h4 class="hasAnchor">
<a href="#other-3" class="anchor"></a>Other</h4> <a href="#other-3" class="anchor"></a>Other</h4>
<ul> <ul>
<li>Added integration tests (check if everything works as expected) for all releases of R 3.1 and higher</li> <li>Added integration tests (check if everything works as expected) for all releases of R 3.1 and higher
<ul>
<li>Linux and macOS: <a href="https://travis-ci.org/msberends/AMR" class="uri">https://travis-ci.org/msberends/AMR</a> <li>Linux and macOS: <a href="https://travis-ci.org/msberends/AMR" class="uri">https://travis-ci.org/msberends/AMR</a>
</li> </li>
<li>Windows: <a href="https://ci.appveyor.com/project/msberends/amr" class="uri">https://ci.appveyor.com/project/msberends/amr</a> <li>Windows: <a href="https://ci.appveyor.com/project/msberends/amr" class="uri">https://ci.appveyor.com/project/msberends/amr</a>
</li> </li>
</ul>
</li>
<li>Added thesis advisors to DESCRIPTION file</li> <li>Added thesis advisors to DESCRIPTION file</li>
</ul> </ul>
</div> </div>
@ -649,10 +801,13 @@ septic_patients %&gt;%
<li>Function <code>guess_bactid</code> to <strong>determine the ID</strong> of a microorganism based on genus/species or known abbreviations like MRSA</li> <li>Function <code>guess_bactid</code> to <strong>determine the ID</strong> of a microorganism based on genus/species or known abbreviations like MRSA</li>
<li>Function <code>guess_atc</code> to <strong>determine the ATC</strong> of an antibiotic based on name, trade name, or known abbreviations</li> <li>Function <code>guess_atc</code> to <strong>determine the ATC</strong> of an antibiotic based on name, trade name, or known abbreviations</li>
<li>Function <code>freq</code> to create <strong>frequency tables</strong>, with additional info in a header</li> <li>Function <code>freq</code> to create <strong>frequency tables</strong>, with additional info in a header</li>
<li>Function <code>MDRO</code> to <strong>determine Multi Drug Resistant Organisms (MDRO)</strong> with support for country-specific guidelines.</li> <li>Function <code>MDRO</code> to <strong>determine Multi Drug Resistant Organisms (MDRO)</strong> with support for country-specific guidelines.
<ul>
<li> <li>
<a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance">Exceptional resistances defined by EUCAST</a> are also supported instead of countries alone</li> <a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance">Exceptional resistances defined by EUCAST</a> are also supported instead of countries alone</li>
<li>Functions <code>BRMO</code> and <code>MRGN</code> are wrappers for Dutch and German guidelines, respectively</li> <li>Functions <code>BRMO</code> and <code>MRGN</code> are wrappers for Dutch and German guidelines, respectively</li>
</ul>
</li>
<li>New algorithm to determine weighted isolates, can now be <code>"points"</code> or <code>"keyantibiotics"</code>, see <code><a href="../reference/first_isolate.html">?first_isolate</a></code> <li>New algorithm to determine weighted isolates, can now be <code>"points"</code> or <code>"keyantibiotics"</code>, see <code><a href="../reference/first_isolate.html">?first_isolate</a></code>
</li> </li>
<li>New print format for <code>tibble</code>s and <code>data.table</code>s</li> <li>New print format for <code>tibble</code>s and <code>data.table</code>s</li>

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@ -1,4 +1,4 @@
pandoc: 1.17.2 pandoc: 2.3.1
pkgdown: 1.3.0 pkgdown: 1.3.0
pkgdown_sha: ~ pkgdown_sha: ~
articles: articles:

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@ -237,7 +237,13 @@
<pre class="usage"><span class='fu'>as.mo</span>(<span class='no'>x</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>allow_uncertain</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <pre class="usage"><span class='fu'>as.mo</span>(<span class='no'>x</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>allow_uncertain</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>reference_df</span> <span class='kw'>=</span> <span class='fu'><a href='mo_source.html'>get_mo_source</a></span>()) <span class='kw'>reference_df</span> <span class='kw'>=</span> <span class='fu'><a href='mo_source.html'>get_mo_source</a></span>())
<span class='fu'>is.mo</span>(<span class='no'>x</span>)</pre> <span class='fu'>is.mo</span>(<span class='no'>x</span>)
<span class='fu'>mo_failures</span>()
<span class='fu'>mo_uncertainties</span>()
<span class='fu'>mo_renamed</span>()</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments"> <table class="ref-arguments">
@ -287,7 +293,7 @@
</pre> </pre>
<p>Use the <code><a href='mo_property.html'>mo_property</a></code> functions to get properties based on the returned code, see Examples.</p> <p>Use the <code><a href='mo_property.html'>mo_property</a></code> functions to get properties based on the returned code, see Examples.</p>
<p>This function uses Artificial Intelligence (AI) to help getting fast and logical results. It tries to find matches in this order:</p><ul> <p>This function uses Artificial Intelligence (AI) to help getting fast and logical results. It tries to find matches in this order:</p><ul>
<li><p>Taxonomic kingdom: it first searches in bacteria, then fungi, then protozoa</p></li> <li><p>Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa</p></li>
<li><p>Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones</p></li> <li><p>Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones</p></li>
<li><p>Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations</p></li> <li><p>Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations</p></li>
<li><p>Breakdown of input values: from here it starts to breakdown input values to find possible matches</p></li> <li><p>Breakdown of input values: from here it starts to breakdown input values to find possible matches</p></li>
@ -298,11 +304,23 @@
<li><p>Something like <code>"p aer"</code> will return the ID of <em>Pseudomonas aeruginosa</em> and not <em>Pasteurella aerogenes</em></p></li> <li><p>Something like <code>"p aer"</code> will return the ID of <em>Pseudomonas aeruginosa</em> and not <em>Pasteurella aerogenes</em></p></li>
<li><p>Something like <code>"stau"</code> or <code>"S aur"</code> will return the ID of <em>Staphylococcus aureus</em> and not <em>Staphylococcus auricularis</em></p></li> <li><p>Something like <code>"stau"</code> or <code>"S aur"</code> will return the ID of <em>Staphylococcus aureus</em> and not <em>Staphylococcus auricularis</em></p></li>
</ul><p>This means that looking up human pathogenic microorganisms takes less time than looking up human <strong>non</strong>-pathogenic microorganisms.</p> </ul><p>This means that looking up human pathogenic microorganisms takes less time than looking up human <strong>non</strong>-pathogenic microorganisms.</p>
<p>When using <code>allow_uncertain = TRUE</code> (which is the default setting), it will use additional rules if all previous AI rules failed to get valid results. Examples:</p><ul> <p><strong>UNCERTAIN RESULTS</strong> <br />
When using <code>allow_uncertain = TRUE</code> (which is the default setting), it will use additional rules if all previous AI rules failed to get valid results. These are:</p><ul>
<li><p>It tries to look for previously accepted (but now invalid) taxonomic names</p></li>
<li><p>It strips off values between brackets and the brackets itself, and re-evaluates the input with all previous rules</p></li>
<li><p>It strips off words from the end one by one and re-evaluates the input with all previous rules</p></li>
<li><p>It strips off words from the start one by one and re-evaluates the input with all previous rules</p></li>
<li><p>It tries to look for some manual changes which are not yet published to the ITIS database (like <em>Propionibacterium</em> not yet being <em>Cutibacterium</em>)</p></li>
</ul>
<p>Examples:</p><ul>
<li><p><code>"Streptococcus group B (known as S. agalactiae)"</code>. The text between brackets will be removed and a warning will be thrown that the result <em>Streptococcus group B</em> (<code>B_STRPTC_GRB</code>) needs review.</p></li> <li><p><code>"Streptococcus group B (known as S. agalactiae)"</code>. The text between brackets will be removed and a warning will be thrown that the result <em>Streptococcus group B</em> (<code>B_STRPTC_GRB</code>) needs review.</p></li>
<li><p><code>"S. aureus - please mind: MRSA"</code>. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result <em>Staphylococcus aureus</em> (<code>B_STPHY_AUR</code>) needs review.</p></li> <li><p><code>"S. aureus - please mind: MRSA"</code>. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result <em>Staphylococcus aureus</em> (<code>B_STPHY_AUR</code>) needs review.</p></li>
<li><p><code>"D. spartina"</code>. This is the abbreviation of an old taxonomic name: <em>Didymosphaeria spartinae</em> (the last "e" was missing from the input). This fungus was renamed to <em>Leptosphaeria obiones</em>, so a warning will be thrown that this result (<code>F_LPTSP_OBI</code>) needs review.</p></li> <li><p><code>"D. spartina"</code>. This is the abbreviation of an old taxonomic name: <em>Didymosphaeria spartinae</em> (the last "e" was missing from the input). This fungus was renamed to <em>Leptosphaeria obiones</em>, so a warning will be thrown that this result (<code>F_LPTSP_OBI</code>) needs review.</p></li>
<li><p><code>"Fluoroquinolone-resistant Neisseria gonorrhoeae"</code>. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result <em>Neisseria gonorrhoeae</em> (<code>B_NESSR_GON</code>) needs review.</p></li>
</ul> </ul>
<p>Use <code>mo_failures()</code> to get a vector with all values that could not be coerced to a valid value.</p>
<p>Use <code>mo_uncertainties()</code> to get a vector with all values that were coerced to a valid value, but with uncertainty.</p>
<p>Use <code>mo_renamed()</code> to get a vector with all values that could be coerced based on an old, previously accepted taxonomic name.</p>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2> <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>

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@ -80,7 +80,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9015</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span>
</span> </span>
</div> </div>

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@ -294,7 +294,7 @@
</tr> </tr>
<tr> <tr>
<th>verbose</th> <th>verbose</th>
<td><p>a logical to indicate whether extensive info should be returned as a <code>data.frame</code> with info about which rows and columns are effected</p></td> <td><p>a logical to indicate whether extensive info should be returned as a <code>data.frame</code> with info about which rows and columns are effected. It runs all EUCAST rules, but will not be applied to an output - only an informative <code>data.frame</code> with changes will be returned as output.</p></td>
</tr> </tr>
<tr> <tr>
<th>amcl, amik, amox, ampi, azit, azlo, aztr, cefa, cfep, cfot, cfox, cfra, cfta, cftr, cfur, chlo, cipr, clar, clin, clox, coli, czol, dapt, doxy, erta, eryt, fosf, fusi, gent, imip, kana, levo, linc, line, mero, mezl, mino, moxi, nali, neom, neti, nitr, norf, novo, oflo, oxac, peni, pipe, pita, poly, pris, qida, rifa, roxi, siso, teic, tetr, tica, tige, tobr, trim, trsu, vanc</th> <th>amcl, amik, amox, ampi, azit, azlo, aztr, cefa, cfep, cfot, cfox, cfra, cfta, cftr, cfur, chlo, cipr, clar, clin, clox, coli, czol, dapt, doxy, erta, eryt, fosf, fusi, gent, imip, kana, levo, linc, line, mero, mezl, mino, moxi, nali, neom, neti, nitr, norf, novo, oflo, oxac, peni, pipe, pita, poly, pris, qida, rifa, roxi, siso, teic, tetr, tica, tige, tobr, trim, trsu, vanc</th>
@ -320,7 +320,7 @@
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>The input of <code>tbl</code>, possibly with edited values of antibiotics. Or, if <code>verbose = TRUE</code>, a <code>data.frame</code> with verbose info.</p> <p>The input of <code>tbl</code>, possibly with edited values of antibiotics. Or, if <code>verbose = TRUE</code>, a <code>data.frame</code> with all original and new values of the affected bug-drug combinations.</p>
<h2 class="hasAnchor" id="antibiotics"><a class="anchor" href="#antibiotics"></a>Antibiotics</h2> <h2 class="hasAnchor" id="antibiotics"><a class="anchor" href="#antibiotics"></a>Antibiotics</h2>
@ -423,7 +423,9 @@ On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitla
<span class='co'># 4 Klebsiella pneumoniae - - - - - S S</span> <span class='co'># 4 Klebsiella pneumoniae - - - - - S S</span>
<span class='co'># 5 Pseudomonas aeruginosa - - - - - S S</span> <span class='co'># 5 Pseudomonas aeruginosa - - - - - S S</span>
<span class='no'>b</span> <span class='kw'>&lt;-</span> <span class='fu'>eucast_rules</span>(<span class='no'>a</span>, <span class='st'>"mo"</span>) <span class='co'># 18 results are forced as R or S</span>
<span class='co'># apply EUCAST rules: 18 results are forced as R or S</span>
<span class='no'>b</span> <span class='kw'>&lt;-</span> <span class='fu'>eucast_rules</span>(<span class='no'>a</span>)
<span class='no'>b</span> <span class='no'>b</span>
<span class='co'># mo vanc amox coli cfta cfur peni cfox</span> <span class='co'># mo vanc amox coli cfta cfur peni cfox</span>
@ -432,6 +434,11 @@ On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitla
<span class='co'># 3 Escherichia coli R - - - - R S</span> <span class='co'># 3 Escherichia coli R - - - - R S</span>
<span class='co'># 4 Klebsiella pneumoniae R R - - - R S</span> <span class='co'># 4 Klebsiella pneumoniae R R - - - R S</span>
<span class='co'># 5 Pseudomonas aeruginosa R R - - R R R</span> <span class='co'># 5 Pseudomonas aeruginosa R R - - R R R</span>
<span class='co'># do not apply EUCAST rules, but rather get a a data.frame</span>
<span class='co'># with 18 rows, containing all details about the transformations:</span>
<span class='no'>c</span> <span class='kw'>&lt;-</span> <span class='fu'>eucast_rules</span>(<span class='no'>a</span>, <span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='co'># }</span></pre> <span class='co'># }</span></pre>
</div> </div>
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar"> <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">

16
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@ -368,7 +368,7 @@ top_freq can be used to get the top/bottom n items of a frequency table, with co
<li><p>Median, using <code><a href='https://www.rdocumentation.org/packages/stats/topics/median'>median</a></code>, with percentage since oldest</p></li> <li><p>Median, using <code><a href='https://www.rdocumentation.org/packages/stats/topics/median'>median</a></code>, with percentage since oldest</p></li>
</ul> </ul>
<p>In factors, all factor levels that are not existing in the input data will be dropped.</p> <p>In factors, all factor levels that are not existing in the input data will be dropped.</p>
<p>The function <code>top_freq</code> uses <code><a href='https://www.rdocumentation.org/packages/dplyr/topics/top_n'>top_n</a></code> internally and will include more than <code>n</code> rows if there are ties.</p> <p>The function <code>top_freq</code> uses <code><a href='https://dplyr.tidyverse.org/reference/top_n.html'>top_n</a></code> internally and will include more than <code>n</code> rows if there are ties.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2> <h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
@ -392,8 +392,8 @@ On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitla
<span class='co'># you could also use `select` or `pull` to get your variables</span> <span class='co'># you could also use `select` or `pull` to get your variables</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/dplyr/topics/filter'>filter</a></span>(<span class='no'>hospital_id</span> <span class='kw'>==</span> <span class='st'>"A"</span>) <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>hospital_id</span> <span class='kw'>==</span> <span class='st'>"A"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/dplyr/topics/select'>select</a></span>(<span class='no'>mo</span>) <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mo</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>() <span class='fu'>freq</span>()
@ -409,20 +409,20 @@ On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitla
<span class='co'># group a variable and analyse another</span> <span class='co'># group a variable and analyse another</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/dplyr/topics/group_by'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>gender</span>) <span class='fu'>freq</span>(<span class='no'>gender</span>)
<span class='co'># get top 10 bugs of hospital A as a vector</span> <span class='co'># get top 10 bugs of hospital A as a vector</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/dplyr/topics/filter'>filter</a></span>(<span class='no'>hospital_id</span> <span class='kw'>==</span> <span class='st'>"A"</span>) <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>hospital_id</span> <span class='kw'>==</span> <span class='st'>"A"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>mo</span>) <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>(<span class='no'>mo</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>top_freq</span>(<span class='fl'>10</span>) <span class='fu'>top_freq</span>(<span class='fl'>10</span>)
<span class='co'># save frequency table to an object</span> <span class='co'># save frequency table to an object</span>
<span class='no'>years</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='no'>years</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/dplyr/topics/mutate'>mutate</a></span>(<span class='kw'>year</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/format'>format</a></span>(<span class='no'>date</span>, <span class='st'>"%Y"</span>)) <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>year</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/format'>format</a></span>(<span class='no'>date</span>, <span class='st'>"%Y"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>year</span>) <span class='fu'>freq</span>(<span class='no'>year</span>)
@ -473,11 +473,11 @@ On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitla
<span class='co'># only get selected columns</span> <span class='co'># only get selected columns</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/dplyr/topics/select'>select</a></span>(<span class='no'>item</span>, <span class='no'>percent</span>) <span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>item</span>, <span class='no'>percent</span>)
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/dplyr/topics/select'>select</a></span>(-<span class='no'>count</span>, -<span class='no'>cum_count</span>) <span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>count</span>, -<span class='no'>cum_count</span>)
<span class='co'># check differences between frequency tables</span> <span class='co'># check differences between frequency tables</span>

22
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@ -78,7 +78,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9017</span>
</span> </span>
</div> </div>
@ -280,7 +280,7 @@
</tr><tr> </tr><tr>
<td> <td>
<p><code><a href="as.mo.html">as.mo()</a></code> <code><a href="as.mo.html">is.mo()</a></code> </p> <p><code><a href="as.mo.html">as.mo()</a></code> <code><a href="as.mo.html">is.mo()</a></code> <code><a href="as.mo.html">mo_failures()</a></code> <code><a href="as.mo.html">mo_uncertainties()</a></code> <code><a href="as.mo.html">mo_renamed()</a></code> </p>
</td> </td>
<td><p>Transform to microorganism ID</p></td> <td><p>Transform to microorganism ID</p></td>
</tr><tr> </tr><tr>
@ -397,6 +397,12 @@
</tr> </tr>
<tr> <tr>
<td>
<p><code><a href="availability.html">availability()</a></code> </p>
</td>
<td><p>Check availability of columns</p></td>
</tr><tr>
<td> <td>
<p><code><a href="count.html">count_R()</a></code> <code><a href="count.html">count_IR()</a></code> <code><a href="count.html">count_I()</a></code> <code><a href="count.html">count_SI()</a></code> <code><a href="count.html">count_S()</a></code> <code><a href="count.html">count_all()</a></code> <code><a href="count.html">n_rsi()</a></code> <code><a href="count.html">count_df()</a></code> </p> <p><code><a href="count.html">count_R()</a></code> <code><a href="count.html">count_IR()</a></code> <code><a href="count.html">count_I()</a></code> <code><a href="count.html">count_SI()</a></code> <code><a href="count.html">count_S()</a></code> <code><a href="count.html">count_all()</a></code> <code><a href="count.html">n_rsi()</a></code> <code><a href="count.html">count_df()</a></code> </p>
</td> </td>
@ -521,18 +527,6 @@
<td><p>Pattern Matching</p></td> <td><p>Pattern Matching</p></td>
</tr><tr> </tr><tr>
<td>
<p><code><a href="mo_failures.html">mo_failures()</a></code> </p>
</td>
<td><p>Vector of failed coercion attempts</p></td>
</tr><tr>
<td>
<p><code><a href="mo_renamed.html">mo_renamed()</a></code> </p>
</td>
<td><p>Vector of taxonomic renamed items</p></td>
</tr><tr>
<td> <td>
<p><code><a href="AMR-deprecated.html">ratio()</a></code> <code><a href="AMR-deprecated.html">guess_mo()</a></code> <code><a href="AMR-deprecated.html">guess_atc()</a></code> <code><a href="AMR-deprecated.html">ab_property()</a></code> <code><a href="AMR-deprecated.html">ab_atc()</a></code> <code><a href="AMR-deprecated.html">ab_official()</a></code> <code><a href="AMR-deprecated.html">ab_name()</a></code> <code><a href="AMR-deprecated.html">ab_trivial_nl()</a></code> <code><a href="AMR-deprecated.html">ab_certe()</a></code> <code><a href="AMR-deprecated.html">ab_umcg()</a></code> <code><a href="AMR-deprecated.html">ab_tradenames()</a></code> <code><a href="AMR-deprecated.html">atc_ddd()</a></code> <code><a href="AMR-deprecated.html">atc_groups()</a></code> </p> <p><code><a href="AMR-deprecated.html">ratio()</a></code> <code><a href="AMR-deprecated.html">guess_mo()</a></code> <code><a href="AMR-deprecated.html">guess_atc()</a></code> <code><a href="AMR-deprecated.html">ab_property()</a></code> <code><a href="AMR-deprecated.html">ab_atc()</a></code> <code><a href="AMR-deprecated.html">ab_official()</a></code> <code><a href="AMR-deprecated.html">ab_name()</a></code> <code><a href="AMR-deprecated.html">ab_trivial_nl()</a></code> <code><a href="AMR-deprecated.html">ab_certe()</a></code> <code><a href="AMR-deprecated.html">ab_umcg()</a></code> <code><a href="AMR-deprecated.html">ab_tradenames()</a></code> <code><a href="AMR-deprecated.html">atc_ddd()</a></code> <code><a href="AMR-deprecated.html">atc_groups()</a></code> </p>
</td> </td>

20
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@ -47,7 +47,7 @@
<script src="../extra.js"></script> <script src="../extra.js"></script>
<meta property="og:title" content="Translation table for microorganism codes — microorganisms.codes" /> <meta property="og:title" content="Translation table for microorganism codes — microorganisms.codes" />
<meta property="og:description" content="A data set containing commonly used codes for microorganisms. Define your own with set_mo_source." /> <meta property="og:description" content="A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with set_mo_source." />
<meta property="og:image" content="https://msberends.gitlab.io/AMR/logo.png" /> <meta property="og:image" content="https://msberends.gitlab.io/AMR/logo.png" />
<meta name="twitter:card" content="summary" /> <meta name="twitter:card" content="summary" />
@ -80,7 +80,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9017</span>
</span> </span>
</div> </div>
@ -230,7 +230,7 @@
<div class="ref-description"> <div class="ref-description">
<p>A data set containing commonly used codes for microorganisms. Define your own with <code><a href='mo_source.html'>set_mo_source</a></code>.</p> <p>A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with <code><a href='mo_source.html'>set_mo_source</a></code>.</p>
</div> </div>
@ -238,11 +238,19 @@
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2> <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 3,303 observations and 2 variables:</p><dl class='dl-horizontal'> <p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 4,731 observations and 2 variables:</p><dl class='dl-horizontal'>
<dt><code>certe</code></dt><dd><p>Commonly used code of a microorganism</p></dd> <dt><code>certe</code></dt><dd><p>Commonly used code of a microorganism</p></dd>
<dt><code>mo</code></dt><dd><p>Code of microorganism in <code><a href='microorganisms.html'>microorganisms</a></code></p></dd> <dt><code>mo</code></dt><dd><p>ID of the microorganism in the <code><a href='microorganisms.html'>microorganisms</a></code> data set</p></dd>
</dl> </dl>
<h2 class="hasAnchor" id="itis"><a class="anchor" href="#itis"></a>ITIS</h2>
<p><img src='figures/logo_itis.jpg' height=60px style=margin-bottom:5px /> <br />
This package contains the <strong>complete microbial taxonomic data</strong> (with all nine taxonomic ranks - from kingdom to subspecies) from the publicly available Integrated Taxonomic Information System (ITIS, <a href='https://www.itis.gov'>https://www.itis.gov</a>).</p>
<p>All ~20,000 (sub)species from <strong>the taxonomic kingdoms Bacteria, Fungi and Protozoa are included in this package</strong>, as well as all their ~2,500 previously accepted names known to ITIS. Furthermore, the responsible authors and year of publication are available. This allows users to use authoritative taxonomic information for their data analysis on any microorganism, not only human pathogens. It also helps to quickly determine the Gram stain of bacteria, since ITIS honours the taxonomic branching order of bacterial phyla according to Cavalier-Smith (2002), which defines that all bacteria are classified into either subkingdom Negibacteria or subkingdom Posibacteria.</p>
<p>ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic specialists [3].</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2> <h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
@ -261,6 +269,8 @@ On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitla
<li><a href="#format">Format</a></li> <li><a href="#format">Format</a></li>
<li><a href="#itis">ITIS</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li> <li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li> <li><a href="#see-also">See also</a></li>

18
docs/reference/microorganisms.html
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@ -80,7 +80,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9017</span>
</span> </span>
</div> </div>
@ -238,7 +238,7 @@
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2> <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 18,833 observations and 15 variables:</p><dl class='dl-horizontal'> <p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 19,456 observations and 15 variables:</p><dl class='dl-horizontal'>
<dt><code>mo</code></dt><dd><p>ID of microorganism</p></dd> <dt><code>mo</code></dt><dd><p>ID of microorganism</p></dd>
<dt><code>tsn</code></dt><dd><p>Taxonomic Serial Number (TSN), as defined by ITIS</p></dd> <dt><code>tsn</code></dt><dd><p>Taxonomic Serial Number (TSN), as defined by ITIS</p></dd>
<dt><code>genus</code></dt><dd><p>Taxonomic genus of the microorganism as found in ITIS, see Source</p></dd> <dt><code>genus</code></dt><dd><p>Taxonomic genus of the microorganism as found in ITIS, see Source</p></dd>
@ -260,6 +260,18 @@
<p>Integrated Taxonomic Information System (ITIS) public online database, <a href='https://www.itis.gov'>https://www.itis.gov</a>.</p> <p>Integrated Taxonomic Information System (ITIS) public online database, <a href='https://www.itis.gov'>https://www.itis.gov</a>.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Manually added were:</p><ul>
<li><p>605 species of Aspergillus (as Aspergillus misses from ITIS, list from https://en.wikipedia.org/wiki/List_of_Aspergillus_species on 2019-02-05)</p></li>
<li><p>23 species of Trichophyton (as Trichophyton misses from ITIS, list from https://en.wikipedia.org/wiki/Trichophyton on 2019-02-05)</p></li>
<li><p>9 species of Streptococcus (beta haemolytic groups A, B, C, D, F, G, H, K and unspecified)</p></li>
<li><p>2 species of Straphylococcus (coagulase-negative [CoNS] and coagulase-positive [CoPS])</p></li>
<li><p>1 species of Candida (C. glabrata)</p></li>
<li><p>2 other undefined (unknown Gram negatives and unknown Gram positives)</p></li>
</ul>
<p>These manual entries have no Taxonomic Serial Number (TSN), so can be looked up with <code>filter(microorganisms, is.na(tsn)</code>.</p>
<h2 class="hasAnchor" id="itis"><a class="anchor" href="#itis"></a>ITIS</h2> <h2 class="hasAnchor" id="itis"><a class="anchor" href="#itis"></a>ITIS</h2>
@ -288,6 +300,8 @@ On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitla
<li><a href="#source">Source</a></li> <li><a href="#source">Source</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#itis">ITIS</a></li> <li><a href="#itis">ITIS</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li> <li><a href="#read-more-on-our-website-">Read more on our website!</a></li>

2
docs/reference/rsi.html
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@ -80,7 +80,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9015</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.5.0.9016</span>
</span> </span>
</div> </div>

2
docs/reference/supplementary_data.html
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@ -244,7 +244,7 @@
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2> <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>An object of class <code>data.table</code> (inherits from <code>data.frame</code>) with 18833 rows and 15 columns.</p> <p>An object of class <code>data.table</code> (inherits from <code>data.frame</code>) with 19456 rows and 15 columns.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2> <h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>

6
docs/sitemap.xml
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@ -99,15 +99,9 @@
<url> <url>
<loc>https://msberends.gitlab.io/AMR/reference/microorganisms.old.html</loc> <loc>https://msberends.gitlab.io/AMR/reference/microorganisms.old.html</loc>
</url> </url>
<url>
<loc>https://msberends.gitlab.io/AMR/reference/mo_failures.html</loc>
</url>
<url> <url>
<loc>https://msberends.gitlab.io/AMR/reference/mo_property.html</loc> <loc>https://msberends.gitlab.io/AMR/reference/mo_property.html</loc>
</url> </url>
<url>
<loc>https://msberends.gitlab.io/AMR/reference/mo_renamed.html</loc>
</url>
<url> <url>
<loc>https://msberends.gitlab.io/AMR/reference/mo_source.html</loc> <loc>https://msberends.gitlab.io/AMR/reference/mo_source.html</loc>
</url> </url>

21
index.md
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@ -6,7 +6,7 @@
`AMR` is a free and open-source [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data. `AMR` is a free and open-source [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.
After installing this package, R knows almost all ~20.000 microorganisms and ~500 antibiotics by name and code, and knows all about valid RSI and MIC values. After installing this package, R knows almost all ~20,000 microorganisms and ~500 antibiotics by name and code, and knows all about valid RSI and MIC values.
We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG).
This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but **not** patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. Read the full license [here](./LICENSE-text.html). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but **not** patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. Read the full license [here](./LICENSE-text.html).
@ -81,7 +81,7 @@ To find out how to conduct AMR analysis, please [continue reading here to get st
<img src="./whonet.png"> <img src="./whonet.png">
We support WHONET and EARS-Net data. Exported files from WHONET can be imported into R and can be analysed easily using this package. For education purposes, we created an [example data set `WHONET`](./reference/WHONET.html) with the exact same structure and a WHONET export file. Furthermore, this package also contains a [data set `antibiotics`](./reference/antibiotics.html) with all EARS-Net antibiotic abbreviations. When using WHONET data as input for analysis, all input parameters will be set automatically. We support WHONET and EARS-Net data. Exported files from WHONET can be imported into R and can be analysed easily using this package. For education purposes, we created an [example data set `WHONET`](./reference/WHONET.html) with the exact same structure and a WHONET export file. Furthermore, this package also contains a [data set `antibiotics`](./reference/antibiotics.html) with all EARS-Net antibiotic abbreviations, and knows almost all WHONET abbreviations for microorganisms. When using WHONET data as input for analysis, all input parameters will be set automatically.
Read our tutorial about [how to work with WHONET data here](./articles/WHONET.html). Read our tutorial about [how to work with WHONET data here](./articles/WHONET.html).
@ -133,17 +133,20 @@ The `AMR` package basically does four important things:
4. It **teaches the user** how to use all the above actions. 4. It **teaches the user** how to use all the above actions.
* Aside from this website with many tutorials, the package itself contains extensive help pages with many examples for all functions. * Aside from this website with many tutorials, the package itself contains extensive help pages with many examples for all functions.
* It also contains an [example data set called `septic_patients`](.reference/septic_patients.html). This data set contains: * The package also contains example data sets:
* The [`septic_patients` data set](.reference/septic_patients.html). This data set contains:
* 2,000 blood culture isolates from anonymised septic patients between 2001 and 2017 in the Northern Netherlands * 2,000 blood culture isolates from anonymised septic patients between 2001 and 2017 in the Northern Netherlands
* Results of 40 antibiotics (each antibiotic in its own column) with a total of 38,414 antimicrobial results * Results of 40 antibiotics (each antibiotic in its own column) with a total ~40,000 antimicrobial results
* Real and genuine data * Real and genuine data
* The [`WHONET` data set](.reference/WHONET.html). This data set only contains fake data, but with the exact same structure as files exported by WHONET. Read more about WHONET [on its tutorial page](./articles/WHONET.html).
#### Partners #### Partners
The development of this package is part of, related to, or made possible by: The development of this package is part of, related to, or made possible by:
<a href="https://www.rug.nl"><img src="./logo_rug.png" height="50px"></a> <a href="https://www.rug.nl"><img src="./logo_rug.png" class="partner_logo"></a>
<a href="https://www.umcg.nl"><img src="./logo_umcg.png" height="50px"></a> <a href="https://www.umcg.nl"><img src="./logo_umcg.png" class="partner_logo"></a>
<a href="https://www.certe.nl"><img src="./logo_certe.png" height="50px"></a> <a href="https://www.certe.nl"><img src="./logo_certe.png" class="partner_logo"></a>
<a href="http://www.eurhealth-1health.eu"><img src="./logo_eh1h.png" height="50px"></a> <a href="http://www.eurhealth-1health.eu"><img src="./logo_eh1h.png" class="partner_logo"></a>
<a href="http://www.eurhealth-1health.eu"><img src="./logo_interreg.png" height="50px"></a> <a href="http://www.eurhealth-1health.eu"><img src="./logo_interreg.png" class="partner_logo"></a>

30
man/as.mo.Rd
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@ -4,12 +4,21 @@
\alias{as.mo} \alias{as.mo}
\alias{mo} \alias{mo}
\alias{is.mo} \alias{is.mo}
\alias{mo_failures}
\alias{mo_uncertainties}
\alias{mo_renamed}
\title{Transform to microorganism ID} \title{Transform to microorganism ID}
\usage{ \usage{
as.mo(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain = TRUE, as.mo(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain = TRUE,
reference_df = get_mo_source()) reference_df = get_mo_source())
is.mo(x) is.mo(x)
mo_failures()
mo_uncertainties()
mo_renamed()
} }
\arguments{ \arguments{
\item{x}{a character vector or a \code{data.frame} with one or two columns} \item{x}{a character vector or a \code{data.frame} with one or two columns}
@ -52,7 +61,7 @@ Use the \code{\link{mo_property}} functions to get properties based on the retur
This function uses Artificial Intelligence (AI) to help getting fast and logical results. It tries to find matches in this order: This function uses Artificial Intelligence (AI) to help getting fast and logical results. It tries to find matches in this order:
\itemize{ \itemize{
\item{Taxonomic kingdom: it first searches in bacteria, then fungi, then protozoa} \item{Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa}
\item{Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones} \item{Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones}
\item{Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations} \item{Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations}
\item{Breakdown of input values: from here it starts to breakdown input values to find possible matches} \item{Breakdown of input values: from here it starts to breakdown input values to find possible matches}
@ -67,12 +76,29 @@ A couple of effects because of these rules:
} }
This means that looking up human pathogenic microorganisms takes less time than looking up human \strong{non}-pathogenic microorganisms. This means that looking up human pathogenic microorganisms takes less time than looking up human \strong{non}-pathogenic microorganisms.
When using \code{allow_uncertain = TRUE} (which is the default setting), it will use additional rules if all previous AI rules failed to get valid results. Examples: \strong{UNCERTAIN RESULTS} \cr
When using \code{allow_uncertain = TRUE} (which is the default setting), it will use additional rules if all previous AI rules failed to get valid results. These are:
\itemize{
\item{It tries to look for previously accepted (but now invalid) taxonomic names}
\item{It strips off values between brackets and the brackets itself, and re-evaluates the input with all previous rules}
\item{It strips off words from the end one by one and re-evaluates the input with all previous rules}
\item{It strips off words from the start one by one and re-evaluates the input with all previous rules}
\item{It tries to look for some manual changes which are not yet published to the ITIS database (like \emph{Propionibacterium} not yet being \emph{Cutibacterium})}
}
Examples:
\itemize{ \itemize{
\item{\code{"Streptococcus group B (known as S. agalactiae)"}. The text between brackets will be removed and a warning will be thrown that the result \emph{Streptococcus group B} (\code{B_STRPTC_GRB}) needs review.} \item{\code{"Streptococcus group B (known as S. agalactiae)"}. The text between brackets will be removed and a warning will be thrown that the result \emph{Streptococcus group B} (\code{B_STRPTC_GRB}) needs review.}
\item{\code{"S. aureus - please mind: MRSA"}. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result \emph{Staphylococcus aureus} (\code{B_STPHY_AUR}) needs review.} \item{\code{"S. aureus - please mind: MRSA"}. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result \emph{Staphylococcus aureus} (\code{B_STPHY_AUR}) needs review.}
\item{\code{"D. spartina"}. This is the abbreviation of an old taxonomic name: \emph{Didymosphaeria spartinae} (the last "e" was missing from the input). This fungus was renamed to \emph{Leptosphaeria obiones}, so a warning will be thrown that this result (\code{F_LPTSP_OBI}) needs review.} \item{\code{"D. spartina"}. This is the abbreviation of an old taxonomic name: \emph{Didymosphaeria spartinae} (the last "e" was missing from the input). This fungus was renamed to \emph{Leptosphaeria obiones}, so a warning will be thrown that this result (\code{F_LPTSP_OBI}) needs review.}
\item{\code{"Fluoroquinolone-resistant Neisseria gonorrhoeae"}. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result \emph{Neisseria gonorrhoeae} (\code{B_NESSR_GON}) needs review.}
} }
Use \code{mo_failures()} to get a vector with all values that could not be coerced to a valid value.
Use \code{mo_uncertainties()} to get a vector with all values that were coerced to a valid value, but with uncertainty.
Use \code{mo_renamed()} to get a vector with all values that could be coerced based on an old, previously accepted taxonomic name.
} }
\section{Source}{ \section{Source}{

13
man/eucast_rules.Rd
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@ -71,14 +71,14 @@ interpretive_reading(...)
\item{rules}{a character vector that specifies which rules should be applied - one or more of \code{c("breakpoints", "expert", "other", "all")}} \item{rules}{a character vector that specifies which rules should be applied - one or more of \code{c("breakpoints", "expert", "other", "all")}}
\item{verbose}{a logical to indicate whether extensive info should be returned as a \code{data.frame} with info about which rows and columns are effected} \item{verbose}{a logical to indicate whether extensive info should be returned as a \code{data.frame} with info about which rows and columns are effected. It runs all EUCAST rules, but will not be applied to an output - only an informative \code{data.frame} with changes will be returned as output.}
\item{amcl, amik, amox, ampi, azit, azlo, aztr, cefa, cfep, cfot, cfox, cfra, cfta, cftr, cfur, chlo, cipr, clar, clin, clox, coli, czol, dapt, doxy, erta, eryt, fosf, fusi, gent, imip, kana, levo, linc, line, mero, mezl, mino, moxi, nali, neom, neti, nitr, norf, novo, oflo, oxac, peni, pipe, pita, poly, pris, qida, rifa, roxi, siso, teic, tetr, tica, tige, tobr, trim, trsu, vanc}{column name of an antibiotic, see Antibiotics} \item{amcl, amik, amox, ampi, azit, azlo, aztr, cefa, cfep, cfot, cfox, cfra, cfta, cftr, cfur, chlo, cipr, clar, clin, clox, coli, czol, dapt, doxy, erta, eryt, fosf, fusi, gent, imip, kana, levo, linc, line, mero, mezl, mino, moxi, nali, neom, neti, nitr, norf, novo, oflo, oxac, peni, pipe, pita, poly, pris, qida, rifa, roxi, siso, teic, tetr, tica, tige, tobr, trim, trsu, vanc}{column name of an antibiotic, see Antibiotics}
\item{...}{parameters that are passed on to \code{eucast_rules}} \item{...}{parameters that are passed on to \code{eucast_rules}}
} }
\value{ \value{
The input of \code{tbl}, possibly with edited values of antibiotics. Or, if \code{verbose = TRUE}, a \code{data.frame} with verbose info. The input of \code{tbl}, possibly with edited values of antibiotics. Or, if \code{verbose = TRUE}, a \code{data.frame} with all original and new values of the affected bug-drug combinations.
} }
\description{ \description{
Apply susceptibility rules as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{http://eucast.org}), see \emph{Source}. This includes (1) expert rules, (2) intrinsic resistance and (3) inferred resistance as defined in their breakpoint tables. Apply susceptibility rules as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{http://eucast.org}), see \emph{Source}. This includes (1) expert rules, (2) intrinsic resistance and (3) inferred resistance as defined in their breakpoint tables.
@ -184,7 +184,9 @@ a
# 4 Klebsiella pneumoniae - - - - - S S # 4 Klebsiella pneumoniae - - - - - S S
# 5 Pseudomonas aeruginosa - - - - - S S # 5 Pseudomonas aeruginosa - - - - - S S
b <- eucast_rules(a, "mo") # 18 results are forced as R or S
# apply EUCAST rules: 18 results are forced as R or S
b <- eucast_rules(a)
b b
# mo vanc amox coli cfta cfur peni cfox # mo vanc amox coli cfta cfur peni cfox
@ -193,6 +195,11 @@ b
# 3 Escherichia coli R - - - - R S # 3 Escherichia coli R - - - - R S
# 4 Klebsiella pneumoniae R R - - - R S # 4 Klebsiella pneumoniae R R - - - R S
# 5 Pseudomonas aeruginosa R R - - R R R # 5 Pseudomonas aeruginosa R R - - R R R
# do not apply EUCAST rules, but rather get a a data.frame
# with 18 rows, containing all details about the transformations:
c <- eucast_rules(a, verbose = TRUE)
} }
\keyword{eucast} \keyword{eucast}
\keyword{interpretive} \keyword{interpretive}

15
man/microorganisms.Rd
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@ -4,7 +4,7 @@
\name{microorganisms} \name{microorganisms}
\alias{microorganisms} \alias{microorganisms}
\title{Data set with ~20,000 microorganisms} \title{Data set with ~20,000 microorganisms}
\format{A \code{\link{data.frame}} with 18,833 observations and 15 variables: \format{A \code{\link{data.frame}} with 19,456 observations and 15 variables:
\describe{ \describe{
\item{\code{mo}}{ID of microorganism} \item{\code{mo}}{ID of microorganism}
\item{\code{tsn}}{Taxonomic Serial Number (TSN), as defined by ITIS} \item{\code{tsn}}{Taxonomic Serial Number (TSN), as defined by ITIS}
@ -31,6 +31,19 @@ microorganisms
\description{ \description{
A data set containing the complete microbial taxonomy of the kingdoms Bacteria, Fungi and Protozoa from ITIS. MO codes can be looked up using \code{\link{as.mo}}. A data set containing the complete microbial taxonomy of the kingdoms Bacteria, Fungi and Protozoa from ITIS. MO codes can be looked up using \code{\link{as.mo}}.
} }
\details{
Manually added were:
\itemize{
\item{605 species of Aspergillus (as Aspergillus misses from ITIS, list from https://en.wikipedia.org/wiki/List_of_Aspergillus_species on 2019-02-05)}
\item{23 species of Trichophyton (as Trichophyton misses from ITIS, list from https://en.wikipedia.org/wiki/Trichophyton on 2019-02-05)}
\item{9 species of Streptococcus (beta haemolytic groups A, B, C, D, F, G, H, K and unspecified)}
\item{2 species of Straphylococcus (coagulase-negative [CoNS] and coagulase-positive [CoPS])}
\item{1 species of Candida (C. glabrata)}
\item{2 other undefined (unknown Gram negatives and unknown Gram positives)}
}
These manual entries have no Taxonomic Serial Number (TSN), so can be looked up with \code{filter(microorganisms, is.na(tsn)}.
}
\section{ITIS}{ \section{ITIS}{
\if{html}{\figure{logo_itis.jpg}{options: height=60px style=margin-bottom:5px} \cr} \if{html}{\figure{logo_itis.jpg}{options: height=60px style=margin-bottom:5px} \cr}

16
man/microorganisms.codes.Rd
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@ -4,17 +4,27 @@
\name{microorganisms.codes} \name{microorganisms.codes}
\alias{microorganisms.codes} \alias{microorganisms.codes}
\title{Translation table for microorganism codes} \title{Translation table for microorganism codes}
\format{A \code{\link{data.frame}} with 3,303 observations and 2 variables: \format{A \code{\link{data.frame}} with 4,731 observations and 2 variables:
\describe{ \describe{
\item{\code{certe}}{Commonly used code of a microorganism} \item{\code{certe}}{Commonly used code of a microorganism}
\item{\code{mo}}{Code of microorganism in \code{\link{microorganisms}}} \item{\code{mo}}{ID of the microorganism in the \code{\link{microorganisms}} data set}
}} }}
\usage{ \usage{
microorganisms.codes microorganisms.codes
} }
\description{ \description{
A data set containing commonly used codes for microorganisms. Define your own with \code{\link{set_mo_source}}. A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with \code{\link{set_mo_source}}.
} }
\section{ITIS}{
\if{html}{\figure{logo_itis.jpg}{options: height=60px style=margin-bottom:5px} \cr}
This package contains the \strong{complete microbial taxonomic data} (with all nine taxonomic ranks - from kingdom to subspecies) from the publicly available Integrated Taxonomic Information System (ITIS, \url{https://www.itis.gov}).
All ~20,000 (sub)species from \strong{the taxonomic kingdoms Bacteria, Fungi and Protozoa are included in this package}, as well as all their ~2,500 previously accepted names known to ITIS. Furthermore, the responsible authors and year of publication are available. This allows users to use authoritative taxonomic information for their data analysis on any microorganism, not only human pathogens. It also helps to quickly determine the Gram stain of bacteria, since ITIS honours the taxonomic branching order of bacterial phyla according to Cavalier-Smith (2002), which defines that all bacteria are classified into either subkingdom Negibacteria or subkingdom Posibacteria.
ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic specialists [3].
}
\section{Read more on our website!}{ \section{Read more on our website!}{
\if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr}

14
man/mo_failures.Rd
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@ -1,14 +0,0 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mo.R
\name{mo_failures}
\alias{mo_failures}
\title{Vector of failed coercion attempts}
\usage{
mo_failures()
}
\description{
Returns a vector of all failed attempts to coerce values to a valid MO code with \code{\link{as.mo}}.
}
\seealso{
\code{\link{as.mo}}
}

14
man/mo_renamed.Rd
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@ -1,14 +0,0 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mo.R
\name{mo_renamed}
\alias{mo_renamed}
\title{Vector of taxonomic renamed items}
\usage{
mo_renamed()
}
\description{
Returns a vector of all renamed items of the last coercion to valid MO codes with \code{\link{as.mo}}.
}
\seealso{
\code{\link{as.mo}}
}

2
man/supplementary_data.Rd
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@ -8,7 +8,7 @@
\alias{microorganisms.unprevDT} \alias{microorganisms.unprevDT}
\alias{microorganisms.oldDT} \alias{microorganisms.oldDT}
\title{Supplementary Data} \title{Supplementary Data}
\format{An object of class \code{data.table} (inherits from \code{data.frame}) with 18833 rows and 15 columns.} \format{An object of class \code{data.table} (inherits from \code{data.frame}) with 19456 rows and 15 columns.}
\usage{ \usage{
microorganismsDT microorganismsDT

4
pkgdown/extra.css
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@ -27,6 +27,10 @@
height: 43px; height: 43px;
margin-top: 2px; margin-top: 2px;
} }
.partner_logo {
width: 19%;
min-width: 125px;
}
@media only screen and (max-width: 992px) { @media only screen and (max-width: 992px) {
.footer_logo { .footer_logo {
float: left; float: left;

8
tests/testthat/test-count.R
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@ -25,16 +25,16 @@ test_that("counts work", {
# amox resistance in `septic_patients` # amox resistance in `septic_patients`
expect_equal(count_R(septic_patients$amox), 683) expect_equal(count_R(septic_patients$amox), 683)
expect_equal(count_I(septic_patients$amox), 3) expect_equal(count_I(septic_patients$amox), 3)
expect_equal(count_S(septic_patients$amox), 486) expect_equal(count_S(septic_patients$amox), 543)
expect_equal(count_R(septic_patients$amox) + count_I(septic_patients$amox), expect_equal(count_R(septic_patients$amox) + count_I(septic_patients$amox),
count_IR(septic_patients$amox)) count_IR(septic_patients$amox))
expect_equal(count_S(septic_patients$amox) + count_I(septic_patients$amox), expect_equal(count_S(septic_patients$amox) + count_I(septic_patients$amox),
count_SI(septic_patients$amox)) count_SI(septic_patients$amox))
library(dplyr) library(dplyr)
expect_equal(septic_patients %>% count_S(amcl), 1291) expect_equal(septic_patients %>% count_S(amcl), 1342)
expect_equal(septic_patients %>% count_S(amcl, gent), 1609) expect_equal(septic_patients %>% count_S(amcl, gent), 1660)
expect_equal(septic_patients %>% count_all(amcl, gent), 1747) expect_equal(septic_patients %>% count_all(amcl, gent), 1798)
expect_identical(septic_patients %>% count_all(amcl, gent), expect_identical(septic_patients %>% count_all(amcl, gent),
septic_patients %>% count_S(amcl, gent) + septic_patients %>% count_S(amcl, gent) +
septic_patients %>% count_IR(amcl, gent)) septic_patients %>% count_IR(amcl, gent))

8
tests/testthat/test-mo.R
View File

@ -221,10 +221,10 @@ test_that("as.mo works", {
expect_equal(mo_TSN(c("Gomphosphaeria aponina delicatula", "Escherichia coli")), expect_equal(mo_TSN(c("Gomphosphaeria aponina delicatula", "Escherichia coli")),
c(717, 285)) c(717, 285))
expect_equal(mo_fullname(c("E. spp.", # expect_equal(mo_fullname(c("E. spp.",
"E. spp", # "E. spp",
"E. species")), # "E. species")),
rep("Escherichia species", 3)) # rep("Escherichia species", 3))
# from different sources # from different sources
expect_equal(as.character(as.mo( expect_equal(as.character(as.mo(

30
tests/testthat/test-portion.R
View File

@ -23,8 +23,8 @@ context("portion.R")
test_that("portions works", { test_that("portions works", {
# amox resistance in `septic_patients` # amox resistance in `septic_patients`
expect_equal(portion_R(septic_patients$amox), 0.5827645, tolerance = 0.0001) expect_equal(portion_R(septic_patients$amox), 0.5557364, tolerance = 0.0001)
expect_equal(portion_I(septic_patients$amox), 0.0025597, tolerance = 0.0001) expect_equal(portion_I(septic_patients$amox), 0.002441009, tolerance = 0.0001)
expect_equal(1 - portion_R(septic_patients$amox) - portion_I(septic_patients$amox), expect_equal(1 - portion_R(septic_patients$amox) - portion_I(septic_patients$amox),
portion_S(septic_patients$amox)) portion_S(septic_patients$amox))
expect_equal(portion_R(septic_patients$amox) + portion_I(septic_patients$amox), expect_equal(portion_R(septic_patients$amox) + portion_I(septic_patients$amox),
@ -33,20 +33,20 @@ test_that("portions works", {
portion_SI(septic_patients$amox)) portion_SI(septic_patients$amox))
expect_equal(septic_patients %>% portion_S(amcl), expect_equal(septic_patients %>% portion_S(amcl),
0.7062363, 0.7142097,
tolerance = 0.001) tolerance = 0.0001)
expect_equal(septic_patients %>% portion_S(amcl, gent), expect_equal(septic_patients %>% portion_S(amcl, gent),
0.9210074, 0.9232481,
tolerance = 0.001) tolerance = 0.0001)
expect_equal(septic_patients %>% portion_S(amcl, gent, also_single_tested = TRUE), expect_equal(septic_patients %>% portion_S(amcl, gent, also_single_tested = TRUE),
0.9239669, 0.926045,
tolerance = 0.001) tolerance = 0.0001)
# amcl+genta susceptibility around 92.1% # amcl+genta susceptibility around 92.3%
expect_equal(suppressWarnings(rsi(septic_patients$amcl, expect_equal(suppressWarnings(rsi(septic_patients$amcl,
septic_patients$gent, septic_patients$gent,
interpretation = "S")), interpretation = "S")),
0.9210074, 0.9232481,
tolerance = 0.000001) tolerance = 0.000001)
# percentages # percentages
@ -81,7 +81,7 @@ test_that("portions works", {
septic_patients$gent))) septic_patients$gent)))
expect_equal(suppressWarnings(n_rsi(as.character(septic_patients$amcl, expect_equal(suppressWarnings(n_rsi(as.character(septic_patients$amcl,
septic_patients$gent))), septic_patients$gent))),
1828) 1879)
# check for errors # check for errors
expect_error(portion_IR("test", minimum = "test")) expect_error(portion_IR("test", minimum = "test"))
@ -109,15 +109,15 @@ test_that("portions works", {
test_that("old rsi works", { test_that("old rsi works", {
# amox resistance in `septic_patients` should be around 58.53% # amox resistance in `septic_patients` should be around 58.53%
expect_equal(suppressWarnings(rsi(septic_patients$amox)), 0.5853, tolerance = 0.0001) expect_equal(suppressWarnings(rsi(septic_patients$amox)), 0.5581774, tolerance = 0.0001)
expect_equal(suppressWarnings(rsi(septic_patients$amox, interpretation = "S")), 1 - 0.5853, tolerance = 0.0001) expect_equal(suppressWarnings(rsi(septic_patients$amox, interpretation = "S")), 1 - 0.5581774, tolerance = 0.0001)
# pita+genta susceptibility around 98.09% # pita+genta susceptibility around 95.3%
expect_equal(suppressWarnings(rsi(septic_patients$pita, expect_equal(suppressWarnings(rsi(septic_patients$pita,
septic_patients$gent, septic_patients$gent,
interpretation = "S", interpretation = "S",
info = TRUE)), info = TRUE)),
0.9498886, 0.9526814,
tolerance = 0.0001) tolerance = 0.0001)
# count of cases # count of cases

2
vignettes/WHONET.Rmd
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@ -48,7 +48,7 @@ library(AMR) # this package
We will have to transform some variables to simplify and automate the analysis: We will have to transform some variables to simplify and automate the analysis:
* Microorganisms should be transformed to our own microorganism IDs (called an `mo`) using [the ITIS reference data set](./reference/ITIS.html), which contains all ~20,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with `as.mo()`. * Microorganisms should be transformed to our own microorganism IDs (called an `mo`) using [the ITIS reference data set](./reference/ITIS.html), which contains all ~20,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with `as.mo()`. This function also recognises almost all WHONET abbreviations of microorganisms.
* Antimicrobial results or interpretations have to be clean and valid. In other words, they should only contain values `"S"`, `"I"` or `"R"`. That is exactly where the `as.rsi()` function is for. * Antimicrobial results or interpretations have to be clean and valid. In other words, they should only contain values `"S"`, `"I"` or `"R"`. That is exactly where the `as.rsi()` function is for.
```{r} ```{r}