diff --git a/.Rbuildignore b/.Rbuildignore
index 1be477454..254a42657 100755
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -11,7 +11,6 @@
^codecov\.yml$
^cran-comments\.md$
^CRAN-RELEASE$
-^developer-guideline.md$
^\.github$
^doc$
^docs$
diff --git a/.github/workflows/check.yaml b/.github/workflows/check.yaml
index c3fe95544..48529b674 100644
--- a/.github/workflows/check.yaml
+++ b/.github/workflows/check.yaml
@@ -99,9 +99,9 @@ jobs:
if: runner.os == 'Linux'
# update the below with sysreqs::sysreqs("DESCRIPTION") and check the "DEB" entries (for Ubuntu).
# we don't want to depend on the sysreqs pkg here, as it requires quite a recent R version
- # as of May 2021: https://sysreqs.r-hub.io/pkg/AMR,R,cleaner,curl,dplyr,ggplot2,ggtext,knitr,microbenchmark,pillar,readxl,rmarkdown,rstudioapi,rvest,skimr,tidyr,tinytest,xml2,backports,crayon,rlang,vctrs,evaluate,highr,markdown,stringr,yaml,xfun,cli,ellipsis,fansi,lifecycle,utf8,glue,mime,magrittr,stringi,generics,R6,tibble,tidyselect,pkgconfig,purrr,digest,gtable,isoband,MASS,mgcv,scales,withr,nlme,Matrix,farver,labeling,munsell,RColorBrewer,viridisLite,lattice,colorspace,gridtext,Rcpp,RCurl,png,jpeg,bitops,cellranger,progress,rematch,hms,prettyunits,htmltools,jsonlite,tinytex,base64enc,httr,selectr,openssl,askpass,sys,repr,cpp11
+ # as of May 2021: https://sysreqs.r-hub.io/pkg/AMR,R,cleaner,curl,dplyr,ggplot2,knitr,microbenchmark,pillar,readxl,rmarkdown,rstudioapi,rvest,skimr,tidyr,tinytest,xml2,backports,crayon,rlang,vctrs,evaluate,highr,markdown,stringr,yaml,xfun,cli,ellipsis,fansi,lifecycle,utf8,glue,mime,magrittr,stringi,generics,R6,tibble,tidyselect,pkgconfig,purrr,digest,gtable,isoband,MASS,mgcv,scales,withr,nlme,Matrix,farver,labeling,munsell,RColorBrewer,viridisLite,lattice,colorspace,gridtext,Rcpp,RCurl,png,jpeg,bitops,cellranger,progress,rematch,hms,prettyunits,htmltools,jsonlite,tinytex,base64enc,httr,selectr,openssl,askpass,sys,repr,cpp11
run: |
- sudo apt install -y libssl-dev libxml2-dev libicu-dev libcurl4-openssl-dev libpng-dev
+ sudo apt install -y libssl-dev libxml2-dev libcurl4-openssl-dev
- name: Restore cached R packages
# this step will add the step 'Post Restore cached R packages' on a succesful run
diff --git a/.github/workflows/website.yaml b/.github/workflows/website.yaml
index 078953507..d87aaa8ad 100644
--- a/.github/workflows/website.yaml
+++ b/.github/workflows/website.yaml
@@ -29,7 +29,7 @@
on:
push:
# only on main
- branches: 'main - REMOVE THIS LATER'
+ branches: 'main'
name: Update website
@@ -57,5 +57,4 @@ jobs:
run: |
git config user.name "github-actions"
git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
- # Rscript -e 'pkgdown::build_favicons()'
Rscript -e 'pkgdown::deploy_to_branch(new_process = FALSE, clean = TRUE, install = TRUE, branch = "gh-pages")'
diff --git a/DESCRIPTION b/DESCRIPTION
index d1312b750..71fc1350a 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
Package: AMR
-Version: 1.8.1.9018
-Date: 2022-08-20
+Version: 1.8.1.9019
+Date: 2022-08-21
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)
data analysis and to work with microbial and antimicrobial properties by
@@ -12,6 +12,7 @@ Authors@R: c(
person("Dennis", "Souverein", role = c("aut", "ctb"), comment = c(ORCID = "0000-0003-0455-0336")),
person(c("Erwin", "E.", "A."), "Hassing", role = c("aut", "ctb")),
person("Casper", "Albers", role = "ths", comment = c(ORCID = "0000-0002-9213-6743")),
+ person("Peter", "Dutey-Magni", role = "ctb", comment = c(ORCID = "0000-0002-8942-9836")),
person("Judith", "Fonville", role = "ctb"),
person("Alex", "Friedrich", role = "ths", comment = c(ORCID = "0000-0003-4881-038X")),
person("Corinna", "Glasner", role = "ths", comment = c(ORCID = "0000-0003-1241-1328")),
@@ -33,7 +34,6 @@ Enhances:
Suggests:
curl,
dplyr,
- ggtext,
knitr,
progress,
readxl,
diff --git a/NEWS.md b/NEWS.md
index 352be3b42..68dbd54b0 100755
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,4 +1,4 @@
-# AMR 1.8.1.9018
+# AMR 1.8.1.9019
### New
* EUCAST 2022 and CLSI 2022 guidelines have been added for `as.rsi()`. EUCAST 2022 is now the new default guideline for all MIC and disks diffusion interpretations.
@@ -13,6 +13,12 @@
* Using any `random_*()` function (such as `random_mic()`) is now possible by directly calling the package without loading it first: `AMR::random_mic(10)`
* Added *Toxoplasma gondii* (`P_TXPL_GOND`) to the `microorganisms` data set, together with its genus, family, and order
* Changed value in column `prevalence` of the `microorganisms` data set from 3 to 2 for these genera: *Acholeplasma*, *Alistipes*, *Alloprevotella*, *Bergeyella*, *Borrelia*, *Brachyspira*, *Butyricimonas*, *Cetobacterium*, *Chlamydia*, *Chlamydophila*, *Deinococcus*, *Dysgonomonas*, *Elizabethkingia*, *Empedobacter*, *Haloarcula*, *Halobacterium*, *Halococcus*, *Myroides*, *Odoribacter*, *Ornithobacterium*, *Parabacteroides*, *Pedobacter*, *Phocaeicola*, *Porphyromonas*, *Riemerella*, *Sphingobacterium*, *Streptobacillus*, *Tenacibaculum*, *Terrimonas*, *Victivallis*, *Wautersiella*, *Weeksella*
+* Fix for using the form `df[carbapenems() == "R", ]` using the latest `vctrs` package
+* Fix for using `info = FALSE` in `mdro()`
+
+### Other
+* New website to make use of the new Bootstrap 5 and pkgdown v2.0. The website now contains results for all examples and will be automatically regenerated with every change to our repository, using GitHub Actions
+* Added Peter Dutey-Magni and Anton Mymrikov as contributors, to thank them for their valuable input
# `AMR` 1.8.1
diff --git a/R/ab.R b/R/ab.R
index 7012169ff..0a19ee8db 100755
--- a/R/ab.R
+++ b/R/ab.R
@@ -26,7 +26,6 @@
#' Transform Input to an Antibiotic ID
#'
#' Use this function to determine the antibiotic code of one or more antibiotics. The data set [antibiotics] will be searched for abbreviations, official names and synonyms (brand names).
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [character] vector to determine to antibiotic ID
#' @param flag_multiple_results a [logical] to indicate whether a note should be printed to the console that probably more than one antibiotic code or name can be retrieved from a single input value.
#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
@@ -55,7 +54,6 @@
#' * [antibiotics] for the [data.frame] that is being used to determine ATCs
#' * [ab_from_text()] for a function to retrieve antimicrobial drugs from clinical text (from health care records)
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @export
#' @examples
#' # these examples all return "ERY", the ID of erythromycin:
diff --git a/R/ab_from_text.R b/R/ab_from_text.R
index 6feba8638..626c7c829 100644
--- a/R/ab_from_text.R
+++ b/R/ab_from_text.R
@@ -26,7 +26,6 @@
#' Retrieve Antimicrobial Drug Names and Doses from Clinical Text
#'
#' Use this function on e.g. clinical texts from health care records. It returns a [list] with all antimicrobial drugs, doses and forms of administration found in the texts.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param text text to analyse
#' @param type type of property to search for, either `"drug"`, `"dose"` or `"administration"`, see *Examples*
#' @param collapse a [character] to pass on to `paste(, collapse = ...)` to only return one [character] per element of `text`, see *Examples*
@@ -53,7 +52,6 @@
#' `df %>% mutate(abx = ab_from_text(clinical_text, collapse = "|"))`
#' @export
#' @return A [list], or a [character] if `collapse` is not `NULL`
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # mind the bad spelling of amoxicillin in this line,
#' # straight from a true health care record:
diff --git a/R/ab_property.R b/R/ab_property.R
index 42188a50a..2c2574939 100644
--- a/R/ab_property.R
+++ b/R/ab_property.R
@@ -26,7 +26,6 @@
#' Get Properties of an Antibiotic
#'
#' Use these functions to return a specific property of an antibiotic from the [antibiotics] data set. All input values will be evaluated internally with [as.ab()].
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
#' @param tolower a [logical] to indicate whether the first [character] of every output should be transformed to a lower case [character]. This will lead to e.g. "polymyxin B" and not "polymyxin b".
#' @param property one of the column names of one of the [antibiotics] data set: `vector_or(colnames(antibiotics), sort = FALSE)`.
@@ -54,7 +53,6 @@
#' @export
#' @seealso [antibiotics]
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # all properties:
#' ab_name("AMX") # "Amoxicillin"
@@ -101,15 +99,18 @@
#' \donttest{
#' if (require("dplyr")) {
#' example_isolates %>%
-#' set_ab_names()
+#' set_ab_names() %>%
+#' head()
#'
#' # this does the same:
#' example_isolates %>%
-#' rename_with(set_ab_names)
+#' rename_with(set_ab_names)%>%
+#' head()
#'
#' # set_ab_names() works with any AB property:
#' example_isolates %>%
-#' set_ab_names(property = "atc")
+#' set_ab_names(property = "atc")%>%
+#' head()
#'
#' example_isolates %>%
#' set_ab_names(where(is.rsi)) %>%
diff --git a/R/ab_selectors.R b/R/ab_selectors.R
index e63001be3..fd159a87f 100644
--- a/R/ab_selectors.R
+++ b/R/ab_selectors.R
@@ -26,7 +26,6 @@
#' Antibiotic Selectors
#'
#' These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group, without the need to define the columns or antibiotic abbreviations. In short, if you have a column name that resembles an antimicrobial agent, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "CZO" and "J01DB04" will all be picked up by [cephalosporins()].
-#' @inheritSection lifecycle Stable Lifecycle
#' @param ab_class an antimicrobial class or a part of it, such as `"carba"` and `"carbapenems"`. The columns `group`, `atc_group1` and `atc_group2` of the [antibiotics] data set will be searched (case-insensitive) for this value.
#' @param filter an [expression] to be evaluated in the [antibiotics] data set, such as `name %like% "trim"`
#' @param only_rsi_columns a [logical] to indicate whether only columns of class `<rsi>` must be selected (defaults to `FALSE`), see [as.rsi()]
@@ -46,103 +45,105 @@
#' @return (internally) a [character] vector of column names, with additional class `"ab_selector"`
#' @export
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+
#' @examples
#' # `example_isolates` is a data set available in the AMR package.
#' # See ?example_isolates.
+#' df <- example_isolates[ , c("hospital_id", "mo",
+#' "AMP", "AMC", "TZP", "CXM", "CRO", "GEN",
+#' "TOB", "COL", "IPM", "MEM", "TEC", "VAN")]
#'
#' # base R ------------------------------------------------------------------
#'
#' # select columns 'IPM' (imipenem) and 'MEM' (meropenem)
-#' example_isolates[, carbapenems()]
+#' df[, carbapenems()]
#'
#' # select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
-#' example_isolates[, c("mo", aminoglycosides())]
+#' df[, c("mo", aminoglycosides())]
#'
#' # select only antibiotic columns with DDDs for oral treatment
-#' example_isolates[, administrable_per_os()]
+#' df[, administrable_per_os()]
#'
#' # filter using any() or all()
-#' example_isolates[any(carbapenems() == "R"), ]
-#' subset(example_isolates, any(carbapenems() == "R"))
+#' df[any(carbapenems() == "R"), ]
+#' subset(df, any(carbapenems() == "R"))
#'
#' # filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
-#' example_isolates[any(carbapenems()), ]
-#' example_isolates[all(carbapenems()), ]
+#' df[any(carbapenems()), ]
+#' df[all(carbapenems()), ]
#'
#' # filter with multiple antibiotic selectors using c()
-#' example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]
+#' df[all(c(carbapenems(), aminoglycosides()) == "R"), ]
#'
#' # filter + select in one go: get penicillins in carbapenems-resistant strains
-#' example_isolates[any(carbapenems() == "R"), penicillins()]
+#' df[any(carbapenems() == "R"), penicillins()]
#'
#' # You can combine selectors with '&' to be more specific. For example,
#' # penicillins() would select benzylpenicillin ('peni G') and
#' # administrable_per_os() would select erythromycin. Yet, when combined these
#' # drugs are both omitted since benzylpenicillin is not administrable per os
#' # and erythromycin is not a penicillin:
-#' example_isolates[, penicillins() & administrable_per_os()]
+#' df[, penicillins() & administrable_per_os()]
#'
#' # ab_selector() applies a filter in the `antibiotics` data set and is thus very
#' # flexible. For instance, to select antibiotic columns with an oral DDD of at
#' # least 1 gram:
-#' example_isolates[, ab_selector(oral_ddd > 1 & oral_units == "g")]
+#' df[, ab_selector(oral_ddd > 1 & oral_units == "g")]
#'
#' # dplyr -------------------------------------------------------------------
#' \donttest{
#' if (require("dplyr")) {
#'
#' # get AMR for all aminoglycosides e.g., per hospital:
-#' example_isolates %>%
+#' df %>%
#' group_by(hospital_id) %>%
#' summarise(across(aminoglycosides(), resistance))
#'
#' # You can combine selectors with '&' to be more specific:
-#' example_isolates %>%
+#' df %>%
#' select(penicillins() & administrable_per_os())
#'
#' # get AMR for only drugs that matter - no intrinsic resistance:
-#' example_isolates %>%
+#' df %>%
#' filter(mo_genus() %in% c("Escherichia", "Klebsiella")) %>%
#' group_by(hospital_id) %>%
#' summarise(across(not_intrinsic_resistant(), resistance))
#'
#' # get susceptibility for antibiotics whose name contains "trim":
-#' example_isolates %>%
+#' df %>%
#' filter(first_isolate()) %>%
#' group_by(hospital_id) %>%
#' summarise(across(ab_selector(name %like% "trim"), susceptibility))
#'
#' # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
-#' example_isolates %>%
+#' df %>%
#' select(carbapenems())
#'
#' # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
-#' example_isolates %>%
+#' df %>%
#' select(mo, aminoglycosides())
#'
#' # any() and all() work in dplyr's filter() too:
-#' example_isolates %>%
+#' df %>%
#' filter(any(aminoglycosides() == "R"),
#' all(cephalosporins_2nd() == "R"))
#'
#' # also works with c():
-#' example_isolates %>%
+#' df %>%
#' filter(any(c(carbapenems(), aminoglycosides()) == "R"))
#'
#' # not setting any/all will automatically apply all():
-#' example_isolates %>%
+#' df %>%
#' filter(aminoglycosides() == "R")
-#' #> i Assuming a filter on all 4 aminoglycosides.
#'
#' # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
-#' example_isolates %>%
+#' df %>%
#' select(mo, ab_class("mycobact"))
#'
-#' # get bug/drug combinations for only macrolides in Gram-positives:
-#' example_isolates %>%
+#' # get bug/drug combinations for only glycopeptides in Gram-positives:
+#' df %>%
#' filter(mo_is_gram_positive()) %>%
-#' select(mo, macrolides()) %>%
+#' select(mo, glycopeptides()) %>%
#' bug_drug_combinations() %>%
#' format()
#'
@@ -151,10 +152,12 @@
#' select(penicillins()) # only the 'J01CA01' column will be selected
#'
#'
-#' # with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal:
-#' example_isolates[carbapenems() == "R", ]
-#' example_isolates %>% filter(carbapenems() == "R")
-#' example_isolates %>% filter(across(carbapenems(), ~.x == "R"))
+#' # with recent versions of dplyr this is all equal:
+#' x <- df[carbapenems() == "R", ]
+#' y <- df %>% filter(carbapenems() == "R")
+#' z <- df %>% filter(if_all(carbapenems(), ~.x == "R"))
+#' identical(x, y)
+#' identical(y, z)
#' }
#' }
ab_class <- function(ab_class,
diff --git a/R/age.R b/R/age.R
index ce8cd1a6f..e9bfb424f 100755
--- a/R/age.R
+++ b/R/age.R
@@ -25,8 +25,7 @@
#' Age in Years of Individuals
#'
-#' Calculates age in years based on a reference date, which is the sytem date at default.
-#' @inheritSection lifecycle Stable Lifecycle
+#' Calculates age in years based on a reference date, which is the system date at default.
#' @param x date(s), [character] (vectors) will be coerced with [as.POSIXlt()]
#' @param reference reference date(s) (defaults to today), [character] (vectors) will be coerced with [as.POSIXlt()]
#' @param exact a [logical] to indicate whether age calculation should be exact, i.e. with decimals. It divides the number of days of [year-to-date](https://en.wikipedia.org/wiki/Year-to-date) (YTD) of `x` by the number of days in the year of `reference` (either 365 or 366).
@@ -37,15 +36,19 @@
#' This function vectorises over both `x` and `reference`, meaning that either can have a length of 1 while the other argument has a larger length.
#' @return An [integer] (no decimals) if `exact = FALSE`, a [double] (with decimals) otherwise
#' @seealso To split ages into groups, use the [age_groups()] function.
-#' @inheritSection AMR Read more on Our Website!
#' @export
#' @examples
-#' # 10 random birth dates
-#' df <- data.frame(birth_date = Sys.Date() - runif(10) * 25000)
+#' # 10 random pre-Y2K birth dates
+#' df <- data.frame(birth_date = as.Date("2000-01-01") - runif(10) * 25000)
+#'
#' # add ages
#' df$age <- age(df$birth_date)
+#'
#' # add exact ages
#' df$age_exact <- age(df$birth_date, exact = TRUE)
+#'
+#' # add age at millenium switch
+#' df$age_at_y2k <- age(df$birth_date, "2000-01-01")
#'
#' df
age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
@@ -115,7 +118,6 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
#' Split Ages into Age Groups
#'
#' Split ages into age groups defined by the `split` argument. This allows for easier demographic (antimicrobial resistance) analysis.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x age, e.g. calculated with [age()]
#' @param split_at values to split `x` at, defaults to age groups 0-11, 12-24, 25-54, 55-74 and 75+. See *Details*.
#' @param na.rm a [logical] to indicate whether missing values should be removed
@@ -131,7 +133,7 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
#' @return Ordered [factor]
#' @seealso To determine ages, based on one or more reference dates, use the [age()] function.
#' @export
-#' @inheritSection AMR Read more on Our Website!
+
#' @examples
#' ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)
#'
@@ -150,7 +152,7 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
#' age_groups(ages, split_at = "fives")
#'
#' # split specifically for children
-#' age_groups(ages, c(1, 2, 4, 6, 13, 17))
+#' age_groups(ages, c(1, 2, 4, 6, 13, 18))
#' age_groups(ages, "children")
#'
#' \donttest{
@@ -161,7 +163,10 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
#' filter(mo == as.mo("E. coli")) %>%
#' group_by(age_group = age_groups(age)) %>%
#' select(age_group, CIP) %>%
-#' ggplot_rsi(x = "age_group", minimum = 0)
+#' ggplot_rsi(x = "age_group",
+#' minimum = 0,
+#' x.title = "Age Group",
+#' title = "Ciprofloxacin resistance per age group")
#' }
#' }
age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
diff --git a/R/atc_online.R b/R/atc_online.R
index e144dadf0..7be614db8 100644
--- a/R/atc_online.R
+++ b/R/atc_online.R
@@ -26,7 +26,6 @@
#' Get ATC Properties from WHOCC Website
#'
#' Gets data from the WHOCC website to determine properties of an Anatomical Therapeutic Chemical (ATC) (e.g. an antibiotic), such as the name, defined daily dose (DDD) or standard unit.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param atc_code a [character] (vector) with ATC code(s) of antibiotics, will be coerced with [as.ab()] and [ab_atc()] internally if not a valid ATC code
#' @param property property of an ATC code. Valid values are `"ATC"`, `"Name"`, `"DDD"`, `"U"` (`"unit"`), `"Adm.R"`, `"Note"` and `groups`. For this last option, all hierarchical groups of an ATC code will be returned, see *Examples*.
#' @param administration type of administration when using `property = "Adm.R"`, see *Details*
@@ -61,7 +60,6 @@
#' **N.B. This function requires an internet connection and only works if the following packages are installed: `curl`, `rvest`, `xml2`.**
#' @export
#' @rdname atc_online
-#' @inheritSection AMR Read more on Our Website!
#' @source <https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/>
#' @examples
#' \donttest{
diff --git a/R/availability.R b/R/availability.R
index 8f26ae7b2..f4c567911 100644
--- a/R/availability.R
+++ b/R/availability.R
@@ -26,12 +26,10 @@
#' Check Availability of Columns
#'
#' Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. [susceptibility()] and [resistance()].
-#' @inheritSection lifecycle Stable Lifecycle
#' @param tbl a [data.frame] or [list]
#' @param width number of characters to present the visual availability, defaults to filling the width of the console
#' @details The function returns a [data.frame] with columns `"resistant"` and `"visual_resistance"`. The values in that columns are calculated with [resistance()].
#' @return [data.frame] with column names of `tbl` as row names
-#' @inheritSection AMR Read more on Our Website!
#' @export
#' @examples
#' availability(example_isolates)
diff --git a/R/bug_drug_combinations.R b/R/bug_drug_combinations.R
index 4c8774f27..fa049b516 100644
--- a/R/bug_drug_combinations.R
+++ b/R/bug_drug_combinations.R
@@ -26,7 +26,6 @@
#' Determine Bug-Drug Combinations
#'
#' Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use [format()] on the result to prettify it to a publishable/printable format, see *Examples*.
-#' @inheritSection lifecycle Stable Lifecycle
#' @inheritParams eucast_rules
#' @param combine_IR a [logical] to indicate whether values R and I should be summed
#' @param add_ab_group a [logical] to indicate where the group of the antimicrobials must be included as a first column
@@ -41,11 +40,10 @@
#' @rdname bug_drug_combinations
#' @return The function [bug_drug_combinations()] returns a [data.frame] with columns "mo", "ab", "S", "I", "R" and "total".
#' @source \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, *Clinical and Laboratory Standards Institute (CLSI)*. <https://clsi.org/standards/products/microbiology/documents/m39/>.
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' \donttest{
#' x <- bug_drug_combinations(example_isolates)
-#' x
+#' head(x)
#' format(x, translate_ab = "name (atc)")
#'
#' # Use FUN to change to transformation of microorganism codes
diff --git a/R/catalogue_of_life.R b/R/catalogue_of_life.R
index f2c035c92..c7b348b31 100755
--- a/R/catalogue_of_life.R
+++ b/R/catalogue_of_life.R
@@ -59,7 +59,6 @@ format_included_data_number <- function(data) {
#' The Catalogue of Life (<http://www.catalogueoflife.org>) is the most comprehensive and authoritative global index of species currently available. It holds essential information on the names, relationships and distributions of over 1.9 million species. The Catalogue of Life is used to support the major biodiversity and conservation information services such as the Global Biodiversity Information Facility (GBIF), Encyclopedia of Life (EoL) and the International Union for Conservation of Nature Red List. It is recognised by the Convention on Biological Diversity as a significant component of the Global Taxonomy Initiative and a contribution to Target 1 of the Global Strategy for Plant Conservation.
#'
#' The syntax used to transform the original data to a cleansed \R format, can be found here: <https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R>.
-#' @inheritSection AMR Read more on Our Website!
#' @name catalogue_of_life
#' @rdname catalogue_of_life
#' @seealso Data set [microorganisms] for the actual data. \cr
@@ -71,28 +70,19 @@ format_included_data_number <- function(data) {
#'
#' # Get a note when a species was renamed
#' mo_shortname("Chlamydophila psittaci")
-#' # Note: 'Chlamydophila psittaci' (Everett et al., 1999) was renamed back to
-#' # 'Chlamydia psittaci' (Page, 1968)
-#' #> [1] "C. psittaci"
#'
#' # Get any property from the entire taxonomic tree for all included species
#' mo_class("E. coli")
-#' #> [1] "Gammaproteobacteria"
#'
#' mo_family("E. coli")
-#' #> [1] "Enterobacteriaceae"
#'
#' mo_gramstain("E. coli") # based on kingdom and phylum, see ?mo_gramstain
-#' #> [1] "Gram-negative"
#'
#' mo_ref("E. coli")
-#' #> [1] "Castellani et al., 1919"
#'
#' # Do not get mistaken - this package is about microorganisms
#' mo_kingdom("C. elegans")
-#' #> [1] "Fungi" # Fungi?!
#' mo_name("C. elegans")
-#' #> [1] "Cladosporium elegans" # Because a microorganism was found
NULL
#' Version info of included Catalogue of Life
@@ -102,7 +92,6 @@ NULL
#' @details For LPSN, see [microorganisms].
#' @return a [list], which prints in pretty format
#' @inheritSection catalogue_of_life Catalogue of Life
-#' @inheritSection AMR Read more on Our Website!
#' @export
catalogue_of_life_version <- function() {
diff --git a/R/count.R b/R/count.R
index 02f76b411..6f9051df0 100755
--- a/R/count.R
+++ b/R/count.R
@@ -28,7 +28,6 @@
#' @description These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, see *Examples*.
#'
#' [count_resistant()] should be used to count resistant isolates, [count_susceptible()] should be used to count susceptible isolates.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.rsi()] if needed.
#' @inheritParams proportion
#' @inheritSection as.rsi Interpretation of R and S/I
@@ -45,11 +44,11 @@
#' @rdname count
#' @name count
#' @export
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # example_isolates is a data set available in the AMR package.
-#' ?example_isolates
+#' # run ?example_isolates for more info.
#'
+#' # base R ------------------------------------------------------------
#' count_resistant(example_isolates$AMX) # counts "R"
#' count_susceptible(example_isolates$AMX) # counts "S" and "I"
#' count_all(example_isolates$AMX) # counts "S", "I" and "R"
@@ -72,6 +71,7 @@
#' count_susceptible(example_isolates$AMX)
#' susceptibility(example_isolates$AMX) * n_rsi(example_isolates$AMX)
#'
+#' # dplyr -------------------------------------------------------------
#' \donttest{
#' if (require("dplyr")) {
#' example_isolates %>%
diff --git a/R/custom_eucast_rules.R b/R/custom_eucast_rules.R
index 73e2bf4c9..9d37c107b 100644
--- a/R/custom_eucast_rules.R
+++ b/R/custom_eucast_rules.R
@@ -26,82 +26,67 @@
#' Define Custom EUCAST Rules
#'
#' Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in [eucast_rules()].
-#' @inheritSection lifecycle Stable Lifecycle
#' @param ... rules in [formula][`~`()] notation, see *Examples*
#' @details
#' Some organisations have their own adoption of EUCAST rules. This function can be used to define custom EUCAST rules to be used in the [eucast_rules()] function.
-#'
#' @section How it works:
#'
#' ### Basics
#'
#' If you are familiar with the [`case_when()`][dplyr::case_when()] function of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written *before* the tilde (`~`) and the consequence of the rule is written *after* the tilde:
#'
-#' ```
+#' ```{r}
#' x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
#' TZP == "R" ~ aminopenicillins == "R")
#' ```
#'
#' These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:
#'
-#' ```
+#' ```{r}
#' x
-#' #> A set of custom EUCAST rules:
-#' #>
-#' #> 1. If TZP is S then set to S:
-#' #> amoxicillin (AMX), ampicillin (AMP)
-#' #>
-#' #> 2. If TZP is R then set to R:
-#' #> amoxicillin (AMX), ampicillin (AMP)
#' ```
#'
#' The rules (the part *before* the tilde, in above example `TZP == "S"` and `TZP == "R"`) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column `TZP` must exist. We will create a sample data set and test the rules set:
#'
-#' ```
-#' df <- data.frame(mo = c("E. coli", "K. pneumoniae"),
-#' TZP = "R",
-#' amox = "",
-#' AMP = "")
+#' ```{r}
+#' df <- data.frame(mo = c("Escherichia coli", "Klebsiella pneumoniae"),
+#' TZP = as.rsi("R"),
+#' ampi = as.rsi("S"),
+#' cipro = as.rsi("S"))
#' df
-#' #> mo TZP amox AMP
-#' #> 1 E. coli R
-#' #> 2 K. pneumoniae R
-#'
-#' eucast_rules(df, rules = "custom", custom_rules = x)
-#' #> mo TZP amox AMP
-#' #> 1 E. coli R R R
-#' #> 2 K. pneumoniae R R R
+#'
+#' eucast_rules(df, rules = "custom", custom_rules = x, info = FALSE)
#' ```
#'
#' ### Using taxonomic properties in rules
#'
-#' There is one exception in variables used for the rules: all column names of the [microorganisms] data set can also be used, but do not have to exist in the data set. These column names are: `r vector_and(colnames(microorganisms), quote = "\u0096", sort = FALSE)`. Thus, this next example will work as well, despite the fact that the `df` data set does not contain a column `genus`:
+#' There is one exception in variables used for the rules: all column names of the [microorganisms] data set can also be used, but do not have to exist in the data set. These column names are: `r vector_and(colnames(microorganisms), sort = FALSE)`. Thus, this next example will work as well, despite the fact that the `df` data set does not contain a column `genus`:
#'
-#' ```
+#' ```{r}
#' y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
#' TZP == "R" & genus == "Klebsiella" ~ aminopenicillins == "R")
#'
-#' eucast_rules(df, rules = "custom", custom_rules = y)
-#' #> mo TZP amox AMP
-#' #> 1 E. coli R
-#' #> 2 K. pneumoniae R R R
+#' eucast_rules(df, rules = "custom", custom_rules = y, info = FALSE)
#' ```
#'
#' ### Usage of antibiotic group names
#'
#' It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part *after* the tilde. In above examples, the antibiotic group `aminopenicillins` is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the agents that will be matched when running the rule.
#'
-#' `r paste0(" * ", sapply(DEFINED_AB_GROUPS, function(x) paste0("\u0096", tolower(gsub("^AB_", "", x)), "\u0096\\cr(", vector_and(ab_name(eval(parse(text = x), envir = asNamespace("AMR")), language = NULL, tolower = TRUE), quotes = FALSE), ")"), USE.NAMES = FALSE), "\n", collapse = "")`
+#' `r paste0(" * ", sapply(DEFINED_AB_GROUPS, function(x) paste0("\"", tolower(gsub("^AB_", "", x)), "\"\\cr(", vector_and(ab_name(eval(parse(text = x), envir = asNamespace("AMR")), language = NULL, tolower = TRUE), quotes = FALSE), ")"), USE.NAMES = FALSE), "\n", collapse = "")`
#' @returns A [list] containing the custom rules
-#' @inheritSection AMR Read more on Our Website!
#' @export
#' @examples
#' x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
#' AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+#' x
+#'
+#' # run the custom rule set (verbose = TRUE will return a logbook instead of the data set):
#' eucast_rules(example_isolates,
#' rules = "custom",
#' custom_rules = x,
-#' info = FALSE)
+#' info = FALSE,
+#' verbose = TRUE)
#'
#' # combine rule sets
#' x2 <- c(x,
diff --git a/R/data.R b/R/data.R
index f350b7f9b..22911ba28 100755
--- a/R/data.R
+++ b/R/data.R
@@ -72,8 +72,10 @@
#' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>
#' @inheritSection AMR Reference Data Publicly Available
#' @inheritSection WHOCC WHOCC
-#' @inheritSection AMR Read more on Our Website!
#' @seealso [microorganisms], [intrinsic_resistant]
+#' @examples
+#' head(antibiotics)
+#' head(antivirals)
"antibiotics"
#' @rdname antibiotics
@@ -136,8 +138,9 @@
#'
#' * Retrieved from the `r SNOMED_VERSION$title`, OID `r SNOMED_VERSION$current_oid`, version `r SNOMED_VERSION$current_version`; url: <`r SNOMED_VERSION$url`>
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @seealso [as.mo()], [mo_property()], [microorganisms.codes], [intrinsic_resistant]
+#' @examples
+#' head(microorganisms)
"microorganisms"
#' Data Set with Previously Accepted Taxonomic Names
@@ -153,8 +156,9 @@
#'
#' Parte, A.C. (2018). LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; \doi{10.1099/ijsem.0.002786}
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @seealso [as.mo()] [mo_property()] [microorganisms]
+#' @examples
+#' head(microorganisms.old)
"microorganisms.old"
#' Data Set with `r format(nrow(microorganisms.codes), big.mark = ",")` Common Microorganism Codes
@@ -165,8 +169,9 @@
#' - `mo`\cr ID of the microorganism in the [microorganisms] data set
#' @inheritSection AMR Reference Data Publicly Available
#' @inheritSection catalogue_of_life Catalogue of Life
-#' @inheritSection AMR Read more on Our Website!
#' @seealso [as.mo()] [microorganisms]
+#' @examples
+#' head(microorganisms.codes)
"microorganisms.codes"
#' Data Set with `r format(nrow(example_isolates), big.mark = ",")` Example Isolates
@@ -184,7 +189,8 @@
#' - `mo`\cr ID of microorganism created with [as.mo()], see also [microorganisms]
#' - `PEN:RIF`\cr `r sum(vapply(FUN.VALUE = logical(1), example_isolates, is.rsi))` different antibiotics with class [`rsi`] (see [as.rsi()]); these column names occur in the [antibiotics] data set and can be translated with [ab_name()]
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#' @examples
+#' head(example_isolates)
"example_isolates"
#' Data Set with Unclean Data
@@ -197,7 +203,8 @@
#' - `bacteria`\cr info about microorganism that can be transformed with [as.mo()], see also [microorganisms]
#' - `AMX:GEN`\cr 4 different antibiotics that have to be transformed with [as.rsi()]
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#' @examples
+#' head(example_isolates_unclean)
"example_isolates_unclean"
#' Data Set with `r format(nrow(WHONET), big.mark = ",")` Isolates - WHONET Example
@@ -231,7 +238,8 @@
#' - `Date of data entry`\cr [Date] this data was entered in WHONET
#' - `AMP_ND10:CIP_EE`\cr `r sum(vapply(FUN.VALUE = logical(1), WHONET, is.rsi))` different antibiotics. You can lookup the abbreviations in the [antibiotics] data set, or use e.g. [`ab_name("AMP")`][ab_name()] to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using [as.rsi()].
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#' @examples
+#' head(WHONET)
"WHONET"
#' Data Set for R/SI Interpretation
@@ -250,16 +258,11 @@
#' - `breakpoint_R`\cr Highest MIC value or lowest number of millimetres that leads to "R"
#' - `uti`\cr A [logical] value (`TRUE`/`FALSE`) to indicate whether the rule applies to a urinary tract infection (UTI)
#' @details
-#' Overview of the data set:
-#'
-#' ```{r}
-#' head(rsi_translation)
-#' ```
-#'
#' The repository of this `AMR` package contains a file comprising this exact data set: <https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt>. This file **allows for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically and the `mo` and `ab` columns have been transformed to contain the full official names instead of codes.
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @seealso [intrinsic_resistant]
+#' @examples
+#' head(rsi_translation)
"rsi_translation"
#' Data Set with Bacterial Intrinsic Resistance
@@ -272,18 +275,8 @@
#'
#' This data set is based on `r format_eucast_version_nr(3.3)`.
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @examples
-#' \donttest{
-#' if (require("dplyr")) {
-#' intrinsic_resistant %>%
-#' mutate(mo = mo_name(mo),
-#' ab = ab_name(mo))
-#' filter(ab == "Vancomycin" & mo %like% "Enterococcus") %>%
-#' pull(mo)
-#' #> [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"
-#' }
-#' }
+#' head(intrinsic_resistant)
"intrinsic_resistant"
#' Data Set with Treatment Dosages as Defined by EUCAST
@@ -301,5 +294,6 @@
#' - `eucast_version`\cr Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply
#' @details `r format_eucast_version_nr(11.0)` are based on the dosages in this data set.
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#' @examples
+#' head(dosage)
"dosage"
diff --git a/R/deprecated.R b/R/deprecated.R
index b8d065d96..fbb6dbacb 100755
--- a/R/deprecated.R
+++ b/R/deprecated.R
@@ -26,8 +26,6 @@
#' Deprecated Functions
#'
#' These functions are so-called '[Deprecated]'. **They will be removed in a future release.** Using the functions will give a warning with the name of the function it has been replaced by (if there is one).
-#' @inheritSection lifecycle Retired Lifecycle
-#' @inheritSection AMR Read more on Our Website!
#' @keywords internal
#' @name AMR-deprecated
# @export
diff --git a/R/disk.R b/R/disk.R
index d8737f853..7a6a2c816 100644
--- a/R/disk.R
+++ b/R/disk.R
@@ -26,7 +26,6 @@
#' Transform Input to Disk Diffusion Diameters
#'
#' This transforms a vector to a new class [`disk`], which is a disk diffusion growth zone size (around an antibiotic disk) in millimetres between 6 and 50.
-#' @inheritSection lifecycle Stable Lifecycle
#' @rdname as.disk
#' @param x vector
#' @param na.rm a [logical] indicating whether missing values should be removed
@@ -35,27 +34,31 @@
#' @aliases disk
#' @export
#' @seealso [as.rsi()]
-#' @inheritSection AMR Read more on Our Website!
#' @examples
-#' \donttest{
-#' # transform existing disk zones to the `disk` class
-#' df <- data.frame(microorganism = "E. coli",
+#' # transform existing disk zones to the `disk` class (using base R)
+#' df <- data.frame(microorganism = "Escherichia coli",
#' AMP = 20,
#' CIP = 14,
#' GEN = 18,
#' TOB = 16)
#' df[, 2:5] <- lapply(df[, 2:5], as.disk)
-#' # same with dplyr:
-#' # df %>% mutate(across(AMP:TOB, as.disk))
+#' str(df)
+#'
+#' #' \donttest{
+#' # transforming is easier with dplyr:
+#' if (require("dplyr")) {
+#' df %>% mutate(across(AMP:TOB, as.disk))
+#' }
+#' }
#'
#' # interpret disk values, see ?as.rsi
#' as.rsi(x = as.disk(18),
#' mo = "Strep pneu", # `mo` will be coerced with as.mo()
#' ab = "ampicillin", # and `ab` with as.ab()
#' guideline = "EUCAST")
-#'
-#' as.rsi(df)
-#' }
+#'
+#' # interpret whole data set, pretend to be all from urinary tract infections:
+#' as.rsi(df, uti = TRUE)
as.disk <- function(x, na.rm = FALSE) {
meet_criteria(x, allow_class = c("disk", "character", "numeric", "integer"), allow_NA = TRUE)
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
diff --git a/R/episode.R b/R/episode.R
index 5089c32c8..1e524cf03 100644
--- a/R/episode.R
+++ b/R/episode.R
@@ -26,7 +26,6 @@
#' Determine (New) Episodes for Patients
#'
#' These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument `episode_days`. This can be used to determine clinical episodes for any epidemiological analysis. The [get_episode()] function returns the index number of the episode per group, while the [is_new_episode()] function returns values `TRUE`/`FALSE` to indicate whether an item in a vector is the start of a new episode.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x vector of dates (class `Date` or `POSIXt`), will be sorted internally to determine episodes
#' @param episode_days required episode length in days, can also be less than a day or `Inf`, see *Details*
#' @param ... ignored, only in place to allow future extensions
@@ -42,16 +41,16 @@
#' @seealso [first_isolate()]
#' @rdname get_episode
#' @export
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # `example_isolates` is a data set available in the AMR package.
-#' # See ?example_isolates.
+#' # See ?example_isolates
+#' df <- example_isolates[sample(seq_len(2000), size = 200), ]
#'
-#' get_episode(example_isolates$date, episode_days = 60) # indices
-#' is_new_episode(example_isolates$date, episode_days = 60) # TRUE/FALSE
+#' get_episode(df$date, episode_days = 60) # indices
+#' is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
#'
#' # filter on results from the third 60-day episode only, using base R
-#' example_isolates[which(get_episode(example_isolates$date, 60) == 3), ]
+#' df[which(get_episode(df$date, 60) == 3), ]
#'
#' # the functions also work for less than a day, e.g. to include one per hour:
#' get_episode(c(Sys.time(),
@@ -62,24 +61,24 @@
#' if (require("dplyr")) {
#' # is_new_episode() can also be used in dplyr verbs to determine patient
#' # episodes based on any (combination of) grouping variables:
-#' example_isolates %>%
+#' df %>%
#' mutate(condition = sample(x = c("A", "B", "C"),
#' size = 2000,
#' replace = TRUE)) %>%
#' group_by(condition) %>%
-#' mutate(new_episode = is_new_episode(date, 365))
+#' mutate(new_episode = is_new_episode(date, 365)) %>%
+#' select(patient_id, date, condition, new_episode)
#'
-#' example_isolates %>%
+#' df %>%
#' group_by(hospital_id, patient_id) %>%
#' transmute(date,
#' patient_id,
#' new_index = get_episode(date, 60),
#' new_logical = is_new_episode(date, 60))
#'
-#'
-#' example_isolates %>%
+#' df %>%
#' group_by(hospital_id) %>%
-#' summarise(patients = n_distinct(patient_id),
+#' summarise(n_patients = n_distinct(patient_id),
#' n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),
#' n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),
#' n_episodes_30 = sum(is_new_episode(date, episode_days = 30)))
@@ -87,21 +86,23 @@
#'
#' # grouping on patients and microorganisms leads to the same
#' # results as first_isolate() when using 'episode-based':
-#' x <- example_isolates %>%
+#' x <- df %>%
#' filter_first_isolate(include_unknown = TRUE,
#' method = "episode-based")
#'
-#' y <- example_isolates %>%
+#' y <- df %>%
#' group_by(patient_id, mo) %>%
-#' filter(is_new_episode(date, 365))
+#' filter(is_new_episode(date, 365)) %>%
+#' ungroup()
#'
-#' identical(x$patient_id, y$patient_id)
+#' identical(x, y)
#'
#' # but is_new_episode() has a lot more flexibility than first_isolate(),
#' # since you can now group on anything that seems relevant:
-#' example_isolates %>%
+#' df %>%
#' group_by(patient_id, mo, hospital_id, ward_icu) %>%
-#' mutate(flag_episode = is_new_episode(date, 365))
+#' mutate(flag_episode = is_new_episode(date, 365)) %>%
+#' select(group_vars(.), flag_episode)
#' }
#' }
get_episode <- function(x, episode_days, ...) {
diff --git a/R/eucast_rules.R b/R/eucast_rules.R
index a64eebf66..ea993a988 100755
--- a/R/eucast_rules.R
+++ b/R/eucast_rules.R
@@ -52,7 +52,6 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
#' Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, <https://eucast.org>), see *Source*. Use [eucast_dosage()] to get a [data.frame] with advised dosages of a certain bug-drug combination, which is based on the [dosage] data set.
#'
#' To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see *Details*.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x data with antibiotic columns, such as `amox`, `AMX` and `AMC`
#' @param info a [logical] to indicate whether progress should be printed to the console, defaults to only print while in interactive sessions
#' @param rules a [character] vector that specifies which rules should be applied. Must be one or more of `"breakpoints"`, `"expert"`, `"other"`, `"custom"`, `"all"`, and defaults to `c("breakpoints", "expert")`. The default value can be set to another value, e.g. using `options(AMR_eucastrules = "all")`. If using `"custom"`, be sure to fill in argument `custom_rules` too. Custom rules can be created with [custom_eucast_rules()].
@@ -76,11 +75,11 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
#'
#' Custom rules can be created using [custom_eucast_rules()], e.g.:
#'
-#' ```
+#' ```{r}
#' x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
#' AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
#'
-#' eucast_rules(example_isolates, rules = "custom", custom_rules = x)
+#' eucast_rules(example_isolates, rules = "custom", custom_rules = x, info = FALSE)
#' ```
#'
#'
@@ -113,8 +112,9 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
#' - EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_9.0_Breakpoint_Tables.xlsx)
#' - EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 10.0, 2020. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_10.0_Breakpoint_Tables.xlsx)
#' - EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 11.0, 2021. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_11.0_Breakpoint_Tables.xlsx)
+#' - EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 12.0, 2022. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_12.0_Breakpoint_Tables.xlsx)
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+
#' @examples
#' \donttest{
#' a <- data.frame(mo = c("Staphylococcus aureus",
@@ -131,33 +131,26 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
#' FOX = "S", # Cefoxitin
#' stringsAsFactors = FALSE)
#'
-#' a
-#' # mo VAN AMX COL CAZ CXM PEN FOX
-#' # 1 Staphylococcus aureus - - - - - S S
-#' # 2 Enterococcus faecalis - - - - - S S
-#' # 3 Escherichia coli - - - - - S S
-#' # 4 Klebsiella pneumoniae - - - - - S S
-#' # 5 Pseudomonas aeruginosa - - - - - S S
+#' head(a)
#'
#'
#' # apply EUCAST rules: some results wil be changed
#' b <- eucast_rules(a)
#'
-#' b
-#' # mo VAN AMX COL CAZ CXM PEN FOX
-#' # 1 Staphylococcus aureus - S R R S S S
-#' # 2 Enterococcus faecalis - - R R R S R
-#' # 3 Escherichia coli R - - - - R S
-#' # 4 Klebsiella pneumoniae R R - - - R S
-#' # 5 Pseudomonas aeruginosa R R - - R R R
+#' head(b)
#'
#'
#' # do not apply EUCAST rules, but rather get a data.frame
#' # containing all details about the transformations:
#' c <- eucast_rules(a, verbose = TRUE)
+#' head(c)
#' }
#'
+#' # Dosage guidelines:
+#'
#' eucast_dosage(c("tobra", "genta", "cipro"), "iv")
+#'
+#' eucast_dosage(c("tobra", "genta", "cipro"), "iv", version_breakpoints = 10)
eucast_rules <- function(x,
col_mo = NULL,
info = interactive(),
diff --git a/R/first_isolate.R b/R/first_isolate.R
index 1c44b68a1..2bd1a9749 100755
--- a/R/first_isolate.R
+++ b/R/first_isolate.R
@@ -26,7 +26,6 @@
#' Determine First Isolates
#'
#' Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler *et al.* in 2007 (\doi{10.1086/511864}). To determine patient episodes not necessarily based on microorganisms, use [is_new_episode()] that also supports grouping with the `dplyr` package.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [data.frame] containing isolates. Can be left blank for automatic determination, see *Examples*.
#' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column with a date class
#' @param col_patient_id column name of the unique IDs of the patients, defaults to the first column that starts with 'patient' or 'patid' (case insensitive)
@@ -126,7 +125,6 @@
#' - **M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition**, 2014, *Clinical and Laboratory Standards Institute (CLSI)*. <https://clsi.org/standards/products/microbiology/documents/m39/>.
#'
#' - Hindler JF and Stelling J (2007). **Analysis and Presentation of Cumulative Antibiograms: A New Consensus Guideline from the Clinical and Laboratory Standards Institute.** Clinical Infectious Diseases, 44(6), 867-873. \doi{10.1086/511864}
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # `example_isolates` is a data set available in the AMR package.
#' # See ?example_isolates.
@@ -134,7 +132,7 @@
#' example_isolates[first_isolate(), ]
#' \donttest{
#' # get all first Gram-negatives
-#' example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
+#' example_isolates[which(first_isolate(info = FALSE) & mo_is_gram_negative()), ]
#'
#' if (require("dplyr")) {
#' # filter on first isolates using dplyr:
@@ -143,12 +141,13 @@
#'
#' # short-hand version:
#' example_isolates %>%
-#' filter_first_isolate()
+#' filter_first_isolate(info = FALSE)
#'
-#' # grouped determination of first isolates (also prints group names):
+#' # flag the first isolates per group:
#' example_isolates %>%
#' group_by(hospital_id) %>%
-#' mutate(first = first_isolate())
+#' mutate(first = first_isolate()) %>%
+#' select(hospital_id, date, patient_id, mo, first)
#'
#' # now let's see if first isolates matter:
#' A <- example_isolates %>%
@@ -163,6 +162,9 @@
#' resistance = resistance(GEN)) # gentamicin resistance
#'
#' # Have a look at A and B.
+#' A
+#' B
+#'
#' # B is more reliable because every isolate is counted only once.
#' # Gentamicin resistance in hospital D appears to be 4.2% higher than
#' # when you (erroneously) would have used all isolates for analysis.
diff --git a/R/g.test.R b/R/g.test.R
index 61ad5201a..eb23c3d5e 100755
--- a/R/g.test.R
+++ b/R/g.test.R
@@ -26,7 +26,6 @@
#' *G*-test for Count Data
#'
#' [g.test()] performs chi-squared contingency table tests and goodness-of-fit tests, just like [chisq.test()] but is more reliable (1). A *G*-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a ***G*-test of goodness-of-fit**), or to see whether the proportions of one variable are different for different values of the other variable (called a ***G*-test of independence**).
-#' @inheritSection lifecycle Questioning Lifecycle
#' @inherit stats::chisq.test params return
#' @details If `x` is a [matrix] with one row or column, or if `x` is a vector and `y` is not given, then a *goodness-of-fit test* is performed (`x` is treated as a one-dimensional contingency table). The entries of `x` must be non-negative integers. In this case, the hypothesis tested is whether the population probabilities equal those in `p`, or are all equal if `p` is not given.
#'
@@ -76,7 +75,6 @@
#' - The possibility to simulate p values with `simulate.p.value` was removed
#' @export
#' @importFrom stats pchisq complete.cases
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # = EXAMPLE 1 =
#' # Shivrain et al. (2006) crossed clearfield rice (which are resistant
@@ -88,8 +86,7 @@
#' # ratio.
#'
#' x <- c(772, 1611, 737)
-#' G <- g.test(x, p = c(1, 2, 1) / 4)
-#' # G$p.value = 0.12574.
+#' g.test(x, p = c(1, 2, 1) / 4)
#'
#' # There is no significant difference from a 1:2:1 ratio.
#' # Meaning: resistance controlled by a single gene with two co-dominant
@@ -105,11 +102,9 @@
#'
#' x <- c(1752, 1895)
#' g.test(x)
-#' # p = 0.01787343
#'
#' # There is a significant difference from a 1:1 ratio.
#' # Meaning: there are significantly more left-billed birds.
-#'
g.test <- function(x,
y = NULL,
# correct = TRUE,
diff --git a/R/ggplot_pca.R b/R/ggplot_pca.R
index 1854e97b1..e7b00172a 100755
--- a/R/ggplot_pca.R
+++ b/R/ggplot_pca.R
@@ -26,7 +26,6 @@
#' PCA Biplot with `ggplot2`
#'
#' Produces a `ggplot2` variant of a so-called [biplot](https://en.wikipedia.org/wiki/Biplot) for PCA (principal component analysis), but is more flexible and more appealing than the base \R [biplot()] function.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x an object returned by [pca()], [prcomp()] or [princomp()]
#' @inheritParams stats::biplot.prcomp
#' @param labels an optional vector of labels for the observations. If set, the labels will be placed below their respective points. When using the [pca()] function as input for `x`, this will be determined automatically based on the attribute `non_numeric_cols`, see [pca()].
@@ -64,23 +63,28 @@
#' # `example_isolates` is a data set available in the AMR package.
#' # See ?example_isolates.
#'
-#' # See ?pca for more info about Principal Component Analysis (PCA).
#' \donttest{
#' if (require("dplyr")) {
-#' pca_model <- example_isolates %>%
-#' filter(mo_genus(mo) == "Staphylococcus") %>%
-#' group_by(species = mo_shortname(mo)) %>%
-#' summarise_if (is.rsi, resistance) %>%
-#' pca(FLC, AMC, CXM, GEN, TOB, TMP, SXT, CIP, TEC, TCY, ERY)
+#' # calculate the resistance per group first
+#' resistance_data <- example_isolates %>%
+#' group_by(order = mo_order(mo), # group on anything, like order
+#' genus = mo_genus(mo)) %>% # and genus as we do here;
+#' filter(n() >= 30) %>% # filter on only 30 results per group
+#' summarise_if(is.rsi, resistance) # then get resistance of all drugs
#'
-#' # old (base R)
-#' biplot(pca_model)
+#' # now conduct PCA for certain antimicrobial agents
+#' pca_result <- resistance_data %>%
+#' pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)
+#'
+#' summary(pca_result)
#'
-#' # new
-#' ggplot_pca(pca_model)
+#' # old base R plotting method:
+#' biplot(pca_result)
+#' # new ggplot2 plotting method using this package:
+#' ggplot_pca(pca_result)
#'
#' if (require("ggplot2")) {
-#' ggplot_pca(pca_model) +
+#' ggplot_pca(pca_result) +
#' scale_colour_viridis_d() +
#' labs(title = "Title here")
#' }
diff --git a/R/ggplot_rsi.R b/R/ggplot_rsi.R
index 04fdf43c8..23abcb5d3 100755
--- a/R/ggplot_rsi.R
+++ b/R/ggplot_rsi.R
@@ -26,7 +26,6 @@
#' AMR Plots with `ggplot2`
#'
#' Use these functions to create bar plots for AMR data analysis. All functions rely on [ggplot2][ggplot2::ggplot()] functions.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param data a [data.frame] with column(s) of class [`rsi`] (see [as.rsi()])
#' @param position position adjustment of bars, either `"fill"`, `"stack"` or `"dodge"`
#' @param x variable to show on x axis, either `"antibiotic"` (default) or `"interpretation"` or a grouping variable
@@ -65,7 +64,6 @@
#' [ggplot_rsi()] is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (`%>%`). See *Examples*.
#' @rdname ggplot_rsi
#' @export
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' \donttest{
#' if (require("ggplot2") & require("dplyr")) {
diff --git a/R/guess_ab_col.R b/R/guess_ab_col.R
index ccfff75dd..efffb4bb7 100755
--- a/R/guess_ab_col.R
+++ b/R/guess_ab_col.R
@@ -26,7 +26,6 @@
#' Guess Antibiotic Column
#'
#' This tries to find a column name in a data set based on information from the [antibiotics] data set. Also supports WHONET abbreviations.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [data.frame]
#' @param search_string a text to search `x` for, will be checked with [as.ab()] if this value is not a column in `x`
#' @param verbose a [logical] to indicate whether additional info should be printed
@@ -34,7 +33,6 @@
#' @details You can look for an antibiotic (trade) name or abbreviation and it will search `x` and the [antibiotics] data set for any column containing a name or code of that antibiotic. **Longer columns names take precedence over shorter column names.**
#' @return A column name of `x`, or `NULL` when no result is found.
#' @export
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' df <- data.frame(amox = "S",
#' tetr = "R")
diff --git a/R/italicise_taxonomy.R b/R/italicise_taxonomy.R
index 1978303da..3dd76d76e 100644
--- a/R/italicise_taxonomy.R
+++ b/R/italicise_taxonomy.R
@@ -25,8 +25,7 @@
#' Italicise Taxonomic Families, Genera, Species, Subspecies
#'
-#' According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italic. This function finds taxonomic names within strings and makes them italic.
-#' @inheritSection lifecycle Stable Lifecycle
+#' According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italics. This function finds taxonomic names within strings and makes them italic.
#' @param string a [character] (vector)
#' @param type type of conversion of the taxonomic names, either "markdown" or "ansi", see *Details*
#' @details
@@ -35,23 +34,12 @@
#' The taxonomic names can be italicised using markdown (the default) by adding `*` before and after the taxonomic names, or using ANSI colours by adding `\033[3m` before and `\033[23m` after the taxonomic names. If multiple ANSI colours are not available, no conversion will occur.
#'
#' This function also supports abbreviation of the genus if it is followed by a species, such as "E. coli" and "K. pneumoniae ozaenae".
-#' @inheritSection AMR Read more on Our Website!
#' @export
#' @examples
#' italicise_taxonomy("An overview of Staphylococcus aureus isolates")
#' italicise_taxonomy("An overview of S. aureus isolates")
#'
#' cat(italicise_taxonomy("An overview of S. aureus isolates", type = "ansi"))
-#'
-#' # since ggplot2 supports no markdown (yet), use
-#' # italicise_taxonomy() and the `ggtext` package for titles:
-#' \donttest{
-#' if (require("ggplot2") && require("ggtext")) {
-#' autoplot(example_isolates$AMC,
-#' title = italicise_taxonomy("Amoxi/clav in E. coli")) +
-#' theme(plot.title = ggtext::element_markdown())
-#' }
-#' }
italicise_taxonomy <- function(string, type = c("markdown", "ansi")) {
if (missing(type)) {
type <- "markdown"
diff --git a/R/join_microorganisms.R b/R/join_microorganisms.R
index 34ea63f82..553d15842 100755
--- a/R/join_microorganisms.R
+++ b/R/join_microorganisms.R
@@ -26,7 +26,6 @@
#' Join [microorganisms] to a Data Set
#'
#' Join the data set [microorganisms] easily to an existing data set or to a [character] vector.
-#' @inheritSection lifecycle Stable Lifecycle
#' @rdname join
#' @name join
#' @aliases join inner_join
@@ -37,7 +36,6 @@
#' @details **Note:** As opposed to the `join()` functions of `dplyr`, [character] vectors are supported and at default existing columns will get a suffix `"2"` and the newly joined columns will not get a suffix.
#'
#' If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base \R will be used.
-#' @inheritSection AMR Read more on Our Website!
#' @return a [data.frame]
#' @export
#' @examples
diff --git a/R/key_antimicrobials.R b/R/key_antimicrobials.R
index e765e6add..c7d622b3f 100755
--- a/R/key_antimicrobials.R
+++ b/R/key_antimicrobials.R
@@ -26,7 +26,6 @@
#' (Key) Antimicrobials for First Weighted Isolates
#'
#' These functions can be used to determine first weighted isolates by considering the phenotype for isolate selection (see [first_isolate()]). Using a phenotype-based method to determine first isolates is more reliable than methods that disregard phenotypes.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank to determine automatically
#' @param y,z [character] vectors to compare
#' @inheritParams first_isolate
@@ -82,7 +81,6 @@
#' @rdname key_antimicrobials
#' @export
#' @seealso [first_isolate()]
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # `example_isolates` is a data set available in the AMR package.
#' # See ?example_isolates.
@@ -110,7 +108,7 @@
#' first_weighted = first_isolate(col_keyantimicrobials = "keyab")
#' )
#'
-#' # Check the difference, in this data set it results in more isolates:
+#' # Check the difference in this data set, 'weighted' results in more isolates:
#' sum(my_patients$first_regular, na.rm = TRUE)
#' sum(my_patients$first_weighted, na.rm = TRUE)
#' }
diff --git a/R/kurtosis.R b/R/kurtosis.R
index e6d72e2b8..87f49795c 100755
--- a/R/kurtosis.R
+++ b/R/kurtosis.R
@@ -26,14 +26,15 @@
#' Kurtosis of the Sample
#'
#' @description Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. A normal distribution has a kurtosis of 3 and a excess kurtosis of 0.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a vector of values, a [matrix] or a [data.frame]
#' @param na.rm a [logical] to indicate whether `NA` values should be stripped before the computation proceeds
#' @param excess a [logical] to indicate whether the *excess kurtosis* should be returned, defined as the kurtosis minus 3.
#' @seealso [skewness()]
#' @rdname kurtosis
-#' @inheritSection AMR Read more on Our Website!
#' @export
+#' @examples
+#' kurtosis(rnorm(10000))
+#' kurtosis(rnorm(10000), excess = TRUE)
kurtosis <- function(x, na.rm = FALSE, excess = FALSE) {
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
meet_criteria(excess, allow_class = "logical", has_length = 1)
diff --git a/R/lifecycle.R b/R/lifecycle.R
deleted file mode 100644
index 867992c5d..000000000
--- a/R/lifecycle.R
+++ /dev/null
@@ -1,54 +0,0 @@
-# ==================================================================== #
-# TITLE #
-# Antimicrobial Resistance (AMR) Data Analysis for R #
-# #
-# SOURCE #
-# https://github.com/msberends/AMR #
-# #
-# LICENCE #
-# (c) 2018-2022 Berends MS, Luz CF et al. #
-# Developed at the University of Groningen, the Netherlands, in #
-# collaboration with non-profit organisations Certe Medical #
-# Diagnostics & Advice, and University Medical Center Groningen. #
-# #
-# This R package is free software; you can freely use and distribute #
-# it for both personal and commercial purposes under the terms of the #
-# GNU General Public License version 2.0 (GNU GPL-2), as published by #
-# the Free Software Foundation. #
-# We created this package for both routine data analysis and academic #
-# research and it was publicly released in the hope that it will be #
-# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
-# #
-# Visit our website for the full manual and a complete tutorial about #
-# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
-# ==================================================================== #
-
-###############
-# NOTE TO SELF: could also have done this with the 'lifecycle' package, but why add a package dependency for such an easy job??
-###############
-
-#' Lifecycles of Functions in the `AMR` Package
-#' @name lifecycle
-#' @rdname lifecycle
-#' @description Functions in this `AMR` package are categorised using [the lifecycle circle of the Tidyverse as found on www.tidyverse.org/lifecycle](https://lifecycle.r-lib.org/articles/stages.html).
-#'
-#' \if{html}{\figure{lifecycle_tidyverse.svg}{options: height="200" style=margin-bottom:"5"} \cr}
-#' This page contains a section for every lifecycle (with text borrowed from the aforementioned Tidyverse website), so they can be used in the manual pages of the functions.
-#' @section Experimental Lifecycle:
-#' \if{html}{\figure{lifecycle_experimental.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **experimental**. An experimental function is in early stages of development. The unlying code might be changing frequently. Experimental functions might be removed without deprecation, so you are generally best off waiting until a function is more mature before you use it in production code. Experimental functions are only available in development versions of this `AMR` package and will thus not be included in releases that are submitted to CRAN, since such functions have not yet matured enough.
-#' @section Maturing Lifecycle:
-#' \if{html}{\figure{lifecycle_maturing.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **maturing**. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome [to suggest changes at our repository](https://github.com/msberends/AMR/issues) or [write us an email (see section 'Contact Us')][AMR::AMR].
-#' @section Stable Lifecycle:
-#' \if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **stable**. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-#'
-#' If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-#' @section Retired Lifecycle:
-#' \if{html}{\figure{lifecycle_retired.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **retired**. A retired function is no longer under active development, and (if appropiate) a better alternative is available. No new arguments will be added, and only the most critical bugs will be fixed. In a future version, this function will be removed.
-#' @section Questioning Lifecycle:
-#' \if{html}{\figure{lifecycle_questioning.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **questioning**. This function might be no longer be optimal approach, or is it questionable whether this function should be in this `AMR` package at all.
-NULL
diff --git a/R/like.R b/R/like.R
index e243a84a5..8029bfdd5 100755
--- a/R/like.R
+++ b/R/like.R
@@ -26,7 +26,6 @@
#' Vectorised Pattern Matching with Keyboard Shortcut
#'
#' Convenient wrapper around [grepl()] to match a pattern: `x %like% pattern`. It always returns a [`logical`] vector and is always case-insensitive (use `x %like_case% pattern` for case-sensitive matching). Also, `pattern` can be as long as `x` to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [character] vector where matches are sought, or an object which can be coerced by [as.character()] to a [character] vector.
#' @param pattern a [character] vector containing regular expressions (or a [character] string for `fixed = TRUE`) to be matched in the given [character] vector. Coerced by [as.character()] to a [character] string if possible.
#' @param ignore.case if `FALSE`, the pattern matching is *case sensitive* and if `TRUE`, case is ignored during matching.
@@ -44,27 +43,21 @@
#' Using RStudio? The `%like%`/`%unlike%` functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like `Shift+Ctrl+L` or `Shift+Cmd+L` (see menu `Tools` > `Modify Keyboard Shortcuts...`). If you keep pressing your shortcut, the inserted text will be iterated over `%like%` -> `%unlike%` -> `%like_case%` -> `%unlike_case%`.
#' @source Idea from the [`like` function from the `data.table` package](https://github.com/Rdatatable/data.table/blob/ec1259af1bf13fc0c96a1d3f9e84d55d8106a9a4/R/like.R), although altered as explained in *Details*.
#' @seealso [grepl()]
-#' @inheritSection AMR Read more on Our Website!
+
#' @examples
#' a <- "This is a test"
#' b <- "TEST"
#' a %like% b
-#' #> TRUE
#' b %like% a
-#' #> FALSE
#'
#' # also supports multiple patterns
#' a <- c("Test case", "Something different", "Yet another thing")
#' b <- c( "case", "diff", "yet")
#' a %like% b
-#' #> TRUE TRUE TRUE
#' a %unlike% b
-#' #> FALSE FALSE FALSE
#'
#' a[1] %like% b
-#' #> TRUE FALSE FALSE
#' a %like% b[1]
-#' #> TRUE FALSE FALSE
#'
#' # get isolates whose name start with 'Ent' or 'ent'
#' example_isolates[which(mo_name(example_isolates$mo) %like% "^ent"), ]
diff --git a/R/mdro.R b/R/mdro.R
index 7bf2e32e6..ad419d469 100755
--- a/R/mdro.R
+++ b/R/mdro.R
@@ -26,7 +26,6 @@
#' Determine Multidrug-Resistant Organisms (MDRO)
#'
#' Determine which isolates are multidrug-resistant organisms (MDRO) according to international, national and custom guidelines.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank for automatic determination.
#' @param guideline a specific guideline to follow, see sections *Supported international / national guidelines* and *Using Custom Guidelines* below. When left empty, the publication by Magiorakos *et al.* (see below) will be followed.
#' @param ... in case of [custom_mdro_guideline()]: a set of rules, see section *Using Custom Guidelines* below. Otherwise: column name of an antibiotic, see section *Antibiotics* below.
@@ -137,15 +136,17 @@
#' @rdname mdro
#' @aliases MDR XDR PDR BRMO 3MRGN 4MRGN
#' @export
-#' @inheritSection AMR Read more on Our Website!
#' @source
#' See the supported guidelines above for the [list] of publications used for this function.
#' @examples
-#' mdro(example_isolates, guideline = "EUCAST")
+#' out <- mdro(example_isolates, guideline = "EUCAST")
+#' str(out)
+#' table(out)
#'
-#' mdro(example_isolates,
-#' guideline = custom_mdro_guideline(AMX == "R" ~ "Custom MDRO 1",
-#' VAN == "R" ~ "Custom MDRO 2"))
+#' out <- mdro(example_isolates,
+#' guideline = custom_mdro_guideline(AMX == "R" ~ "Custom MDRO 1",
+#' VAN == "R" ~ "Custom MDRO 2"))
+#' table(out)
#'
#' \donttest{
#' if (require("dplyr")) {
@@ -155,10 +156,10 @@
#'
#' # no need to define `x` when used inside dplyr verbs:
#' example_isolates %>%
-#' mutate(MDRO = mdro(),
-#' EUCAST = eucast_exceptional_phenotypes(),
-#' BRMO = brmo(),
-#' MRGN = mrgn())
+#' mutate(MDRO = mdro()) %>%
+#' pull(MDRO) %>%
+#' table()
+#'
#' }
#' }
mdro <- function(x = NULL,
@@ -191,8 +192,10 @@ mdro <- function(x = NULL,
info.bak <- info
# don't thrown info's more than once per call
- info <- message_not_thrown_before("mdro")
-
+ if (isTRUE(info)) {
+ info <- message_not_thrown_before("mdro")
+ }
+
if (interactive() & verbose == TRUE & info == TRUE) {
txt <- paste0("WARNING: In Verbose mode, the mdro() function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.",
"\n\nThis may overwrite your existing data if you use e.g.:",
diff --git a/R/mic.R b/R/mic.R
index 65c6004b6..c629561f5 100755
--- a/R/mic.R
+++ b/R/mic.R
@@ -43,7 +43,6 @@ valid_mic_levels <- c(c(t(vapply(FUN.VALUE = character(9), ops,
#' Transform Input to Minimum Inhibitory Concentrations (MIC)
#'
#' This transforms vectors to a new class [`mic`], which treats the input as decimal numbers, while maintaining operators (such as ">=") and only allowing valid MIC values known to the field of (medical) microbiology.
-#' @inheritSection lifecycle Stable Lifecycle
#' @rdname as.mic
#' @param x a [character] or [numeric] vector
#' @param na.rm a [logical] indicating whether missing values should be removed
@@ -95,32 +94,35 @@ valid_mic_levels <- c(c(t(vapply(FUN.VALUE = character(9), ops,
#' @aliases mic
#' @export
#' @seealso [as.rsi()]
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
+#' mic_data
#' is.mic(mic_data)
#'
#' # this can also coerce combined MIC/RSI values:
-#' as.mic("<=0.002; S") # will return <=0.002
+#' as.mic("<=0.002; S")
#'
-#' # mathematical processing treats MICs as [numeric] values
+#' # mathematical processing treats MICs as numeric values
#' fivenum(mic_data)
#' quantile(mic_data)
#' all(mic_data < 512)
#'
#' # interpret MIC values
#' as.rsi(x = as.mic(2),
-#' mo = as.mo("S. pneumoniae"),
+#' mo = as.mo("Streptococcus pneumoniae"),
#' ab = "AMX",
#' guideline = "EUCAST")
-#' as.rsi(x = as.mic(4),
-#' mo = as.mo("S. pneumoniae"),
+#' as.rsi(x = as.mic(c(0.01, 2, 4, 8)),
+#' mo = as.mo("Streptococcus pneumoniae"),
#' ab = "AMX",
#' guideline = "EUCAST")
#'
#' # plot MIC values, see ?plot
#' plot(mic_data)
#' plot(mic_data, mo = "E. coli", ab = "cipro")
+#' autoplot(mic_data, mo = "E. coli", ab = "cipro")
+#' autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "nl") # Dutch
+#' autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "uk") # Ukrainian
as.mic <- function(x, na.rm = FALSE) {
meet_criteria(x, allow_class = c("mic", "character", "numeric", "integer", "factor"), allow_NA = TRUE)
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
diff --git a/R/mo.R b/R/mo.R
index 903d58ae0..db6fd454c 100755
--- a/R/mo.R
+++ b/R/mo.R
@@ -26,7 +26,6 @@
#' Transform Input to a Microorganism Code
#'
#' Use this function to determine a valid microorganism code ([`mo`]). Determination is done using intelligent rules and the complete taxonomic kingdoms Bacteria, Chromista, Protozoa, Archaea and most microbial species from the kingdom Fungi (see *Source*). The input can be almost anything: a full name (like `"Staphylococcus aureus"`), an abbreviated name (such as `"S. aureus"`), an abbreviation known in the field (such as `"MRSA"`), or just a genus. See *Examples*.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [character] vector or a [data.frame] with one or two columns
#' @param Becker a [logical] to indicate whether staphylococci should be categorised into coagulase-negative staphylococci ("CoNS") and coagulase-positive staphylococci ("CoPS") instead of their own species, according to Karsten Becker *et al.* (1,2,3).
#'
@@ -116,7 +115,6 @@
#'
#' The [`mo_*`][mo_property()] functions (such as [mo_genus()], [mo_gramstain()]) to get properties based on the returned code.
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' \donttest{
#' # These examples all return "B_STPHY_AURS", the ID of S. aureus:
diff --git a/R/mo_matching_score.R b/R/mo_matching_score.R
index 74fd84127..00bd5b6f2 100755
--- a/R/mo_matching_score.R
+++ b/R/mo_matching_score.R
@@ -26,7 +26,6 @@
#' Calculate the Matching Score for Microorganisms
#'
#' This algorithm is used by [as.mo()] and all the [`mo_*`][mo_property()] functions to determine the most probable match of taxonomic records based on user input.
-#' @inheritSection lifecycle Stable Lifecycle
#' @author Dr Matthijs Berends
#' @param x Any user input value(s)
#' @param n A full taxonomic name, that exists in [`microorganisms$fullname`][microorganisms]
@@ -53,7 +52,6 @@
#' Since `AMR` version 1.8.1, common microorganism abbreviations are ignored in determining the matching score. These abbreviations are currently: `r vector_and(pkg_env$mo_field_abbreviations, quotes = FALSE)`.
#' @export
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' as.mo("E. coli")
#' mo_uncertainties()
diff --git a/R/mo_property.R b/R/mo_property.R
index 5f8a0258f..abcd4ab42 100755
--- a/R/mo_property.R
+++ b/R/mo_property.R
@@ -26,7 +26,6 @@
#' Get Properties of a Microorganism
#'
#' Use these functions to return a specific property of a microorganism based on the latest accepted taxonomy. All input values will be evaluated internally with [as.mo()], which makes it possible to use microbial abbreviations, codes and names as input. See *Examples*.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x any [character] (vector) that can be coerced to a valid microorganism code with [as.mo()]. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, see *Examples*.
#' @param property one of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, quotes = TRUE)`, or must be `"shortname"`
#' @param language language of the returned text, defaults to system language (see [get_AMR_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Also used to translate text like "no growth". Use `language = NULL` or `language = ""` to prevent translation.
@@ -67,93 +66,91 @@
#' @export
#' @seealso Data set [microorganisms]
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # taxonomic tree -----------------------------------------------------------
-#' mo_kingdom("E. coli") # "Bacteria"
-#' mo_phylum("E. coli") # "Proteobacteria"
-#' mo_class("E. coli") # "Gammaproteobacteria"
-#' mo_order("E. coli") # "Enterobacterales"
-#' mo_family("E. coli") # "Enterobacteriaceae"
-#' mo_genus("E. coli") # "Escherichia"
-#' mo_species("E. coli") # "coli"
-#' mo_subspecies("E. coli") # ""
+#' mo_kingdom("Klebsiella pneumoniae")
+#' mo_phylum("Klebsiella pneumoniae")
+#' mo_class("Klebsiella pneumoniae")
+#' mo_order("Klebsiella pneumoniae")
+#' mo_family("Klebsiella pneumoniae")
+#' mo_genus("Klebsiella pneumoniae")
+#' mo_species("Klebsiella pneumoniae")
+#' mo_subspecies("Klebsiella pneumoniae")
#'
#' # colloquial properties ----------------------------------------------------
-#' mo_name("E. coli") # "Escherichia coli"
-#' mo_fullname("E. coli") # "Escherichia coli" - same as mo_name()
-#' mo_shortname("E. coli") # "E. coli"
+#' mo_name("Klebsiella pneumoniae")
+#' mo_fullname("Klebsiella pneumoniae")
+#' mo_shortname("Klebsiella pneumoniae")
#'
#' # other properties ---------------------------------------------------------
-#' mo_gramstain("E. coli") # "Gram-negative"
-#' mo_snomed("E. coli") # 112283007, 116395006, ... (SNOMED codes)
-#' mo_type("E. coli") # "Bacteria" (equal to kingdom, but may be translated)
-#' mo_rank("E. coli") # "species"
-#' mo_url("E. coli") # get the direct url to the online database entry
-#' mo_synonyms("E. coli") # get previously accepted taxonomic names
+#' mo_gramstain("Klebsiella pneumoniae")
+#' mo_snomed("Klebsiella pneumoniae")
+#' mo_type("Klebsiella pneumoniae")
+#' mo_rank("Klebsiella pneumoniae")
+#' mo_url("Klebsiella pneumoniae")
+#' mo_synonyms("Klebsiella pneumoniae")
#'
#' # scientific reference -----------------------------------------------------
-#' mo_ref("E. coli") # "Castellani et al., 1919"
-#' mo_authors("E. coli") # "Castellani et al."
-#' mo_year("E. coli") # 1919
-#' mo_lpsn("E. coli") # 776057 (LPSN record ID)
+#' mo_ref("Klebsiella pneumoniae")
+#' mo_authors("Klebsiella pneumoniae")
+#' mo_year("Klebsiella pneumoniae")
+#' mo_lpsn("Klebsiella pneumoniae")
#'
#' # abbreviations known in the field -----------------------------------------
-#' mo_genus("MRSA") # "Staphylococcus"
-#' mo_species("MRSA") # "aureus"
-#' mo_shortname("VISA") # "S. aureus"
-#' mo_gramstain("VISA") # "Gram-positive"
+#' mo_genus("MRSA")
+#' mo_species("MRSA")
+#' mo_shortname("VISA")
+#' mo_gramstain("VISA")
#'
-#' mo_genus("EHEC") # "Escherichia"
-#' mo_species("EHEC") # "coli"
+#' mo_genus("EHEC")
+#' mo_species("EHEC")
#'
#' # known subspecies ---------------------------------------------------------
-#' mo_name("doylei") # "Campylobacter jejuni doylei"
-#' mo_genus("doylei") # "Campylobacter"
-#' mo_species("doylei") # "jejuni"
-#' mo_subspecies("doylei") # "doylei"
+#' mo_name("doylei")
+#' mo_genus("doylei")
+#' mo_species("doylei")
+#' mo_subspecies("doylei")
#'
-#' mo_fullname("K. pneu rh") # "Klebsiella pneumoniae rhinoscleromatis"
-#' mo_shortname("K. pneu rh") # "K. pneumoniae"
+#' mo_fullname("K. pneu rh")
+#' mo_shortname("K. pneu rh")
#'
#' \donttest{
#' # Becker classification, see ?as.mo ----------------------------------------
-#' mo_fullname("S. epi") # "Staphylococcus epidermidis"
-#' mo_fullname("S. epi", Becker = TRUE) # "Coagulase-negative Staphylococcus (CoNS)"
-#' mo_shortname("S. epi") # "S. epidermidis"
-#' mo_shortname("S. epi", Becker = TRUE) # "CoNS"
+#' mo_fullname("S. epi")
+#' mo_fullname("S. epi", Becker = TRUE)
+#' mo_shortname("S. epi")
+#' mo_shortname("S. epi", Becker = TRUE)
#'
#' # Lancefield classification, see ?as.mo ------------------------------------
-#' mo_fullname("S. pyo") # "Streptococcus pyogenes"
-#' mo_fullname("S. pyo", Lancefield = TRUE) # "Streptococcus group A"
-#' mo_shortname("S. pyo") # "S. pyogenes"
-#' mo_shortname("S. pyo", Lancefield = TRUE) # "GAS" (='Group A Streptococci')
+#' mo_fullname("S. pyo")
+#' mo_fullname("S. pyo", Lancefield = TRUE)
+#' mo_shortname("S. pyo")
+#' mo_shortname("S. pyo", Lancefield = TRUE)
#'
#'
#' # language support --------------------------------------------------------
-#' mo_gramstain("E. coli", language = "de") # "Gramnegativ"
-#' mo_gramstain("E. coli", language = "nl") # "Gram-negatief"
-#' mo_gramstain("E. coli", language = "es") # "Gram negativo"
+#' mo_gramstain("Klebsiella pneumoniae", language = "de")
+#' mo_gramstain("Klebsiella pneumoniae", language = "nl")
+#' mo_gramstain("Klebsiella pneumoniae", language = "es")
#'
#' # mo_type is equal to mo_kingdom, but mo_kingdom will remain official
-#' mo_kingdom("E. coli") # "Bacteria" on a German system
-#' mo_type("E. coli") # "Bakterien" on a German system
-#' mo_type("E. coli") # "Bacteria" on an English system
+#' mo_kingdom("Klebsiella pneumoniae")
+#' mo_type("Klebsiella pneumoniae")
+#' mo_type("Klebsiella pneumoniae")
#'
#' mo_fullname("S. pyogenes",
#' Lancefield = TRUE,
-#' language = "de") # "Streptococcus Gruppe A"
+#' language = "de")
#' mo_fullname("S. pyogenes",
#' Lancefield = TRUE,
-#' language = "nl") # "Streptococcus groep A"
+#' language = "nl")
#'
#'
#' # other --------------------------------------------------------------------
#'
-#' mo_is_yeast(c("Candida", "E. coli")) # TRUE, FALSE
+#' mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
#'
-#' # gram stains and intrinsic resistance can also be used as a filter in dplyr verbs
-#' \donttest{
+#' # gram stains and intrinsic resistance can be used as a filter in dplyr verbs
#' if (require("dplyr")) {
#' example_isolates %>%
#' filter(mo_is_gram_positive())
@@ -164,11 +161,11 @@
#'
#'
#' # get a list with the complete taxonomy (from kingdom to subspecies)
-#' mo_taxonomy("E. coli")
+#' mo_taxonomy("Klebsiella pneumoniae")
+#'
#' # get a list with the taxonomy, the authors, Gram-stain,
-#' # SNOMED codes, and URL to the online database
-#' mo_info("E. coli")
-#' }
+#' # SNOMED codes, and URL to the online database
+#' mo_info("Klebsiella pneumoniae")
#' }
mo_name <- function(x, language = get_AMR_locale(), ...) {
if (missing(x)) {
diff --git a/R/mo_source.R b/R/mo_source.R
index c1fa48350..4aa83d5ca 100644
--- a/R/mo_source.R
+++ b/R/mo_source.R
@@ -28,7 +28,6 @@
#' @description These functions can be used to predefine your own reference to be used in [as.mo()] and consequently all [`mo_*`][mo_property()] functions (such as [mo_genus()] and [mo_gramstain()]).
#'
#' This is **the fastest way** to have your organisation (or analysis) specific codes picked up and translated by this package, since you don't have to bother about it again after setting it up once.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param path location of your reference file, this can be any text file (comma-, tab- or pipe-separated) or an Excel file (see *Details*). Can also be `""`, `NULL` or `FALSE` to delete the reference file.
#' @param destination destination of the compressed data file, default to the user's home directory.
#' @rdname mo_source
@@ -121,7 +120,6 @@
#'
#' If the original file (in the previous case an Excel file) is moved or deleted, the `mo_source.rds` file will be removed upon the next use of [as.mo()] or any [`mo_*`][mo_property()] function.
#' @export
-#' @inheritSection AMR Read more on Our Website!
set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_source.rds")) {
meet_criteria(path, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(destination, allow_class = "character", has_length = 1)
diff --git a/R/pca.R b/R/pca.R
index 906afa224..599fd59ff 100755
--- a/R/pca.R
+++ b/R/pca.R
@@ -26,7 +26,6 @@
#' Principal Component Analysis (for AMR)
#'
#' Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [data.frame] containing [numeric] columns
#' @param ... columns of `x` to be selected for PCA, can be unquoted since it supports quasiquotation.
#' @inheritParams stats::prcomp
@@ -36,7 +35,6 @@
#' @return An object of classes [pca] and [prcomp]
#' @importFrom stats prcomp
#' @export
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # `example_isolates` is a data set available in the AMR package.
#' # See ?example_isolates.
@@ -47,6 +45,7 @@
#' resistance_data <- example_isolates %>%
#' group_by(order = mo_order(mo), # group on anything, like order
#' genus = mo_genus(mo)) %>% # and genus as we do here;
+#' filter(n() >= 30) %>% # filter on only 30 results per group
#' summarise_if(is.rsi, resistance) # then get resistance of all drugs
#'
#' # now conduct PCA for certain antimicrobial agents
@@ -55,8 +54,17 @@
#'
#' pca_result
#' summary(pca_result)
+#'
+#' # old base R plotting method:
#' biplot(pca_result)
-#' ggplot_pca(pca_result) # a new and convenient plot function
+#' # new ggplot2 plotting method using this package:
+#' ggplot_pca(pca_result)
+#'
+#' if (require("ggplot2")) {
+#' ggplot_pca(pca_result) +
+#' scale_colour_viridis_d() +
+#' labs(title = "Title here")
+#' }
#' }
#' }
pca <- function(x,
diff --git a/R/plot.R b/R/plot.R
index a9bc97c42..68ec43519 100644
--- a/R/plot.R
+++ b/R/plot.R
@@ -26,8 +26,7 @@
#' Plotting for Classes `rsi`, `mic` and `disk`
#'
#' Functions to plot classes `rsi`, `mic` and `disk`, with support for base \R and `ggplot2`.
-#' @inheritSection lifecycle Stable Lifecycle
-#' @inheritSection AMR Read more on Our Website!
+
#' @param x,object values created with [as.mic()], [as.disk()] or [as.rsi()] (or their `random_*` variants, such as [random_mic()])
#' @param mo any (vector of) text that can be coerced to a valid microorganism code with [as.mo()]
#' @param ab any (vector of) text that can be coerced to a valid antimicrobial code with [as.ab()]
diff --git a/R/proportion.R b/R/proportion.R
index a85ee5caa..c46d06d4c 100755
--- a/R/proportion.R
+++ b/R/proportion.R
@@ -28,7 +28,6 @@
#' @description These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, see *Examples*.
#'
#' [resistance()] should be used to calculate resistance, [susceptibility()] should be used to calculate susceptibility.\cr
-#' @inheritSection lifecycle Stable Lifecycle
#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.rsi()] if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See *Examples*.
#' @param minimum the minimum allowed number of available (tested) isolates. Any isolate count lower than `minimum` will return `NA` with a warning. The default number of `30` isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see *Source*.
#' @param as_percent a [logical] to indicate whether the output must be returned as a hundred fold with % sign (a character). A value of `0.123456` will then be returned as `"12.3%"`.
@@ -88,11 +87,11 @@
#' @aliases portion
#' @name proportion
#' @export
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # example_isolates is a data set available in the AMR package.
-#' ?example_isolates
+#' # run ?example_isolates for more info.
#'
+#' # base R ------------------------------------------------------------
#' resistance(example_isolates$AMX) # determines %R
#' susceptibility(example_isolates$AMX) # determines %S+I
#'
@@ -103,6 +102,7 @@
#' proportion_IR(example_isolates$AMX)
#' proportion_R(example_isolates$AMX)
#'
+#' # dplyr -------------------------------------------------------------
#' \donttest{
#' if (require("dplyr")) {
#' example_isolates %>%
@@ -157,10 +157,11 @@
#' proportion_df(translate = FALSE)
#'
#' # It also supports grouping variables
+#' # (use rsi_df to also include the count)
#' example_isolates %>%
#' select(hospital_id, AMX, CIP) %>%
#' group_by(hospital_id) %>%
-#' proportion_df(translate = FALSE)
+#' rsi_df(translate = FALSE)
#' }
#' }
resistance <- function(...,
diff --git a/R/random.R b/R/random.R
index cb8a64e5d..12f692635 100644
--- a/R/random.R
+++ b/R/random.R
@@ -25,8 +25,7 @@
#' Random MIC Values/Disk Zones/RSI Generation
#'
-#' These functions can be used for generating random MIC values and disk diffusion diameters, for AMR data analysis practice. By providing a microorganism and antimicrobial agent, the generated results will reflect reality as much as possible.
-#' @inheritSection lifecycle Stable Lifecycle
+#' These functions can be used for generating random MIC values and disk diffusion diameters, for AMR data analysis practice. By providing a microorganism and antimicrobial agent, the generated results will reflect reality as much as possible.
#' @param size desired size of the returned vector. If used in a [data.frame] call or `dplyr` verb, will get the current (group) size if left blank.
#' @param mo any [character] that can be coerced to a valid microorganism code with [as.mo()]
#' @param ab any [character] that can be coerced to a valid antimicrobial agent code with [as.ab()]
@@ -39,21 +38,20 @@
#' @name random
#' @rdname random
#' @export
-#' @inheritSection AMR Read more on Our Website!
#' @examples
-#' random_mic(100)
-#' random_disk(100)
-#' random_rsi(100)
+#' random_mic(25)
+#' random_disk(25)
+#' random_rsi(25)
#'
#' \donttest{
#' # make the random generation more realistic by setting a bug and/or drug:
-#' random_mic(100, "Klebsiella pneumoniae") # range 0.0625-64
-#' random_mic(100, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
-#' random_mic(100, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
+#' random_mic(25, "Klebsiella pneumoniae") # range 0.0625-64
+#' random_mic(25, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
+#' random_mic(25, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
#'
-#' random_disk(100, "Klebsiella pneumoniae") # range 8-50
-#' random_disk(100, "Klebsiella pneumoniae", "ampicillin") # range 11-17
-#' random_disk(100, "Streptococcus pneumoniae", "ampicillin") # range 12-27
+#' random_disk(25, "Klebsiella pneumoniae") # range 8-50
+#' random_disk(25, "Klebsiella pneumoniae", "ampicillin") # range 11-17
+#' random_disk(25, "Streptococcus pneumoniae", "ampicillin") # range 12-27
#' }
random_mic <- function(size = NULL, mo = NULL, ab = NULL, ...) {
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
diff --git a/R/resistance_predict.R b/R/resistance_predict.R
index e44cb15f9..1b6a592d3 100755
--- a/R/resistance_predict.R
+++ b/R/resistance_predict.R
@@ -26,7 +26,6 @@
#' Predict Antimicrobial Resistance
#'
#' Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns `se_min` and `se_max`. See *Examples* for a real live example.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param object model data to be plotted
#' @param col_ab column name of `x` containing antimicrobial interpretations (`"R"`, `"I"` and `"S"`)
#' @param col_date column name of the date, will be used to calculate years if this column doesn't consist of years already, defaults to the first column of with a date class
@@ -64,7 +63,6 @@
#' @rdname resistance_predict
#' @export
#' @importFrom stats predict glm lm
-#' @inheritSection AMR Read more on Our Website!
#' @examples
#' x <- resistance_predict(example_isolates,
#' col_ab = "AMX",
@@ -99,24 +97,8 @@
#' model = "binomial",
#' info = FALSE,
#' minimum = 15)
-#'
+#' head(data)
#' autoplot(data)
-#'
-#' ggplot(data,
-#' aes(x = year)) +
-#' geom_col(aes(y = value),
-#' fill = "grey75") +
-#' geom_errorbar(aes(ymin = se_min,
-#' ymax = se_max),
-#' colour = "grey50") +
-#' scale_y_continuous(limits = c(0, 1),
-#' breaks = seq(0, 1, 0.1),
-#' labels = paste0(seq(0, 100, 10), "%")) +
-#' labs(title = expression(paste("Forecast of Amoxicillin Resistance in ",
-#' italic("E. coli"))),
-#' y = "%R",
-#' x = "Year") +
-#' theme_minimal(base_size = 13)
#' }
#' }
resistance_predict <- function(x,
diff --git a/R/rsi.R b/R/rsi.R
index 1b86ee7e2..bdeddf867 100755
--- a/R/rsi.R
+++ b/R/rsi.R
@@ -26,7 +26,6 @@
#' Interpret MIC and Disk Values, or Clean Raw R/SI Data
#'
#' Interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI, or clean up existing R/SI values. This transforms the input to a new class [`rsi`], which is an ordered [factor] with levels `S < I < R`.
-#' @inheritSection lifecycle Stable Lifecycle
#' @rdname as.rsi
#' @param x vector of values (for class [`mic`]: MIC values in mg/L, for class [`disk`]: a disk diffusion radius in millimetres)
#' @param mo any (vector of) text that can be coerced to valid microorganism codes with [as.mo()], can be left empty to determine it automatically
@@ -98,15 +97,10 @@
#' @export
#' @seealso [as.mic()], [as.disk()], [as.mo()]
#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
#' @examples
+#' example_isolates
#' summary(example_isolates) # see all R/SI results at a glance
-#' \donttest{
-#' if (require("skimr")) {
-#' # class <rsi> supported in skim() too:
-#' skim(example_isolates)
-#' }
-#' }
+#'
#' # For INTERPRETING disk diffusion and MIC values -----------------------
#'
#' # a whole data set, even with combined MIC values and disk zones
@@ -796,7 +790,7 @@ exec_as.rsi <- function(method,
lookup_lancefield[i],
lookup_other[i]))
- if (any(get_record$uti == TRUE, na.rm = TRUE) && message_not_thrown_before("as.rsi", "msg3", ab)) {
+ if (any(get_record$uti == TRUE, na.rm = TRUE) && !any(uti == TRUE, na.rm = TRUE) && message_not_thrown_before("as.rsi", "msg3", ab)) {
warning_("in `as.rsi()`: interpretation of ", font_bold(ab_name(ab, tolower = TRUE)), " is only available for (uncomplicated) urinary tract infections (UTI) for some microorganisms. Use argument `uti` to set which isolates are from urine. See ?as.rsi.")
rise_warning <- TRUE
}
diff --git a/R/skewness.R b/R/skewness.R
index f078899dd..0e5050911 100755
--- a/R/skewness.R
+++ b/R/skewness.R
@@ -28,13 +28,13 @@
#' @description Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
#'
#' When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0.
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x a vector of values, a [matrix] or a [data.frame]
#' @param na.rm a [logical] value indicating whether `NA` values should be stripped before the computation proceeds
#' @seealso [kurtosis()]
#' @rdname skewness
-#' @inheritSection AMR Read more on Our Website!
#' @export
+#' @examples
+#' skewness(runif(1000))
skewness <- function(x, na.rm = FALSE) {
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
UseMethod("skewness")
diff --git a/R/translate.R b/R/translate.R
index a65f856b8..8926b58ab 100755
--- a/R/translate.R
+++ b/R/translate.R
@@ -26,12 +26,11 @@
#' Translate Strings from the AMR Package
#'
#' For language-dependent output of AMR functions, like [mo_name()], [mo_gramstain()], [mo_type()] and [ab_name()].
-#' @inheritSection lifecycle Stable Lifecycle
#' @param x text to translate
#' @param lang language to choose. Use one of these supported language names or ISO-639-1 codes: `r paste0('"', sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), '" ("' , LANGUAGES_SUPPORTED, '")', collapse = ", ")`.
#' @details The currently `r length(LANGUAGES_SUPPORTED)` supported languages are `r vector_and(sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), quotes = FALSE, sort = FALSE)`. All these languages have translations available for all antimicrobial agents and colloquial microorganism names.
#'
-#' Please read about adding or updating a language in [our developer guideline](https://github.com/msberends/AMR/blob/main/developer-guideline.md).
+#' Please read about adding or updating a language in [our Wiki](https://github.com/msberends/AMR/wiki/).
#'
#' ## Changing the Default Language
#' The system language will be used at default (as returned by `Sys.getenv("LANG")` or, if `LANG` is not set, [Sys.getlocale("LC_COLLATE")]), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:
@@ -42,7 +41,6 @@
#' 2. Setting the system variable `LANGUAGE` or `LANG`, e.g. by adding `LANGUAGE="de_DE.utf8"` to your `.Renviron` file in your home directory.
#'
#' Thus, if the R option `AMR_locale` is set, the system variables `LANGUAGE` and `LANG` will be ignored.
-#' @inheritSection AMR Read more on Our Website!
#' @rdname translate
#' @name translate
#' @export
diff --git a/R/vctrs.R b/R/vctrs.R
index b123f91d5..3241c502e 100644
--- a/R/vctrs.R
+++ b/R/vctrs.R
@@ -28,8 +28,9 @@
# They are to convert AMR-specific classes to bare characters and integers.
# All of them will be exported using s3_register() in R/zzz.R when loading the package.
-# S3: ab_selector
# see https://github.com/tidyverse/dplyr/issues/5955 why this is required
+
+# S3: ab_selector
vec_ptype2.character.ab_selector <- function(x, y, ...) {
x
}
@@ -40,6 +41,17 @@ vec_cast.character.ab_selector <- function(x, to, ...) {
unclass(x)
}
+# S3: ab_selector_any_all
+vec_ptype2.logical.ab_selector_any_all <- function(x, y, ...) {
+ x
+}
+vec_ptype2.ab_selector_any_all.logical <- function(x, y, ...) {
+ y
+}
+vec_cast.logical.ab_selector_any_all <- function(x, to, ...) {
+ unclass(x)
+}
+
# S3: ab
vec_ptype2.character.ab <- function(x, y, ...) {
x
diff --git a/R/whocc.R b/R/whocc.R
index 170aff6c1..e99bd3663 100755
--- a/R/whocc.R
+++ b/R/whocc.R
@@ -35,7 +35,7 @@
#' The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.
#'
#' **NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.** See <https://www.whocc.no/copyright_disclaimer/.>
-#' @inheritSection AMR Read more on Our Website!
+
#' @name WHOCC
#' @rdname WHOCC
#' @examples
diff --git a/R/zzz.R b/R/zzz.R
index 21124befd..396f753fc 100755
--- a/R/zzz.R
+++ b/R/zzz.R
@@ -87,6 +87,9 @@ if (utf8_supported && !is_latex) {
s3_register("vctrs::vec_ptype2", "ab_selector.character")
s3_register("vctrs::vec_ptype2", "character.ab_selector")
s3_register("vctrs::vec_cast", "character.ab_selector")
+ s3_register("vctrs::vec_ptype2", "ab_selector_any_all.logical")
+ s3_register("vctrs::vec_ptype2", "logical.ab_selector_any_all")
+ s3_register("vctrs::vec_cast", "logical.ab_selector_any_all")
s3_register("vctrs::vec_ptype2", "disk.integer")
s3_register("vctrs::vec_ptype2", "integer.disk")
s3_register("vctrs::vec_cast", "integer.disk")
@@ -106,11 +109,6 @@ if (utf8_supported && !is_latex) {
assign(x = "MO.old_lookup", value = create_MO.old_lookup(), envir = asNamespace("AMR"))
# for mo_is_intrinsic_resistant() - saves a lot of time when executed on this vector
assign(x = "INTRINSIC_R", value = create_intr_resistance(), envir = asNamespace("AMR"))
-
- # for building the website, only print first 5 rows of a data set
- # if (Sys.getenv("IN_PKGDOWN") != "" && !interactive()) {
- # ...
- # }
}
# Helper functions --------------------------------------------------------
diff --git a/README.md b/README.md
index 3df4f1deb..1dbaf29fe 100755
--- a/README.md
+++ b/README.md
@@ -8,9 +8,7 @@
<img src="https://msberends.github.io/AMR/AMR_intro.svg" align="center" height="300px" />
-The latest built **source package** (`AMR_latest.tar.gz`) can be found in folder [/data-raw/](https://github.com/msberends/AMR/tree/main/data-raw).
-
-`AMR` is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. It is currently being used in over 150 countries.
+`AMR` is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. It is currently being used in over 175 countries.
After installing this package, R knows ~71,000 distinct microbial species and all ~570 antibiotic, antimycotic, and antiviral drugs by name and code (including ATC, WHONET/EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. Antimicrobial names and group names are available in Danish, Dutch, English, French, German, Italian, Portuguese and Spanish.
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 1f896ae3c..4a7892a54 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -26,13 +26,38 @@
title: "AMR (for R)"
url: "https://msberends.github.io/AMR/"
-development:
- mode: "release" # improves indexing by search engines
- version_tooltip: "Latest development version"
+template:
+ bootstrap: 5
+ bootswatch: "flatly"
+ assets: "pkgdown/logos" # use logos in this folder
+ bslib:
+ code_font: {google: "Fira Code"}
+ body-text-align: "justify"
+ # the green "success" colour of this bootstrap theme should be the same as the green in our logo
+ success: "#128f76"
+ link-color: "#128f76"
+ navbar-padding-y: "0.5rem"
+ opengraph:
+ twitter:
+ creator: "@msberends"
+ site: "@univgroningen"
+ card: summary_large_image
news:
one_page: true
cran_dates: true
+
+footer:
+ structure:
+ left: [devtext]
+ right: [logo]
+ components:
+ devtext: '<code>AMR</code> (for R). Developed at the <a target="_blank" href="https://www.rug.nl">University of Groningen</a> in collaboration with non-profit organisations<br><a target="_blank" href="https://www.certe.nl">Certe Medical Diagnostics and Advice Foundation</a> and <a target="_blank" href="https://www.umcg.nl">University Medical Center Groningen</a>.'
+ logo: '<a target="_blank" href="https://www.rug.nl"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/logos/logo_rug.png" style="max-width: 200px;"></a>'
+
+home:
+ sidebar:
+ structure: [toc, links, authors, citation]
navbar:
title: "AMR (for R)"
@@ -161,7 +186,6 @@ reference:
- "`catalogue_of_life`"
- "`catalogue_of_life_version`"
- "`WHOCC`"
- - "`lifecycle`"
- "`example_isolates_unclean`"
- "`rsi_translation`"
- "`WHONET`"
@@ -200,14 +224,3 @@ reference:
contents:
- "`AMR-deprecated`"
-template:
- bootstrap: 3
- opengraph:
- twitter:
- creator: "@msberends"
- site: "@univgroningen"
- card: summary_large_image
- assets: "pkgdown/logos" # use logos in this folder
- params:
- noindex: false
- bootswatch: "flatly"
diff --git a/data/example_isolates.rda b/data/example_isolates.rda
index 73c96e995..38f9c2c82 100644
Binary files a/data/example_isolates.rda and b/data/example_isolates.rda differ
diff --git a/developer-guideline.md b/developer-guideline.md
deleted file mode 100644
index 18e90e22f..000000000
--- a/developer-guideline.md
+++ /dev/null
@@ -1,84 +0,0 @@
-# Developer Guideline
-
-Welcome to the Developer Guideline of the `AMR` R package. This guideline explains about repository workflows and updates of package elements.
-
-## Copyright
-
-This R package and of its components are licensed under the [GNU General Public License (GPL) v2.0](https://github.com/msberends/AMR/blob/main/LICENSE). In a nutshell, this means that this package:
-
-- May be used for commercial purposes
-
-- May be used for private purposes
-
-- May **not** be used for patent purposes
-
-- May be modified, although:
-
- - Modifications **must** be released under the same license when distributing the package
- - Changes made to the code **must** be documented
-
-- May be distributed, although:
-
- - Source code **must** be made available when the package is distributed
- - A copy of the license and copyright notice **must** be included with the package.
-
-- Comes with a LIMITATION of liability
-
-- Comes with NO warranty
-
-## General Intended Git(Hub) Workflow
-
-All updates to the reposo should be done using `git commit`, preferably with the following predefined pre-commit Git hook.
-
-This repository provides automated semantic versioning and R documentation updates by using a pre-commit Git hook. When using `git commit`, a script will be run to increase the version number, update the date and R documentation. To set this up, run this command when working locally in the repository:
-
-```bash
-git config --local core.hooksPath ".github/prehooks"
-```
-
-Now, when using `git commit`:
-
-```bash
-git commit -am "test commit"
-# Running pre-commit hook...
-# >> Updating R documentation...
-# >> done.
-# >>
-# >> Updating semantic versioning and date...
-# >> - latest tag is 'v1.8.1', with 26 previous commits
-# >> - testpkg pkg version set to 1.8.1.9027
-# >> - updated DESCRIPTION
-# >> - updated NEWS.md
-# >>
-# [main 300b93e] test commit
-# 3 files changed, 3 insertions(+), 4 deletions(-)
-```
-
-### Website Generation
-
-### Commiting Changes
-
-## Updating the AMR Package
-
-### Update EUCAST/CLSI Guidelines
-
-### Update the Microbial Taxonomy
-
-### Update the Antimicrobial Agents
-
-### Add or Update a Language for Translation
-
-For the most ideal workflow, please fork this repository and make the changes in your own forked repository. Afterwards, please create a Pull Request. If you are unfamiliar with these terms, no problem at all! Then please send us the edited files by email or any way you prefer.
-
-The repository file [`data-raw/translations.tsv`](https://github.com/msberends/AMR/blob/main/developer-guideline.md) contains all translations. This file will be read by all functions where a translated output can be desired, like all `mo_*` functions (such as `mo_name()`, `mo_gramstain()`, `mo_type()`, etc.) and ``ab_*` functions (such as `ab_name()`, `ab_group()`, etc.).
-
-1. To **add** a translation, edit `data-raw/translations.tsv` (you can copy the contains to MS Excel for convenience and paste the contents back later), add a column where the new column name is a [ISO 639-1 language code](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (such as `en` for English, `de` for German and `es` for Spanish) and put in the new column all translated text from the first column.\
- \
- To **update** a translation, open `data-raw/translations.tsv` and save it with the language updates.
-
-2. Set the current working directory to the AMR package root folder (either by opening the AMR package as RStudio project, or by setting the working directory with `setwd()`).
-
-3. Run `source("data-raw/_language_update.R)"` to update the internal package data. If you have the `roxygen2` package installed, this script automatically updates the package documentation as well.
-
-Many thanks for your contribution!
-
diff --git a/docs/404.html b/docs/404.html
deleted file mode 100644
index 0cd5bb7c1..000000000
--- a/docs/404.html
+++ /dev/null
@@ -1,225 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en">
-<head>
-<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
-<meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
-<title>Page not found (404) • AMR (for R)</title>
-<!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="https://msberends.github.io/AMR/favicon-16x16.png">
-<link rel="icon" type="image/png" sizes="32x32" href="https://msberends.github.io/AMR/favicon-32x32.png">
-<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="https://msberends.github.io/AMR/apple-touch-icon.png">
-<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="https://msberends.github.io/AMR/apple-touch-icon-120x120.png">
-<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="https://msberends.github.io/AMR/apple-touch-icon-76x76.png">
-<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="https://msberends.github.io/AMR/apple-touch-icon-60x60.png">
-<!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link href="https://cdnjs.cloudflare.com/ajax/libs/bootswatch/3.4.0/flatly/bootstrap.min.css" rel="stylesheet" crossorigin="anonymous">
-<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="https://msberends.github.io/AMR/bootstrap-toc.css">
-<script src="https://msberends.github.io/AMR/bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
-<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
-<!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="https://msberends.github.io/AMR/pkgdown.css" rel="stylesheet">
-<script src="https://msberends.github.io/AMR/pkgdown.js"></script><link href="https://msberends.github.io/AMR/extra.css" rel="stylesheet">
-<script src="https://msberends.github.io/AMR/extra.js"></script><meta property="og:title" content="Page not found (404)">
-<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg">
-<meta name="twitter:card" content="summary_large_image">
-<meta name="twitter:creator" content="@msberends">
-<meta name="twitter:site" content="@univgroningen">
-<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
-<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
-<![endif]-->
-</head>
-<body data-spy="scroll" data-target="#toc">
-
-
- <div class="container template-title-body">
- <header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
- <div class="container">
- <div class="navbar-header">
- <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
- <span class="sr-only">Toggle navigation</span>
- <span class="icon-bar"></span>
- <span class="icon-bar"></span>
- <span class="icon-bar"></span>
- </button>
- <span class="navbar-brand">
- <a class="navbar-link" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
- <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1.9014</span>
- </span>
- </div>
-
- <div id="navbar" class="navbar-collapse collapse">
- <ul class="nav navbar-nav">
-<li>
- <a href="https://msberends.github.io/AMR/index.html">
- <span class="fa fa-home"></span>
-
- Home
- </a>
-</li>
-<li class="dropdown">
- <a href="https://msberends.github.io/AMR/#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">
- <span class="fa fa-question-circle"></span>
-
- How to
-
- <span class="caret"></span>
- </a>
- <ul class="dropdown-menu" role="menu">
-<li>
- <a href="https://msberends.github.io/AMR/articles/AMR.html">
- <span class="fa fa-directions"></span>
-
- Conduct AMR analysis
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/articles/resistance_predict.html">
- <span class="fa fa-dice"></span>
-
- Predict antimicrobial resistance
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/articles/datasets.html">
- <span class="fa fa-database"></span>
-
- Data sets for download / own use
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/articles/PCA.html">
- <span class="fa fa-compress"></span>
-
- Conduct principal component analysis for AMR
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/articles/MDR.html">
- <span class="fa fa-skull-crossbones"></span>
-
- Determine multi-drug resistance (MDR)
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/articles/WHONET.html">
- <span class="fa fa-globe-americas"></span>
-
- Work with WHONET data
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/articles/SPSS.html">
- <span class="fa fa-file-upload"></span>
-
- Import data from SPSS/SAS/Stata
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/articles/EUCAST.html">
- <span class="fa fa-exchange-alt"></span>
-
- Apply EUCAST rules
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/reference/mo_property.html">
- <span class="fa fa-bug"></span>
-
- Get properties of a microorganism
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/reference/ab_property.html">
- <span class="fa fa-capsules"></span>
-
- Get properties of an antibiotic
- </a>
- </li>
- <li>
- <a href="https://msberends.github.io/AMR/articles/benchmarks.html">
- <span class="fa fa-shipping-fast"></span>
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- Other: benchmarks
- </a>
- </li>
- </ul>
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- <span class="fa fa-book-open"></span>
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- Manual
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- <span class="fa fa-users"></span>
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- Authors
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-<li>
- <a href="https://msberends.github.io/AMR/news/index.html">
- <span class="far fa-newspaper"></span>
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- Changelog
- </a>
-</li>
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- Source Code
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\ No newline at end of file
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- <h1>License</h1>
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-
-<pre>GNU GENERAL PUBLIC LICENSE
-Version 2, June 1991
-
-Copyright (C) 1989, 1991 Free Software Foundation, Inc., <http://fsf.org/>
- 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
-Everyone is permitted to copy and distribute verbatim copies
-of this license document, but changing it is not allowed.
-
-A SUMMARY OF THIS LICENSE BY THE ORIGINAL AUTHORS OF THE AMR R PACKAGE
-
-This R package, with package name 'AMR':
-- May be used for commercial purposes
-- May be used for private purposes
-- May NOT be used for patent purposes
-- May be modified, although:
- - Modifications MUST be released under the same license when distributing the package
- - Changes made to the code MUST be documented
-- May be distributed, although:
- - Source code MUST be made available when the package is distributed
- - A copy of the license and copyright notice MUST be included with the package.
-- Comes with a LIMITATION of liability
-- Comes with NO warranty
-
-END OF THE SUMMARY
-
-
-GNU GENERAL PUBLIC LICENSE
-TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
-
-0. This License applies to any program or other work which contains
-a notice placed by the copyright holder saying it may be distributed
-under the terms of this General Public License. The "Program", below,
-refers to any such program or work, and a "work based on the Program"
-means either the Program or any derivative work under copyright law:
-that is to say, a work containing the Program or a portion of it,
-either verbatim or with modifications and/or translated into another
-language. (Hereinafter, translation is included without limitation in
-the term "modification".) Each licensee is addressed as "you".
-
-Activities other than copying, distribution and modification are not
-covered by this License; they are outside its scope. The act of
-running the Program is not restricted, and the output from the Program
-is covered only if its contents constitute a work based on the
-Program (independent of having been made by running the Program).
-Whether that is true depends on what the Program does.
-
-1. You may copy and distribute verbatim copies of the Program's
-source code as you receive it, in any medium, provided that you
-conspicuously and appropriately publish on each copy an appropriate
-copyright notice and disclaimer of warranty; keep intact all the
-notices that refer to this License and to the absence of any warranty;
-and give any other recipients of the Program a copy of this License
-along with the Program.
-
-You may charge a fee for the physical act of transferring a copy, and
-you may at your option offer warranty protection in exchange for a fee.
-
-2. You may modify your copy or copies of the Program or any portion
-of it, thus forming a work based on the Program, and copy and
-distribute such modifications or work under the terms of Section 1
-above, provided that you also meet all of these conditions:
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- stating that you changed the files and the date of any change.
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- b) You must cause any work that you distribute or publish, that in
- whole or in part contains or is derived from the Program or any
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-These requirements apply to the modified work as a whole. If
-identifiable sections of that work are not derived from the Program,
-and can be reasonably considered independent and separate works in
-themselves, then this License, and its terms, do not apply to those
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-distribute the same sections as part of a whole which is a work based
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-this License, whose permissions for other licensees extend to the
-entire whole, and thus to each and every part regardless of who wrote it.
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-your rights to work written entirely by you; rather, the intent is to
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-In addition, mere aggregation of another work not based on the Program
-with the Program (or with a work based on the Program) on a volume of
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-the scope of this License.
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-3. You may copy and distribute the Program (or a work based on it,
-under Section 2) in object code or executable form under the terms of
-Sections 1 and 2 above provided that you also do one of the following:
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- a) Accompany it with the complete corresponding machine-readable
- source code, which must be distributed under the terms of Sections
- 1 and 2 above on a medium customarily used for software interchange; or,
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- b) Accompany it with a written offer, valid for at least three
- years, to give any third party, for a charge no more than your
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- to distribute corresponding source code. (This alternative is
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- received the program in object code or executable form with such
- an offer, in accord with Subsection b above.)
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-The source code for a work means the preferred form of the work for
-making modifications to it. For an executable work, complete source
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-distribution of the source code, even though third parties are not
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-4. You may not copy, modify, sublicense, or distribute the Program
-except as expressly provided under this License. Any attempt
-otherwise to copy, modify, sublicense or distribute the Program is
-void, and will automatically terminate your rights under this License.
-However, parties who have received copies, or rights, from you under
-this License will not have their licenses terminated so long as such
-parties remain in full compliance.
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-5. You are not required to accept this License, since you have not
-signed it. However, nothing else grants you permission to modify or
-distribute the Program or its derivative works. These actions are
-prohibited by law if you do not accept this License. Therefore, by
-modifying or distributing the Program (or any work based on the
-Program), you indicate your acceptance of this License to do so, and
-all its terms and conditions for copying, distributing or modifying
-the Program or works based on it.
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-6. Each time you redistribute the Program (or any work based on the
-Program), the recipient automatically receives a license from the
-original licensor to copy, distribute or modify the Program subject to
-these terms and conditions. You may not impose any further
-restrictions on the recipients' exercise of the rights granted herein.
-You are not responsible for enforcing compliance by third parties to
-this License.
-
-7. If, as a consequence of a court judgment or allegation of patent
-infringement or for any other reason (not limited to patent issues),
-conditions are imposed on you (whether by court order, agreement or
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- <h1 data-toc-skip>How to conduct AMR data analysis</h1>
- <h4 data-toc-skip class="author">Dr Matthijs
-Berends</h4>
-
- <h4 data-toc-skip class="date">11 mei 2022</h4>
-
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small>
- <div class="hidden name"><code>AMR.Rmd</code></div>
-
- </div>
-
-
-
-<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/" class="external-link">R
-Markdown</a>. However, the methodology remains unchanged. This page was
-generated on 11 mei 2022.</p>
-<div class="section level2">
-<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
-</h2>
-<p>Conducting AMR data analysis unfortunately requires in-depth
-knowledge from different scientific fields, which makes it hard to do
-right. At least, it requires:</p>
-<ul>
-<li>Good questions (always start with those!)</li>
-<li>A thorough understanding of (clinical) epidemiology, to understand
-the clinical and epidemiological relevance and possible bias of
-results</li>
-<li>A thorough understanding of (clinical) microbiology/infectious
-diseases, to understand which microorganisms are causal to which
-infections and the implications of pharmaceutical treatment, as well as
-understanding intrinsic and acquired microbial resistance</li>
-<li>Experience with data analysis with microbiological tests and their
-results, to understand the determination and limitations of MIC values
-and their interpretations to RSI values</li>
-<li>Availability of the biological taxonomy of microorganisms and
-probably normalisation factors for pharmaceuticals, such as defined
-daily doses (DDD)</li>
-<li>Available (inter-)national guidelines, and profound methods to apply
-them</li>
-</ul>
-<p>Of course, we cannot instantly provide you with knowledge and
-experience. But with this <code>AMR</code> package, we aimed at
-providing (1) tools to simplify antimicrobial resistance data cleaning,
-transformation and analysis, (2) methods to easily incorporate
-international guidelines and (3) scientifically reliable reference data,
-including the requirements mentioned above.</p>
-<p>The <code>AMR</code> package enables standardised and reproducible
-AMR data analysis, with the application of evidence-based rules,
-determination of first isolates, translation of various codes for
-microorganisms and antimicrobial agents, determination of (multi-drug)
-resistant microorganisms, and calculation of antimicrobial resistance,
-prevalence and future trends.</p>
-</div>
-<div class="section level2">
-<h2 id="preparation">Preparation<a class="anchor" aria-label="anchor" href="#preparation"></a>
-</h2>
-<p>For this tutorial, we will create fake demonstration data to work
-with.</p>
-<p>You can skip to <a href="#cleaning-the-data">Cleaning the data</a> if
-you already have your own data ready. If you start your analysis, try to
-make the structure of your data generally look like this:</p>
-<table class="table">
-<thead><tr class="header">
-<th align="center">date</th>
-<th align="center">patient_id</th>
-<th align="center">mo</th>
-<th align="center">AMX</th>
-<th align="center">CIP</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">2022-05-11</td>
-<td align="center">abcd</td>
-<td align="center">Escherichia coli</td>
-<td align="center">S</td>
-<td align="center">S</td>
-</tr>
-<tr class="even">
-<td align="center">2022-05-11</td>
-<td align="center">abcd</td>
-<td align="center">Escherichia coli</td>
-<td align="center">S</td>
-<td align="center">R</td>
-</tr>
-<tr class="odd">
-<td align="center">2022-05-11</td>
-<td align="center">efgh</td>
-<td align="center">Escherichia coli</td>
-<td align="center">R</td>
-<td align="center">S</td>
-</tr>
-</tbody>
-</table>
-<div class="section level3">
-<h3 id="needed-r-packages">Needed R packages<a class="anchor" aria-label="anchor" href="#needed-r-packages"></a>
-</h3>
-<p>As with many uses in R, we need some additional packages for AMR data
-analysis. Our package works closely together with the <a href="https://www.tidyverse.org" class="external-link">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/" class="external-link"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org" class="external-link"><code>ggplot2</code></a> by
-RStudio. The tidyverse tremendously improves the way we conduct data
-science - it allows for a very natural way of writing syntaxes and
-creating beautiful plots in R.</p>
-<p>We will also use the <code>cleaner</code> package, that can be used
-for cleaning data and creating frequency tables.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner" class="external-link">cleaner</a></span><span class="op">)</span>
-
-<span class="co"># (if not yet installed, install with:)</span>
-<span class="co"># install.packages(c("dplyr", "ggplot2", "AMR", "cleaner"))</span></code></pre></div>
-</div>
-</div>
-<div class="section level2">
-<h2 id="creation-of-data">Creation of data<a class="anchor" aria-label="anchor" href="#creation-of-data"></a>
-</h2>
-<p>We will create some fake example data to use for analysis. For AMR
-data analysis, we need at least: a patient ID, name or code of a
-microorganism, a date and antimicrobial results (an antibiogram). It
-could also include a specimen type (e.g. to filter on blood or urine),
-the ward type (e.g. to filter on ICUs).</p>
-<p>With additional columns (like a hospital name, the patients gender of
-even [well-defined] clinical properties) you can do a comparative
-analysis, as this tutorial will demonstrate too.</p>
-<div class="section level3">
-<h3 id="patients">Patients<a class="anchor" aria-label="anchor" href="#patients"></a>
-</h3>
-<p>To start with patients, we need a unique list of patients.</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">patients</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/unlist.html" class="external-link">unlist</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">LETTERS</span>, <span class="va">paste0</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">10</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p>The <code>LETTERS</code> object is available in R - it’s a vector
-with 26 characters: <code>A</code> to <code>Z</code>. The
-<code>patients</code> object we just created is now a vector of length
-260, with values (patient IDs) varying from <code>A1</code> to
-<code>Z10</code>. Now we we also set the gender of our patients, by
-putting the ID and the gender in a table:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">patients_table</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>patient_id <span class="op">=</span> <span class="va">patients</span>,
- gender <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"M"</span>, <span class="fl">135</span><span class="op">)</span>,
- <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"F"</span>, <span class="fl">125</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p>The first 135 patient IDs are now male, the other 125 are female.</p>
-</div>
-<div class="section level3">
-<h3 id="dates">Dates<a class="anchor" aria-label="anchor" href="#dates"></a>
-</h3>
-<p>Let’s pretend that our data consists of blood cultures isolates from
-between 1 January 2010 and 1 January 2018.</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">dates</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/as.Date.html" class="external-link">as.Date</a></span><span class="op">(</span><span class="st">"2010-01-01"</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/as.Date.html" class="external-link">as.Date</a></span><span class="op">(</span><span class="st">"2018-01-01"</span><span class="op">)</span>, by <span class="op">=</span> <span class="st">"day"</span><span class="op">)</span></code></pre></div>
-<p>This <code>dates</code> object now contains all days in our date
-range.</p>
-<div class="section level5">
-<h5 id="microorganisms">Microorganisms<a class="anchor" aria-label="anchor" href="#microorganisms"></a>
-</h5>
-<p>For this tutorial, we will uses four different microorganisms:
-<em>Escherichia coli</em>, <em>Staphylococcus aureus</em>,
-<em>Streptococcus pneumoniae</em>, and <em>Klebsiella
-pneumoniae</em>:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">bacteria</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Escherichia coli"</span>, <span class="st">"Staphylococcus aureus"</span>,
- <span class="st">"Streptococcus pneumoniae"</span>, <span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span></code></pre></div>
-</div>
-</div>
-<div class="section level3">
-<h3 id="put-everything-together">Put everything together<a class="anchor" aria-label="anchor" href="#put-everything-together"></a>
-</h3>
-<p>Using the <code><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample()</a></code> function, we can randomly select
-items from all objects we defined earlier. To let our fake data reflect
-reality a bit, we will also approximately define the probabilities of
-bacteria and the antibiotic results, using the <code><a href="../reference/random.html">random_rsi()</a></code>
-function.</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">sample_size</span> <span class="op"><-</span> <span class="fl">20000</span>
-<span class="va">data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>date <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="va">dates</span>, size <span class="op">=</span> <span class="va">sample_size</span>, replace <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,
- patient_id <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="va">patients</span>, size <span class="op">=</span> <span class="va">sample_size</span>, replace <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,
- hospital <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Hospital A"</span>,
- <span class="st">"Hospital B"</span>,
- <span class="st">"Hospital C"</span>,
- <span class="st">"Hospital D"</span><span class="op">)</span>,
- size <span class="op">=</span> <span class="va">sample_size</span>, replace <span class="op">=</span> <span class="cn">TRUE</span>,
- prob <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.30</span>, <span class="fl">0.35</span>, <span class="fl">0.15</span>, <span class="fl">0.20</span><span class="op">)</span><span class="op">)</span>,
- bacteria <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="va">bacteria</span>, size <span class="op">=</span> <span class="va">sample_size</span>, replace <span class="op">=</span> <span class="cn">TRUE</span>,
- prob <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.50</span>, <span class="fl">0.25</span>, <span class="fl">0.15</span>, <span class="fl">0.10</span><span class="op">)</span><span class="op">)</span>,
- AMX <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="va">sample_size</span>, prob_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.35</span>, <span class="fl">0.60</span>, <span class="fl">0.05</span><span class="op">)</span><span class="op">)</span>,
- AMC <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="va">sample_size</span>, prob_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.15</span>, <span class="fl">0.75</span>, <span class="fl">0.10</span><span class="op">)</span><span class="op">)</span>,
- CIP <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="va">sample_size</span>, prob_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.20</span>, <span class="fl">0.80</span>, <span class="fl">0.00</span><span class="op">)</span><span class="op">)</span>,
- GEN <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="va">sample_size</span>, prob_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.08</span>, <span class="fl">0.92</span>, <span class="fl">0.00</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p>Using the <code><a href="https://dplyr.tidyverse.org/reference/mutate-joins.html" class="external-link">left_join()</a></code> function from the
-<code>dplyr</code> package, we can ‘map’ the gender to the patient ID
-using the <code>patients_table</code> object we created earlier:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op"><-</span> <span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate-joins.html" class="external-link">left_join</a></span><span class="op">(</span><span class="va">patients_table</span><span class="op">)</span></code></pre></div>
-<p>The resulting data set contains 20,000 blood culture isolates. With
-the <code><a href="https://rdrr.io/r/utils/head.html" class="external-link">head()</a></code> function we can preview the first 6 rows of this
-data set:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></code></pre></div>
-<table class="table">
-<colgroup>
-<col width="13%">
-<col width="13%">
-<col width="13%">
-<col width="26%">
-<col width="5%">
-<col width="5%">
-<col width="5%">
-<col width="5%">
-<col width="9%">
-</colgroup>
-<thead><tr class="header">
-<th align="center">date</th>
-<th align="center">patient_id</th>
-<th align="center">hospital</th>
-<th align="center">bacteria</th>
-<th align="center">AMX</th>
-<th align="center">AMC</th>
-<th align="center">CIP</th>
-<th align="center">GEN</th>
-<th align="center">gender</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">2012-05-19</td>
-<td align="center">T9</td>
-<td align="center">Hospital D</td>
-<td align="center">Escherichia coli</td>
-<td align="center">I</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">F</td>
-</tr>
-<tr class="even">
-<td align="center">2014-09-16</td>
-<td align="center">D6</td>
-<td align="center">Hospital C</td>
-<td align="center">Klebsiella pneumoniae</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="odd">
-<td align="center">2017-03-16</td>
-<td align="center">D10</td>
-<td align="center">Hospital C</td>
-<td align="center">Escherichia coli</td>
-<td align="center">S</td>
-<td align="center">I</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">M</td>
-</tr>
-<tr class="even">
-<td align="center">2014-05-04</td>
-<td align="center">S5</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">S</td>
-<td align="center">S</td>
-<td align="center">F</td>
-</tr>
-<tr class="odd">
-<td align="center">2011-06-06</td>
-<td align="center">N10</td>
-<td align="center">Hospital B</td>
-<td align="center">Staphylococcus aureus</td>
-<td align="center">I</td>
-<td align="center">I</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">F</td>
-</tr>
-<tr class="even">
-<td align="center">2016-05-12</td>
-<td align="center">R3</td>
-<td align="center">Hospital D</td>
-<td align="center">Klebsiella pneumoniae</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>
-</tr>
-</tbody>
-</table>
-<p>Now, let’s start the cleaning and the analysis!</p>
-</div>
-</div>
-<div class="section level2">
-<h2 id="cleaning-the-data">Cleaning the data<a class="anchor" aria-label="anchor" href="#cleaning-the-data"></a>
-</h2>
-<p>We also created a package dedicated to data cleaning and checking,
-called the <code>cleaner</code> package. It <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq()</a></code> function
-can be used to create frequency tables.</p>
-<p>For example, for the <code>gender</code> variable:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></code></pre></div>
-<p><strong>Frequency table</strong></p>
-<p>Class: character<br>
-Length: 20,000<br>
-Available: 20,000 (100%, NA: 0 = 0%)<br>
-Unique: 2</p>
-<p>Shortest: 1<br>
-Longest: 1</p>
-<table class="table">
-<thead><tr class="header">
-<th align="left"></th>
-<th align="left">Item</th>
-<th align="right">Count</th>
-<th align="right">Percent</th>
-<th align="right">Cum. Count</th>
-<th align="right">Cum. Percent</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">1</td>
-<td align="left">M</td>
-<td align="right">10,452</td>
-<td align="right">52.26%</td>
-<td align="right">10,452</td>
-<td align="right">52.26%</td>
-</tr>
-<tr class="even">
-<td align="left">2</td>
-<td align="left">F</td>
-<td align="right">9,548</td>
-<td align="right">47.74%</td>
-<td align="right">20,000</td>
-<td align="right">100.00%</td>
-</tr>
-</tbody>
-</table>
-<p>So, we can draw at least two conclusions immediately. From a data
-scientists perspective, the data looks clean: only values <code>M</code>
-and <code>F</code>. From a researchers 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" class="external-link">mutate()</a></code> function
-of the <code>dplyr</code> package makes this really easy:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op"><-</span> <span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>bacteria <span class="op">=</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p>We also want to transform the antibiotics, because in real life data
-we don’t know if they are really clean. The <code><a href="../reference/as.rsi.html">as.rsi()</a></code>
-function ensures reliability and reproducibility in these kind of
-variables. The <code><a href="../reference/as.rsi.html">is.rsi.eligible()</a></code> can check which columns
-are probably columns with R/SI test results. Using <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code>
-and <code><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across()</a></code>, we can apply the transformation to the formal
-<code><rsi></code> class:</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/as.rsi.html">is.rsi.eligible</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span>
-<span class="co"># [1] FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE</span>
-<span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span><span class="op">[</span><span class="fu"><a href="../reference/as.rsi.html">is.rsi.eligible</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span><span class="op">]</span>
-<span class="co"># [1] "AMX" "AMC" "CIP" "GEN"</span>
-
-<span class="va">data</span> <span class="op"><-</span> <span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu">where</span><span class="op">(</span><span class="va">is.rsi.eligible</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p>Finally, we will apply <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">EUCAST
-rules</a> on our antimicrobial results. In Europe, most medical
-microbiological laboratories already apply these rules. Our package
-features their latest insights on intrinsic resistance and exceptional
-phenotypes. Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function can also
-apply additional rules, like forcing
-<help title="ATC: J01CA01">ampicillin</help> = R when
-<help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p>
-<p>Because the amoxicillin (column <code>AMX</code>) and
-amoxicillin/clavulanic acid (column <code>AMC</code>) in our data were
-generated randomly, some rows will undoubtedly contain AMX = S and AMC =
-R, which is technically impossible. The <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
-fixes this:</p>
-<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op"><-</span> <span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">data</span>, col_mo <span class="op">=</span> <span class="st">"bacteria"</span>, rules <span class="op">=</span> <span class="st">"all"</span><span class="op">)</span></code></pre></div>
-</div>
-<div class="section level2">
-<h2 id="adding-new-variables">Adding new variables<a class="anchor" aria-label="anchor" href="#adding-new-variables"></a>
-</h2>
-<p>Now that we have the microbial ID, we can add some taxonomic
-properties:</p>
-<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op"><-</span> <span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>gramstain <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span>,
- genus <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span>,
- species <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<div class="section level3">
-<h3 id="first-isolates">First isolates<a class="anchor" aria-label="anchor" href="#first-isolates"></a>
-</h3>
-<p>We also need to know which isolates we can <em>actually</em> use for
-analysis.</p>
-<p>To conduct an analysis of antimicrobial resistance, you must <a href="https:/pubmed.ncbi.nlm.nih.gov/17304462/">only include the first
-isolate of every patient per episode</a> (Hindler <em>et al.</em>, Clin
-Infect Dis. 2007). If you would not do this, you could easily get an
-overestimate or underestimate of the resistance of an antibiotic.
-Imagine that a patient was admitted with an MRSA and that it was found
-in 5 different blood cultures the following weeks (yes, some countries
-like the Netherlands have these blood drawing policies). The resistance
-percentage of oxacillin of all isolates would be overestimated, because
-you included this MRSA more than once. It would clearly be <a href="https://en.wikipedia.org/wiki/Selection_bias" class="external-link">selection
-bias</a>.</p>
-<p>The Clinical and Laboratory Standards Institute (CLSI) appoints this
-as follows:</p>
-<blockquote>
-<p><em>(…) When preparing a cumulative antibiogram to guide clinical
-decisions about empirical antimicrobial therapy of initial infections,
-<strong>only the first isolate of a given species per patient, per
-analysis period (eg, one year) should be included, irrespective of body
-site, antimicrobial susceptibility profile, or other phenotypical
-characteristics (eg, biotype)</strong>. The first isolate is easily
-identified, and cumulative antimicrobial susceptibility test data
-prepared using the first isolate are generally comparable to cumulative
-antimicrobial susceptibility test data calculated by other methods,
-providing duplicate isolates are excluded.</em> <br><a href="https://clsi.org/standards/products/microbiology/documents/m39/" class="external-link">M39-A4
-Analysis and Presentation of Cumulative Antimicrobial Susceptibility
-Test Data, 4th Edition. CLSI, 2014. Chapter 6.4</a></p>
-</blockquote>
-<p>This <code>AMR</code> package includes this methodology with the
-<code><a href="../reference/first_isolate.html">first_isolate()</a></code> function and is able to apply the four
-different methods as defined by <a href="https://academic.oup.com/cid/article/44/6/867/364325" class="external-link">Hindler
-<em>et al.</em> in 2007</a>: phenotype-based, episode-based,
-patient-based, isolate-based. The right method depends on your goals and
-analysis, but the default phenotype-based method is in any case the
-method to properly correct for most duplicate isolates. This method also
-takes into account the antimicrobial susceptibility test results using
-<code>all_microbials()</code>. Read more about the methods on the
-<code><a href="../reference/first_isolate.html">first_isolate()</a></code> page.</p>
-<p>The outcome of the function can easily be added to our data:</p>
-<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op"><-</span> <span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>first <span class="op">=</span> <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span>info <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span>
-<span class="co"># Determining first isolates using an episode length of 365 days</span>
-<span class="co"># ℹ Using column 'bacteria' as input for `col_mo`.</span>
-<span class="co"># ℹ Using column 'date' as input for `col_date`.</span>
-<span class="co"># ℹ Using column 'patient_id' as input for `col_patient_id`.</span>
-<span class="co"># Basing inclusion on all antimicrobial results, using a points threshold of</span>
-<span class="co"># 2</span>
-<span class="co"># => Found 10,708 'phenotype-based' first isolates (53.5% of total where a</span>
-<span class="co"># microbial ID was available)</span></code></pre></div>
-<p>So only 53.5% is suitable for resistance analysis! We can now filter
-on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code> function, also from the
-<code>dplyr</code> package:</p>
-<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><-</span> <span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">first</span> <span class="op">==</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div>
-<p>For future use, the above two syntaxes can be shortened:</p>
-<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><-</span> <span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
-<p>So we end up with 10,708 isolates for analysis. Now our data looks
-like:</p>
-<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">data_1st</span><span class="op">)</span></code></pre></div>
-<table style="width:100%;" class="table">
-<colgroup>
-<col width="2%">
-<col width="9%">
-<col width="9%">
-<col width="9%">
-<col width="10%">
-<col width="3%">
-<col width="3%">
-<col width="3%">
-<col width="3%">
-<col width="6%">
-<col width="11%">
-<col width="12%">
-<col width="9%">
-<col width="5%">
-</colgroup>
-<thead><tr class="header">
-<th align="left"></th>
-<th align="center">date</th>
-<th align="center">patient_id</th>
-<th align="center">hospital</th>
-<th align="center">bacteria</th>
-<th align="center">AMX</th>
-<th align="center">AMC</th>
-<th align="center">CIP</th>
-<th align="center">GEN</th>
-<th align="center">gender</th>
-<th align="center">gramstain</th>
-<th align="center">genus</th>
-<th align="center">species</th>
-<th align="center">first</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">2</td>
-<td align="center">2014-09-16</td>
-<td align="center">D6</td>
-<td align="center">Hospital C</td>
-<td align="center">B_KLBSL_PNMN</td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center">M</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="even">
-<td align="left">5</td>
-<td align="center">2011-06-06</td>
-<td align="center">N10</td>
-<td align="center">Hospital B</td>
-<td align="center">B_STPHY_AURS</td>
-<td align="center">I</td>
-<td align="center">I</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">F</td>
-<td align="center">Gram-positive</td>
-<td align="center">Staphylococcus</td>
-<td align="center">aureus</td>
-<td align="center">TRUE</td>
-</tr>
-<tr class="odd">
-<td align="left">6</td>
-<td align="center">2016-05-12</td>
-<td align="center">R3</td>
-<td align="center">Hospital D</td>
-<td align="center">B_KLBSL_PNMN</td>
-<td align="center">R</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="even">
-<td align="left">8</td>
-<td align="center">2010-02-19</td>
-<td align="center">U1</td>
-<td align="center">Hospital D</td>
-<td align="center">B_ESCHR_COLI</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>
-<td align="center">Gram-negative</td>
-<td align="center">Escherichia</td>
-<td align="center">coli</td>
-<td align="center">TRUE</td>
-</tr>
-<tr class="odd">
-<td align="left">11</td>
-<td align="center">2012-02-09</td>
-<td align="center">G7</td>
-<td align="center">Hospital D</td>
-<td align="center">B_STPHY_AURS</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">M</td>
-<td align="center">Gram-positive</td>
-<td align="center">Staphylococcus</td>
-<td align="center">aureus</td>
-<td align="center">TRUE</td>
-</tr>
-<tr class="even">
-<td align="left">12</td>
-<td align="center">2012-04-12</td>
-<td align="center">Q10</td>
-<td align="center">Hospital D</td>
-<td align="center">B_STRPT_PNMN</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center">F</td>
-<td align="center">Gram-positive</td>
-<td align="center">Streptococcus</td>
-<td align="center">pneumoniae</td>
-<td align="center">TRUE</td>
-</tr>
-</tbody>
-</table>
-<p>Time for the analysis!</p>
-</div>
-</div>
-<div class="section level2">
-<h2 id="analysing-the-data">Analysing the data<a class="anchor" aria-label="anchor" href="#analysing-the-data"></a>
-</h2>
-<p>You might want to start by getting an idea of how the data is
-distributed. It’s an important start, because it also decides how you
-will continue your analysis. Although this package contains a convenient
-function to make frequency tables, exploratory data analysis (EDA) is
-not the primary scope of this package. Use a package like <a href="https://cran.r-project.org/package=DataExplorer" class="external-link"><code>DataExplorer</code></a>
-for that, or read the free online book <a href="https://bookdown.org/rdpeng/exdata/" class="external-link">Exploratory Data Analysis
-with R</a> by Roger D. Peng.</p>
-<div class="section level3">
-<h3 id="dispersion-of-species">Dispersion of species<a class="anchor" aria-label="anchor" href="#dispersion-of-species"></a>
-</h3>
-<p>To just get an idea how the species are distributed, create a
-frequency table with our <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq()</a></code> function. We created the
-<code>genus</code> and <code>species</code> column earlier based on the
-microbial ID. With <code><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste()</a></code>, we can concatenate them
-together.</p>
-<p>The <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq()</a></code> function can be used like the base R language
-was intended:</p>
-<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="va">data_1st</span><span class="op">$</span><span class="va">genus</span>, <span class="va">data_1st</span><span class="op">$</span><span class="va">species</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p>Or can be used like the <code>dplyr</code> way, which is easier
-readable:</p>
-<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="va">genus</span>, <span class="va">species</span><span class="op">)</span></code></pre></div>
-<p><strong>Frequency table</strong></p>
-<p>Class: character<br>
-Length: 10,708<br>
-Available: 10,708 (100%, NA: 0 = 0%)<br>
-Unique: 4</p>
-<p>Shortest: 16<br>
-Longest: 24</p>
-<table class="table">
-<colgroup>
-<col width="4%">
-<col width="36%">
-<col width="9%">
-<col width="12%">
-<col width="16%">
-<col width="19%">
-</colgroup>
-<thead><tr class="header">
-<th align="left"></th>
-<th align="left">Item</th>
-<th align="right">Count</th>
-<th align="right">Percent</th>
-<th align="right">Cum. Count</th>
-<th align="right">Cum. Percent</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">1</td>
-<td align="left">Escherichia coli</td>
-<td align="right">4,664</td>
-<td align="right">43.56%</td>
-<td align="right">4,664</td>
-<td align="right">43.56%</td>
-</tr>
-<tr class="even">
-<td align="left">2</td>
-<td align="left">Staphylococcus aureus</td>
-<td align="right">2,713</td>
-<td align="right">25.34%</td>
-<td align="right">7,377</td>
-<td align="right">68.89%</td>
-</tr>
-<tr class="odd">
-<td align="left">3</td>
-<td align="left">Streptococcus pneumoniae</td>
-<td align="right">2,154</td>
-<td align="right">20.12%</td>
-<td align="right">9,531</td>
-<td align="right">89.01%</td>
-</tr>
-<tr class="even">
-<td align="left">4</td>
-<td align="left">Klebsiella pneumoniae</td>
-<td align="right">1,177</td>
-<td align="right">10.99%</td>
-<td align="right">10,708</td>
-<td align="right">100.00%</td>
-</tr>
-</tbody>
-</table>
-</div>
-<div class="section level3">
-<h3 id="overview-of-different-bugdrug-combinations">Overview of different bug/drug combinations<a class="anchor" aria-label="anchor" href="#overview-of-different-bugdrug-combinations"></a>
-</h3>
-<p>Using <a href="https://tidyselect.r-lib.org/reference/language.html" class="external-link">tidyverse
-selections</a>, you can also select or filter columns based on the
-antibiotic class they are in:</p>
-<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<pre><code><span class="co"># ℹ For `aminoglycosides()` using column 'GEN' (gentamicin)</span></code></pre>
-<table class="table">
-<colgroup>
-<col width="9%">
-<col width="9%">
-<col width="9%">
-<col width="11%">
-<col width="3%">
-<col width="3%">
-<col width="3%">
-<col width="3%">
-<col width="6%">
-<col width="11%">
-<col width="11%">
-<col width="9%">
-<col width="5%">
-</colgroup>
-<thead><tr class="header">
-<th align="center">date</th>
-<th align="center">patient_id</th>
-<th align="center">hospital</th>
-<th align="center">bacteria</th>
-<th align="center">AMX</th>
-<th align="center">AMC</th>
-<th align="center">CIP</th>
-<th align="center">GEN</th>
-<th align="center">gender</th>
-<th align="center">gramstain</th>
-<th align="center">genus</th>
-<th align="center">species</th>
-<th align="center">first</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">2012-04-12</td>
-<td align="center">Q10</td>
-<td align="center">Hospital D</td>
-<td align="center">B_STRPT_PNMN</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center">F</td>
-<td align="center">Gram-positive</td>
-<td align="center">Streptococcus</td>
-<td align="center">pneumoniae</td>
-<td align="center">TRUE</td>
-</tr>
-<tr class="even">
-<td align="center">2011-03-17</td>
-<td align="center">Z4</td>
-<td align="center">Hospital C</td>
-<td align="center">B_STRPT_PNMN</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">F</td>
-<td align="center">Gram-positive</td>
-<td align="center">Streptococcus</td>
-<td align="center">pneumoniae</td>
-<td align="center">TRUE</td>
-</tr>
-<tr class="odd">
-<td align="center">2010-09-07</td>
-<td align="center">P9</td>
-<td align="center">Hospital B</td>
-<td align="center">B_ESCHR_COLI</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">F</td>
-<td align="center">Gram-negative</td>
-<td align="center">Escherichia</td>
-<td align="center">coli</td>
-<td align="center">TRUE</td>
-</tr>
-<tr class="even">
-<td align="center">2013-08-06</td>
-<td align="center">Z6</td>
-<td align="center">Hospital A</td>
-<td align="center">B_ESCHR_COLI</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center">F</td>
-<td align="center">Gram-negative</td>
-<td align="center">Escherichia</td>
-<td align="center">coli</td>
-<td align="center">TRUE</td>
-</tr>
-<tr class="odd">
-<td align="center">2017-02-20</td>
-<td align="center">K5</td>
-<td align="center">Hospital D</td>
-<td align="center">B_ESCHR_COLI</td>
-<td align="center">S</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-negative</td>
-<td align="center">Escherichia</td>
-<td align="center">coli</td>
-<td align="center">TRUE</td>
-</tr>
-<tr class="even">
-<td align="center">2015-08-23</td>
-<td align="center">G1</td>
-<td align="center">Hospital A</td>
-<td align="center">B_STRPT_PNMN</td>
-<td align="center">S</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">TRUE</td>
-</tr>
-</tbody>
-</table>
-<p>If you want to get a quick glance of the number of isolates in
-different bug/drug combinations, you can use the
-<code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> function:</p>
-<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="op">)</span> <span class="co"># show first 6 rows</span></code></pre></div>
-<pre><code><span class="co"># ℹ Using column 'bacteria' as input for `col_mo`.</span></code></pre>
-<table class="table">
-<thead><tr class="header">
-<th align="center">mo</th>
-<th align="center">ab</th>
-<th align="center">S</th>
-<th align="center">I</th>
-<th align="center">R</th>
-<th align="center">total</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">E. coli</td>
-<td align="center">AMX</td>
-<td align="center">2171</td>
-<td align="center">132</td>
-<td align="center">2361</td>
-<td align="center">4664</td>
-</tr>
-<tr class="even">
-<td align="center">E. coli</td>
-<td align="center">AMC</td>
-<td align="center">3389</td>
-<td align="center">168</td>
-<td align="center">1107</td>
-<td align="center">4664</td>
-</tr>
-<tr class="odd">
-<td align="center">E. coli</td>
-<td align="center">CIP</td>
-<td align="center">3428</td>
-<td align="center">0</td>
-<td align="center">1236</td>
-<td align="center">4664</td>
-</tr>
-<tr class="even">
-<td align="center">E. coli</td>
-<td align="center">GEN</td>
-<td align="center">4083</td>
-<td align="center">0</td>
-<td align="center">581</td>
-<td align="center">4664</td>
-</tr>
-<tr class="odd">
-<td align="center">K. pneumoniae</td>
-<td align="center">AMX</td>
-<td align="center">0</td>
-<td align="center">0</td>
-<td align="center">1177</td>
-<td align="center">1177</td>
-</tr>
-<tr class="even">
-<td align="center">K. pneumoniae</td>
-<td align="center">AMC</td>
-<td align="center">935</td>
-<td align="center">30</td>
-<td align="center">212</td>
-<td align="center">1177</td>
-</tr>
-</tbody>
-</table>
-<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
-<pre><code><span class="co"># ℹ For `aminoglycosides()` using column 'GEN' (gentamicin)</span>
-<span class="co"># ℹ Using column 'bacteria' as input for `col_mo`.</span></code></pre>
-<table class="table">
-<thead><tr class="header">
-<th align="center">mo</th>
-<th align="center">ab</th>
-<th align="center">S</th>
-<th align="center">I</th>
-<th align="center">R</th>
-<th align="center">total</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">E. coli</td>
-<td align="center">GEN</td>
-<td align="center">4083</td>
-<td align="center">0</td>
-<td align="center">581</td>
-<td align="center">4664</td>
-</tr>
-<tr class="even">
-<td align="center">K. pneumoniae</td>
-<td align="center">GEN</td>
-<td align="center">1074</td>
-<td align="center">0</td>
-<td align="center">103</td>
-<td align="center">1177</td>
-</tr>
-<tr class="odd">
-<td align="center">S. aureus</td>
-<td align="center">GEN</td>
-<td align="center">2426</td>
-<td align="center">0</td>
-<td align="center">287</td>
-<td align="center">2713</td>
-</tr>
-<tr class="even">
-<td align="center">S. pneumoniae</td>
-<td align="center">GEN</td>
-<td align="center">0</td>
-<td align="center">0</td>
-<td align="center">2154</td>
-<td align="center">2154</td>
-</tr>
-</tbody>
-</table>
-<p>This will only give you the crude numbers in the data. To calculate
-antimicrobial resistance in a more sensible way, also by correcting for
-too few results, we use the <code><a href="../reference/proportion.html">resistance()</a></code> and
-<code><a href="../reference/proportion.html">susceptibility()</a></code> functions.</p>
-</div>
-<div class="section level3">
-<h3 id="resistance-percentages">Resistance percentages<a class="anchor" aria-label="anchor" href="#resistance-percentages"></a>
-</h3>
-<p>The functions <code><a href="../reference/proportion.html">resistance()</a></code> and
-<code><a href="../reference/proportion.html">susceptibility()</a></code> can be used to calculate antimicrobial
-resistance or susceptibility. For more specific analyses, the functions
-<code><a href="../reference/proportion.html">proportion_S()</a></code>, <code><a href="../reference/proportion.html">proportion_SI()</a></code>,
-<code><a href="../reference/proportion.html">proportion_I()</a></code>, <code><a href="../reference/proportion.html">proportion_IR()</a></code> and
-<code><a href="../reference/proportion.html">proportion_R()</a></code> can be used to determine the proportion of a
-specific antimicrobial outcome.</p>
-<p>All these functions contain a <code>minimum</code> argument, denoting
-the minimum required number of test results for returning a value. These
-functions will otherwise return <code>NA</code>. The default is
-<code>minimum = 30</code>, following the <a href="https://clsi.org/standards/products/microbiology/documents/m39/" class="external-link">CLSI
-M39-A4 guideline</a> for applying microbial epidemiology.</p>
-<p>As per the EUCAST guideline of 2019, we calculate resistance as the
-proportion of R (<code><a href="../reference/proportion.html">proportion_R()</a></code>, equal to
-<code><a href="../reference/proportion.html">resistance()</a></code>) and susceptibility as the proportion of S and
-I (<code><a href="../reference/proportion.html">proportion_SI()</a></code>, equal to
-<code><a href="../reference/proportion.html">susceptibility()</a></code>). These functions can be used on their
-own:</p>
-<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span>
-<span class="co"># [1] 0.5473478</span></code></pre></div>
-<p>Or can be used in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> and
-<code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
-<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>amoxicillin <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<table class="table">
-<thead><tr class="header">
-<th align="center">hospital</th>
-<th align="center">amoxicillin</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">Hospital A</td>
-<td align="center">0.5482456</td>
-</tr>
-<tr class="even">
-<td align="center">Hospital B</td>
-<td align="center">0.5499477</td>
-</tr>
-<tr class="odd">
-<td align="center">Hospital C</td>
-<td align="center">0.5403687</td>
-</tr>
-<tr class="even">
-<td align="center">Hospital D</td>
-<td align="center">0.5464842</td>
-</tr>
-</tbody>
-</table>
-<p>Of course it would be very convenient to know the number of isolates
-responsible for the percentages. For that purpose the
-<code><a href="../reference/count.html">n_rsi()</a></code> can be used, which works exactly like
-<code><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct()</a></code> from the <code>dplyr</code> package. It counts
-all isolates available for every group (i.e. values S, I or R):</p>
-<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>amoxicillin <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span>,
- available <span class="op">=</span> <span class="fu"><a href="../reference/count.html">n_rsi</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<table class="table">
-<thead><tr class="header">
-<th align="center">hospital</th>
-<th align="center">amoxicillin</th>
-<th align="center">available</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">Hospital A</td>
-<td align="center">0.5482456</td>
-<td align="center">3192</td>
-</tr>
-<tr class="even">
-<td align="center">Hospital B</td>
-<td align="center">0.5499477</td>
-<td align="center">3824</td>
-</tr>
-<tr class="odd">
-<td align="center">Hospital C</td>
-<td align="center">0.5403687</td>
-<td align="center">1573</td>
-</tr>
-<tr class="even">
-<td align="center">Hospital D</td>
-<td align="center">0.5464842</td>
-<td align="center">2119</td>
-</tr>
-</tbody>
-</table>
-<p>These functions can also be used to get the proportion of multiple
-antibiotics, to calculate empiric susceptibility of combination
-therapies very easily:</p>
-<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">genus</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>amoxiclav <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">susceptibility</a></span><span class="op">(</span><span class="va">AMC</span><span class="op">)</span>,
- gentamicin <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">susceptibility</a></span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span>,
- amoxiclav_genta <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">susceptibility</a></span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<table class="table">
-<thead><tr class="header">
-<th align="center">genus</th>
-<th align="center">amoxiclav</th>
-<th align="center">gentamicin</th>
-<th align="center">amoxiclav_genta</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">Escherichia</td>
-<td align="center">0.7626501</td>
-<td align="center">0.8754288</td>
-<td align="center">0.9774871</td>
-</tr>
-<tr class="even">
-<td align="center">Klebsiella</td>
-<td align="center">0.8198811</td>
-<td align="center">0.9124894</td>
-<td align="center">0.9821580</td>
-</tr>
-<tr class="odd">
-<td align="center">Staphylococcus</td>
-<td align="center">0.7983782</td>
-<td align="center">0.8942130</td>
-<td align="center">0.9834132</td>
-</tr>
-<tr class="even">
-<td align="center">Streptococcus</td>
-<td align="center">0.5329619</td>
-<td align="center">0.0000000</td>
-<td align="center">0.5329619</td>
-</tr>
-</tbody>
-</table>
-<p>Or if you are curious for the resistance within certain antibiotic
-classes, use a antibiotic class selector such as
-<code><a href="../reference/antibiotic_class_selectors.html">penicillins()</a></code>, which automatically will include the columns
-<code>AMX</code> and <code>AMC</code> of our data:</p>
-<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># group by hospital</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># / -> select all penicillins in the data for calculation</span>
- <span class="co"># | / -> use resistance() for all peni's per hospital</span>
- <span class="co"># | | / -> print as percentages</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">penicillins</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">resistance</span>, as_percent <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># format the antibiotic column names, using so-called snake case,</span>
- <span class="co"># so 'Amoxicillin/clavulanic acid' becomes 'amoxicillin_clavulanic_acid'</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/rename.html" class="external-link">rename_with</a></span><span class="op">(</span><span class="va">set_ab_names</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">penicillins</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<table class="table">
-<thead><tr class="header">
-<th align="left">hospital</th>
-<th align="right">amoxicillin</th>
-<th align="right">amoxicillin_clavulanic_acid</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">Hospital A</td>
-<td align="right">54.8%</td>
-<td align="right">28.0%</td>
-</tr>
-<tr class="even">
-<td align="left">Hospital B</td>
-<td align="right">55.0%</td>
-<td align="right">26.3%</td>
-</tr>
-<tr class="odd">
-<td align="left">Hospital C</td>
-<td align="right">54.0%</td>
-<td align="right">26.2%</td>
-</tr>
-<tr class="even">
-<td align="left">Hospital D</td>
-<td align="right">54.6%</td>
-<td align="right">26.4%</td>
-</tr>
-</tbody>
-</table>
-<p>To make a transition to the next part, let’s see how differences in
-the previously calculated combination therapies could be plotted:</p>
-<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">genus</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="st">"1. Amoxi/clav"</span> <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">susceptibility</a></span><span class="op">(</span><span class="va">AMC</span><span class="op">)</span>,
- <span class="st">"2. Gentamicin"</span> <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">susceptibility</a></span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span>,
- <span class="st">"3. Amoxi/clav + genta"</span> <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">susceptibility</a></span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># pivot_longer() from the tidyr package "lengthens" data:</span>
- <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html" class="external-link">pivot_longer</a></span><span class="op">(</span><span class="op">-</span><span class="va">genus</span>, names_to <span class="op">=</span> <span class="st">"antibiotic"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">genus</span>,
- y <span class="op">=</span> <span class="va">value</span>,
- fill <span class="op">=</span> <span class="va">antibiotic</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html" class="external-link">geom_col</a></span><span class="op">(</span>position <span class="op">=</span> <span class="st">"dodge2"</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/plot%201-1.png" width="720"></p>
-</div>
-<div class="section level3">
-<h3 id="plots">Plots<a class="anchor" aria-label="anchor" href="#plots"></a>
-</h3>
-<p>To show results in plots, most R users would nowadays use the
-<code>ggplot2</code> package. This package lets you create plots in
-layers. You can read more about it <a href="https://ggplot2.tidyverse.org/" class="external-link">on their website</a>. A quick
-example would look like these syntaxes:</p>
-<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">a_data_set</span>,
- mapping <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">year</span>,
- y <span class="op">=</span> <span class="va">value</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html" class="external-link">geom_col</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"A title"</span>,
- subtitle <span class="op">=</span> <span class="st">"A subtitle"</span>,
- x <span class="op">=</span> <span class="st">"My X axis"</span>,
- y <span class="op">=</span> <span class="st">"My Y axis"</span><span class="op">)</span>
-
-<span class="co"># or as short as:</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">a_data_set</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html" class="external-link">geom_bar</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">year</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p>The <code>AMR</code> package contains functions to extend this
-<code>ggplot2</code> package, for example <code><a href="../reference/ggplot_rsi.html">geom_rsi()</a></code>. It
-automatically transforms data with <code><a href="../reference/count.html">count_df()</a></code> or
-<code><a href="../reference/proportion.html">proportion_df()</a></code> and show results in stacked bars. Its
-simplest and shortest example:</p>
-<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">data_1st</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="../reference/ggplot_rsi.html">geom_rsi</a></span><span class="op">(</span>translate_ab <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/plot%203-1.png" width="720"></p>
-<p>Omit the <code>translate_ab = FALSE</code> to have the antibiotic
-codes (AMX, AMC, CIP, GEN) translated to official WHO names
-(amoxicillin, amoxicillin/clavulanic acid, ciprofloxacin,
-gentamicin).</p>
-<p>If we group on e.g. the <code>genus</code> column and add some
-additional functions from our package, we can create this:</p>
-<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># group the data on `genus`</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">genus</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span>
- <span class="co"># create bars with genus on x axis</span>
- <span class="co"># it looks for variables with class `rsi`,</span>
- <span class="co"># of which we have 4 (earlier created with `as.rsi`)</span>
- <span class="fu"><a href="../reference/ggplot_rsi.html">geom_rsi</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"genus"</span><span class="op">)</span> <span class="op">+</span>
- <span class="co"># split plots on antibiotic</span>
- <span class="fu"><a href="../reference/ggplot_rsi.html">facet_rsi</a></span><span class="op">(</span>facet <span class="op">=</span> <span class="st">"antibiotic"</span><span class="op">)</span> <span class="op">+</span>
- <span class="co"># set colours to the R/SI interpretations (colour-blind friendly)</span>
- <span class="fu"><a href="../reference/ggplot_rsi.html">scale_rsi_colours</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
- <span class="co"># show percentages on y axis</span>
- <span class="fu"><a href="../reference/ggplot_rsi.html">scale_y_percent</a></span><span class="op">(</span>breaks <span class="op">=</span> <span class="fl">0</span><span class="op">:</span><span class="fl">4</span> <span class="op">*</span> <span class="fl">25</span><span class="op">)</span> <span class="op">+</span>
- <span class="co"># turn 90 degrees, to make it bars instead of columns</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/coord_flip.html" class="external-link">coord_flip</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
- <span class="co"># add labels</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"Resistance per genus and antibiotic"</span>,
- subtitle <span class="op">=</span> <span class="st">"(this is fake data)"</span><span class="op">)</span> <span class="op">+</span>
- <span class="co"># and print genus in italic to follow our convention</span>
- <span class="co"># (is now y axis because we turned the plot)</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>axis.text.y <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_text</a></span><span class="op">(</span>face <span class="op">=</span> <span class="st">"italic"</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/plot%204-1.png" width="720"></p>
-<p>To simplify this, we also created the <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code>
-function, which combines almost all above functions:</p>
-<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">genus</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/ggplot_rsi.html">ggplot_rsi</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"genus"</span>,
- facet <span class="op">=</span> <span class="st">"antibiotic"</span>,
- breaks <span class="op">=</span> <span class="fl">0</span><span class="op">:</span><span class="fl">4</span> <span class="op">*</span> <span class="fl">25</span>,
- datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/coord_flip.html" class="external-link">coord_flip</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/plot%205-1.png" width="720"></p>
-<div class="section level4">
-<h4 id="plotting-mic-and-disk-diffusion-values">Plotting MIC and disk diffusion values<a class="anchor" aria-label="anchor" href="#plotting-mic-and-disk-diffusion-values"></a>
-</h4>
-<p>The AMR package also extends the <code><a href="../reference/plot.html">plot()</a></code> and
-<code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">ggplot2::autoplot()</a></code> functions for plotting minimum
-inhibitory concentrations (MIC, created with <code><a href="../reference/as.mic.html">as.mic()</a></code>) and
-disk diffusion diameters (created with <code><a href="../reference/as.disk.html">as.disk()</a></code>).</p>
-<p>With the <code><a href="../reference/random.html">random_mic()</a></code> and <code><a href="../reference/random.html">random_disk()</a></code>
-functions, we can generate sampled values for the new data types (S3
-classes) <code><mic></code> and <code><disk></code>:</p>
-<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">mic_values</span> <span class="op"><-</span> <span class="fu"><a href="../reference/random.html">random_mic</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
-<span class="va">mic_values</span>
-<span class="co"># Class <mic></span>
-<span class="co"># [1] 4 4 <=0.001 2 256 32 32 0.002 4 </span>
-<span class="co"># [10] 0.002 0.125 0.005 <=0.001 4 0.002 128 16 32 </span>
-<span class="co"># [19] 256 8 256 0.25 0.025 0.25 0.002 64 <=0.001</span>
-<span class="co"># [28] 0.25 256 2 0.0625 2 0.25 0.01 0.005 2 </span>
-<span class="co"># [37] 0.0625 1 64 32 0.0625 0.002 0.0625 0.125 0.005 </span>
-<span class="co"># [46] 1 256 0.025 256 0.005 16 64 0.25 2 </span>
-<span class="co"># [55] 0.25 1 128 0.0625 0.005 0.5 0.5 <=0.001 0.025 </span>
-<span class="co"># [64] 2 64 0.005 0.0625 0.5 128 0.0625 8 4 </span>
-<span class="co"># [73] 0.002 128 0.01 <=0.001 2 64 64 128 32 </span>
-<span class="co"># [82] 0.005 256 64 0.0625 0.5 32 0.002 <=0.001 1 </span>
-<span class="co"># [91] 16 0.25 0.005 16 2 64 0.005 <=0.001 256 </span>
-<span class="co"># [100] 32</span></code></pre></div>
-<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># base R:</span>
-<span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">mic_values</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/mic_plots-1.png" width="720"></p>
-<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># ggplot2:</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">mic_values</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/mic_plots-2.png" width="720"></p>
-<p>But we could also be more specific, by generating MICs that are
-likely to be found in <em>E. coli</em> for ciprofloxacin:</p>
-<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">mic_values</span> <span class="op"><-</span> <span class="fu"><a href="../reference/random.html">random_mic</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">100</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span></code></pre></div>
-<p>For the <code><a href="../reference/plot.html">plot()</a></code> and <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot()</a></code> function, we
-can define the microorganism and an antimicrobial agent the same way.
-This will add the interpretation of those values according to a chosen
-guidelines (defaults to the latest EUCAST guideline).</p>
-<p>Default colours are colour-blind friendly, while maintaining the
-convention that e.g. ‘susceptible’ should be green and ‘resistant’
-should be red:</p>
-<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># base R:</span>
-<span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">mic_values</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/mic_plots_mo_ab-1.png" width="720"></p>
-<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># ggplot2:</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">mic_values</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/mic_plots_mo_ab-2.png" width="720"></p>
-<p>For disk diffusion values, there is not much of a difference in
-plotting:</p>
-<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">disk_values</span> <span class="op"><-</span> <span class="fu"><a href="../reference/random.html">random_disk</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">100</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span>
-<span class="co"># ℹ Function `as.mo()` is uncertain about "E. coli" (assuming Escherichia</span>
-<span class="co"># coli). Run `mo_uncertainties()` to review this.</span>
-<span class="va">disk_values</span>
-<span class="co"># Class <disk></span>
-<span class="co"># [1] 28 27 24 30 31 28 30 27 21 22 18 28 20 25 29 18 31 20 31 28 26 31 25 30 29</span>
-<span class="co"># [26] 21 20 25 24 29 23 26 27 26 20 18 29 21 17 31 18 30 30 26 19 17 18 23 30 31</span>
-<span class="co"># [51] 24 22 27 29 17 27 29 20 31 30 19 28 30 21 21 19 19 25 24 30 29 19 21 27 22</span>
-<span class="co"># [76] 30 17 26 21 18 31 29 26 21 23 31 27 30 19 18 20 20 23 28 25 24 31 18 17 28</span></code></pre></div>
-<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># base R:</span>
-<span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">disk_values</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/disk_plots-1.png" width="720"></p>
-<p>And when using the <code>ggplot2</code> package, but now choosing the
-latest implemented CLSI guideline (notice that the EUCAST-specific term
-“Susceptible, incr. exp.” has changed to “Intermediate”):</p>
-<div class="sourceCode" id="cb44"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">disk_values</span>,
- mo <span class="op">=</span> <span class="st">"E. coli"</span>,
- ab <span class="op">=</span> <span class="st">"cipro"</span>,
- guideline <span class="op">=</span> <span class="st">"CLSI"</span><span class="op">)</span></code></pre></div>
-<p><img src="AMR_files/figure-html/disk_plots_mo_ab-1.png" width="720"></p>
-</div>
-</div>
-<div class="section level3">
-<h3 id="independence-test">Independence test<a class="anchor" aria-label="anchor" href="#independence-test"></a>
-</h3>
-<p>The next example uses the <code>example_isolates</code> data set.
-This is a data set included with this package and contains 2,000
-microbial isolates with their full antibiograms. It reflects reality and
-can be used to practice AMR data analysis.</p>
-<p>We will compare the resistance to fosfomycin (column
-<code>FOS</code>) in hospital A and D. The input for the
-<code><a href="https://rdrr.io/r/stats/fisher.test.html" class="external-link">fisher.test()</a></code> can be retrieved with a transformation like
-this:</p>
-<div class="sourceCode" id="cb45"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># use package 'tidyr' to pivot data:</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://tidyr.tidyverse.org" class="external-link">tidyr</a></span><span class="op">)</span>
-
-<span class="va">check_FOS</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://tidyr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">hospital_id</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"A"</span>, <span class="st">"D"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://tidyr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># filter on only hospitals A and D</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">hospital_id</span>, <span class="va">FOS</span><span class="op">)</span> <span class="op"><a href="https://tidyr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># select the hospitals and fosfomycin</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://tidyr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># group on the hospitals</span>
- <span class="fu"><a href="../reference/count.html">count_df</a></span><span class="op">(</span>combine_SI <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op"><a href="https://tidyr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># count all isolates per group (hospital_id)</span>
- <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>names_from <span class="op">=</span> <span class="va">hospital_id</span>, <span class="co"># transform output so A and D are columns</span>
- values_from <span class="op">=</span> <span class="va">value</span><span class="op">)</span> <span class="op"><a href="https://tidyr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">A</span>, <span class="va">D</span><span class="op">)</span> <span class="op"><a href="https://tidyr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># and only select these columns</span>
- <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span> <span class="co"># transform to a good old matrix for fisher.test()</span>
-
-<span class="va">check_FOS</span>
-<span class="co"># A D</span>
-<span class="co"># [1,] 25 77</span>
-<span class="co"># [2,] 24 33</span></code></pre></div>
-<p>We can apply the test now with:</p>
-<div class="sourceCode" id="cb46"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># do Fisher's Exact Test</span>
-<span class="fu"><a href="https://rdrr.io/r/stats/fisher.test.html" class="external-link">fisher.test</a></span><span class="op">(</span><span class="va">check_FOS</span><span class="op">)</span>
-<span class="co"># </span>
-<span class="co"># Fisher's Exact Test for Count Data</span>
-<span class="co"># </span>
-<span class="co"># data: check_FOS</span>
-<span class="co"># p-value = 0.03104</span>
-<span class="co"># alternative hypothesis: true odds ratio is not equal to 1</span>
-<span class="co"># 95 percent confidence interval:</span>
-<span class="co"># 0.2111489 0.9485124</span>
-<span class="co"># sample estimates:</span>
-<span class="co"># odds ratio </span>
-<span class="co"># 0.4488318</span></code></pre></div>
-<p>As can be seen, the p value is 0.031, which means that the fosfomycin
-resistance found in isolates from patients in hospital A and D are
-really different.</p>
-</div>
-</div>
- </div>
-
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- <h1 data-toc-skip>How to apply EUCAST rules</h1>
-
-
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/EUCAST.Rmd" class="external-link"><code>vignettes/EUCAST.Rmd</code></a></small>
- <div class="hidden name"><code>EUCAST.Rmd</code></div>
-
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-
-
-
-<div class="section level2">
-<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
-</h2>
-<p>What are EUCAST rules? The European Committee on Antimicrobial
-Susceptibility Testing (EUCAST) states <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">on
-their website</a>:</p>
-<blockquote>
-<p><em>EUCAST expert rules are a tabulated collection of expert
-knowledge on intrinsic resistances, exceptional resistance phenotypes
-and interpretive rules that may be applied to antimicrobial
-susceptibility testing in order to reduce errors and make appropriate
-recommendations for reporting particular resistances.</em></p>
-</blockquote>
-<p>In Europe, a lot of medical microbiological laboratories already
-apply these rules (<a href="https://www.eurosurveillance.org/content/10.2807/1560-7917.ES2015.20.2.21008" class="external-link">Brown
-<em>et al.</em>, 2015</a>). Our package features their latest insights
-on intrinsic resistance and unusual phenotypes (v3.3, 2021).</p>
-<p>Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function we use for this
-purpose can also apply additional rules, like forcing
-<help title="ATC: J01CA01">ampicillin</help> = R in isolates when
-<help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p>
-</div>
-<div class="section level2">
-<h2 id="examples">Examples<a class="anchor" aria-label="anchor" href="#examples"></a>
-</h2>
-<p>These rules can be used to discard impossible bug-drug combinations
-in your data. For example, <em>Klebsiella</em> produces beta-lactamase
-that prevents ampicillin (or amoxicillin) from working against it. In
-other words, practically every strain of <em>Klebsiella</em> is
-resistant to ampicillin.</p>
-<p>Sometimes, laboratory data can still contain such strains with
-ampicillin being susceptible to ampicillin. This could be because an
-antibiogram is available before an identification is available, and the
-antibiogram is then not re-interpreted based on the identification
-(namely, <em>Klebsiella</em>). EUCAST expert rules solve this, that can
-be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">oops</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>,
- <span class="st">"Escherichia"</span><span class="op">)</span>,
- ampicillin <span class="op">=</span> <span class="st">"S"</span><span class="op">)</span>
-<span class="va">oops</span>
-<span class="co"># mo ampicillin</span>
-<span class="co"># 1 Klebsiella S</span>
-<span class="co"># 2 Escherichia S</span>
-
-<span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">oops</span>, info <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-<span class="co"># mo ampicillin</span>
-<span class="co"># 1 Klebsiella R</span>
-<span class="co"># 2 Escherichia S</span></code></pre></div>
-<p>A more convenient function is
-<code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> that uses the same guideline,
-but allows to check for one or more specific microorganisms or
-antibiotics:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,
- <span class="st">"ampicillin"</span><span class="op">)</span>
-<span class="co"># [1] TRUE FALSE</span>
-
-<span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>,
- <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"kanamycin"</span><span class="op">)</span><span class="op">)</span>
-<span class="co"># [1] TRUE FALSE</span></code></pre></div>
-<p>EUCAST rules can not only be used for correction, they can also be
-used for filling in known resistance and susceptibility based on results
-of other antimicrobials drugs. This process is called <em>interpretive
-reading</em>, is basically a form of imputation, and is part of the
-<code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span>,
- <span class="st">"Enterococcus faecalis"</span>,
- <span class="st">"Escherichia coli"</span>,
- <span class="st">"Klebsiella pneumoniae"</span>,
- <span class="st">"Pseudomonas aeruginosa"</span><span class="op">)</span>,
- VAN <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Vancomycin</span>
- AMX <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Amoxicillin</span>
- COL <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Colistin</span>
- CAZ <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Ceftazidime</span>
- CXM <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Cefuroxime</span>
- PEN <span class="op">=</span> <span class="st">"S"</span>, <span class="co"># Benzylenicillin</span>
- FOX <span class="op">=</span> <span class="st">"S"</span>, <span class="co"># Cefoxitin</span>
- stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span></code></pre></div>
-<table class="table">
-<thead><tr class="header">
-<th align="left">mo</th>
-<th align="center">VAN</th>
-<th align="center">AMX</th>
-<th align="center">COL</th>
-<th align="center">CAZ</th>
-<th align="center">CXM</th>
-<th align="center">PEN</th>
-<th align="center">FOX</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">Staphylococcus aureus</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">S</td>
-<td align="center">S</td>
-</tr>
-<tr class="even">
-<td align="left">Enterococcus faecalis</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">S</td>
-<td align="center">S</td>
-</tr>
-<tr class="odd">
-<td align="left">Escherichia coli</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">S</td>
-<td align="center">S</td>
-</tr>
-<tr class="even">
-<td align="left">Klebsiella pneumoniae</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">S</td>
-<td align="center">S</td>
-</tr>
-<tr class="odd">
-<td align="left">Pseudomonas aeruginosa</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">S</td>
-<td align="center">S</td>
-</tr>
-</tbody>
-</table>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></code></pre></div>
-<table class="table">
-<thead><tr class="header">
-<th align="left">mo</th>
-<th align="center">VAN</th>
-<th align="center">AMX</th>
-<th align="center">COL</th>
-<th align="center">CAZ</th>
-<th align="center">CXM</th>
-<th align="center">PEN</th>
-<th align="center">FOX</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">Staphylococcus aureus</td>
-<td align="center">-</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>
-</tr>
-<tr class="even">
-<td align="left">Enterococcus faecalis</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center">R</td>
-</tr>
-<tr class="odd">
-<td align="left">Escherichia coli</td>
-<td align="center">R</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">R</td>
-<td align="center">S</td>
-</tr>
-<tr class="even">
-<td align="left">Klebsiella pneumoniae</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">R</td>
-<td align="center">S</td>
-</tr>
-<tr class="odd">
-<td align="left">Pseudomonas aeruginosa</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">-</td>
-<td align="center">-</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">R</td>
-</tr>
-</tbody>
-</table>
-</div>
- </div>
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- <div class="page-header toc-ignore">
- <h1 data-toc-skip>How to determine multi-drug resistance
-(MDR)</h1>
-
-
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/MDR.Rmd" class="external-link"><code>vignettes/MDR.Rmd</code></a></small>
- <div class="hidden name"><code>MDR.Rmd</code></div>
-
- </div>
-
-
-
-<p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine which
-micro-organisms are multi-drug resistant organisms (MDRO).</p>
-<div class="section level3">
-<h3 id="type-of-input">Type of input<a class="anchor" aria-label="anchor" href="#type-of-input"></a>
-</h3>
-<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function takes a data set as input, such as a
-regular <code>data.frame</code>. It tries to automatically determine the
-right columns for info about your isolates, such as the name of the
-species and all columns with results of antimicrobial agents. See the
-help page for more info about how to set the right settings for your
-data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p>
-<p>For WHONET data (and most other data), all settings are automatically
-set correctly.</p>
-</div>
-<div class="section level3">
-<h3 id="guidelines">Guidelines<a class="anchor" aria-label="anchor" href="#guidelines"></a>
-</h3>
-<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function support multiple guidelines. You can
-select a guideline with the <code>guideline</code> parameter. Currently
-supported guidelines are (case-insensitive):</p>
-<ul>
-<li>
-<p><code>guideline = "CMI2012"</code> (default)</p>
-<p>Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant,
-extensively drug-resistant and pandrug-resistant bacteria: an
-international expert proposal for interim standard definitions for
-acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext" class="external-link">link</a>)</p>
-</li>
-<li>
-<p><code>guideline = "EUCAST3.2"</code> (or simply
-<code>guideline = "EUCAST"</code>)</p>
-<p>The European international guideline - EUCAST Expert Rules Version
-3.2 “Intrinsic Resistance and Unusual Phenotypes” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf" class="external-link">link</a>)</p>
-</li>
-<li>
-<p><code>guideline = "EUCAST3.1"</code></p>
-<p>The European international guideline - EUCAST Expert Rules Version
-3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf" class="external-link">link</a>)</p>
-</li>
-<li>
-<p><code>guideline = "TB"</code></p>
-<p>The international guideline for multi-drug resistant tuberculosis -
-World Health Organization “Companion handbook to the WHO guidelines for
-the programmatic management of drug-resistant tuberculosis” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/" class="external-link">link</a>)</p>
-</li>
-<li>
-<p><code>guideline = "MRGN"</code></p>
-<p>The German national guideline - Mueller <em>et al.</em> (2015)
-Antimicrobial Resistance and Infection Control 4:7. DOI:
-10.1186/s13756-015-0047-6</p>
-</li>
-<li>
-<p><code>guideline = "BRMO"</code></p>
-<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en
-Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen)
-(ZKH)” (<a href="https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh" class="external-link">link</a>)</p>
-</li>
-</ul>
-<p>Please suggest your own (country-specific) guidelines by letting us
-know: <a href="https://github.com/msberends/AMR/issues/new" class="external-link uri">https://github.com/msberends/AMR/issues/new</a>.</p>
-<div class="section level4">
-<h4 id="custom-guidelines">Custom Guidelines<a class="anchor" aria-label="anchor" href="#custom-guidelines"></a>
-</h4>
-<p>You can also use your own custom guideline. Custom guidelines can be
-set with the <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function. This is of
-great importance if you have custom rules to determine MDROs in your
-hospital, e.g., rules that are dependent on ward, state of contact
-isolation or other variables in your data.</p>
-<p>If you are familiar with <code><a href="https://dplyr.tidyverse.org/reference/case_when.html" class="external-link">case_when()</a></code> of the
-<code>dplyr</code> package, you will recognise the input method to set
-your own rules. Rules must be set using what R considers to be the
-‘formula notation’:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">custom</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mdro.html">custom_mdro_guideline</a></span><span class="op">(</span><span class="va">CIP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&</span> <span class="va">age</span> <span class="op">></span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type A"</span>,
- <span class="va">ERY</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&</span> <span class="va">age</span> <span class="op">></span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type B"</span><span class="op">)</span></code></pre></div>
-<p>If a row/an isolate matches the first rule, the value after the first
-<code>~</code> (in this case <em>‘Elderly Type A’</em>) will be set as
-MDRO value. Otherwise, the second rule will be tried and so on. The
-maximum number of rules is unlimited.</p>
-<p>You can print the rules set in the console for an overview. Colours
-will help reading it if your console supports colours.</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">custom</span>
-<span class="co"># A set of custom MDRO rules:</span>
-<span class="co"># 1. If CIP is "R" and age is higher than 60 then: Elderly Type A</span>
-<span class="co"># 2. If ERY is "R" and age is higher than 60 then: Elderly Type B</span>
-<span class="co"># 3. Otherwise: Negative</span>
-<span class="co"># </span>
-<span class="co"># Unmatched rows will return NA.</span>
-<span class="co"># Results will be of class <factor>, with ordered levels: Negative < Elderly Type A < Elderly Type B</span></code></pre></div>
-<p>The outcome of the function can be used for the
-<code>guideline</code> argument in the <code><a href="../reference/mdro.html">mdro()</a></code> function:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">example_isolates</span>, guideline <span class="op">=</span> <span class="va">custom</span><span class="op">)</span>
-<span class="co"># Determining MDROs based on custom rules, resulting in factor levels:</span>
-<span class="co"># Negative < Elderly Type A < Elderly Type B.</span>
-<span class="co"># - Custom MDRO rule 1: `CIP == "R" & age > 60` (198 rows matched)</span>
-<span class="co"># - Custom MDRO rule 2: `ERY == "R" & age > 60` (732 rows matched)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/table.html" class="external-link">table</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-<span class="co"># x</span>
-<span class="co"># Negative Elderly Type A Elderly Type B </span>
-<span class="co"># 1070 198 732</span></code></pre></div>
-<p>The rules set (the <code>custom</code> object in this case) could be
-exported to a shared file location using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">saveRDS()</a></code> if you
-collaborate with multiple users. The custom rules set could then be
-imported using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">readRDS()</a></code>.</p>
-</div>
-</div>
-<div class="section level3">
-<h3 id="examples">Examples<a class="anchor" aria-label="anchor" href="#examples"></a>
-</h3>
-<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered
-<code>factor</code> for predefined guidelines. For example, the output
-of the default guideline by Magiorakos <em>et al.</em> returns a
-<code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in
-that order.</p>
-<p>The next example uses the <code>example_isolates</code> data set.
-This is a data set included with this package and contains full
-antibiograms of 2,000 microbial isolates. It reflects reality and can be
-used to practise AMR data analysis. If we test the MDR/XDR/PDR guideline
-on this data set, we get:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># to support pipes: %>%</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="op">)</span> <span class="co"># show frequency table of the result</span>
-<span class="co"># ℹ Using column 'mo' as input for `col_mo`.</span>
-<span class="co"># Auto-guessing columns suitable for analysis... OK.</span>
-<span class="co"># ℹ Reliability would be improved if these antimicrobial results would be</span>
-<span class="co"># available too: ampicillin/sulbactam (SAM), aztreonam (ATM), cefotetan</span>
-<span class="co"># (CTT), ceftaroline (CPT), daptomycin (DAP), doripenem (DOR), ertapenem</span>
-<span class="co"># (ETP), fusidic acid (FUS), gentamicin-high (GEH), levofloxacin (LVX),</span>
-<span class="co"># minocycline (MNO), netilmicin (NET), polymyxin B (PLB),</span>
-<span class="co"># quinupristin/dalfopristin (QDA), streptomycin-high (STH), telavancin (TLV)</span>
-<span class="co"># and ticarcillin/clavulanic acid (TCC)</span>
-<span class="co"># Table 1 - Staphylococcus aureus... OK.</span>
-<span class="co"># Table 2 - Enterococcus spp.... OK.</span>
-<span class="co"># Table 3 - Enterobacteriaceae... OK.</span>
-<span class="co"># Table 4 - Pseudomonas aeruginosa... OK.</span>
-<span class="co"># Table 5 - Acinetobacter spp.... OK.</span>
-<span class="co"># Warning: in `mdro()`: NA introduced for isolates where the available percentage of</span>
-<span class="co"># antimicrobial classes was below 50% (set with `pct_required_classes`)</span></code></pre></div>
-<p>Only results with ‘R’ are considered as resistance. Use
-<code>combine_SI = FALSE</code> to also consider ‘I’ as resistance.</p>
-<p>Determining multidrug-resistant organisms (MDRO), according to:
-Guideline: Multidrug-resistant, extensively drug-resistant and
-pandrug-resistant bacteria: an international expert proposal for interim
-standard definitions for acquired resistance. Author(s): Magiorakos AP,
-Srinivasan A, Carey RB, …, Vatopoulos A, Weber JT, Monnet DL Source:
-Clinical Microbiology and Infection 18:3, 2012; doi:
-10.1111/j.1469-0691.2011.03570.x</p>
-<p>(16 isolates had no test results)</p>
-<p><strong>Frequency table</strong></p>
-<p>Class: factor > ordered (numeric)<br>
-Length: 2,000<br>
-Levels: 4: Negative < Multi-drug-resistant (MDR) < Extensively
-drug-resistant …<br>
-Available: 1,729 (86.45%, NA: 271 = 13.55%)<br>
-Unique: 2</p>
-<table style="width:100%;" class="table">
-<colgroup>
-<col width="4%">
-<col width="38%">
-<col width="9%">
-<col width="12%">
-<col width="16%">
-<col width="19%">
-</colgroup>
-<thead><tr class="header">
-<th align="left"></th>
-<th align="left">Item</th>
-<th align="right">Count</th>
-<th align="right">Percent</th>
-<th align="right">Cum. Count</th>
-<th align="right">Cum. Percent</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">1</td>
-<td align="left">Negative</td>
-<td align="right">1601</td>
-<td align="right">92.6%</td>
-<td align="right">1601</td>
-<td align="right">92.6%</td>
-</tr>
-<tr class="even">
-<td align="left">2</td>
-<td align="left">Multi-drug-resistant (MDR)</td>
-<td align="right">128</td>
-<td align="right">7.4%</td>
-<td align="right">1729</td>
-<td align="right">100.0%</td>
-</tr>
-</tbody>
-</table>
-<p>For another example, I will create a data set to determine multi-drug
-resistant TB:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># random_rsi() is a helper function to generate</span>
-<span class="co"># a random vector with values S, I and R</span>
-<span class="va">my_TB_data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>rifampicin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- isoniazid <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- gatifloxacin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- ethambutol <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- pyrazinamide <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- moxifloxacin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- kanamycin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p>Because all column names are automatically verified for valid drug
-names or codes, this would have worked exactly the same way:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">my_TB_data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>RIF <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- INH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- GAT <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- ETH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- PZA <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- MFX <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
- KAN <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></code></pre></div>
-<p>The data set now looks like this:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
-<span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span>
-<span class="co"># 1 R I R R I S</span>
-<span class="co"># 2 I I S S R S</span>
-<span class="co"># 3 I S R R S R</span>
-<span class="co"># 4 R I S R R I</span>
-<span class="co"># 5 R I I I R I</span>
-<span class="co"># 6 R I R S R I</span>
-<span class="co"># kanamycin</span>
-<span class="co"># 1 R</span>
-<span class="co"># 2 R</span>
-<span class="co"># 3 S</span>
-<span class="co"># 4 I</span>
-<span class="co"># 5 I</span>
-<span class="co"># 6 R</span></code></pre></div>
-<p>We can now add the interpretation of MDR-TB to our data set. You can
-use:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">my_TB_data</span>, guideline <span class="op">=</span> <span class="st">"TB"</span><span class="op">)</span></code></pre></div>
-<p>or its shortcut <code><a href="../reference/mdro.html">mdr_tb()</a></code>:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mdro.html">mdr_tb</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
-<span class="co"># ℹ No column found as input for `col_mo`, assuming all rows contain</span>
-<span class="co"># Mycobacterium tuberculosis.</span>
-<span class="co"># Auto-guessing columns suitable for analysis... OK.</span>
-<span class="co"># ℹ Reliability would be improved if these antimicrobial results would be</span>
-<span class="co"># available too: capreomycin (CAP), rifabutin (RIB) and rifapentine (RFP)</span>
-<span class="co"># </span>
-<span class="co"># Only results with 'R' are considered as resistance. Use `combine_SI = FALSE` to also consider 'I' as resistance.</span>
-<span class="co"># </span>
-<span class="co"># Determining multidrug-resistant organisms (MDRO), according to:</span>
-<span class="co"># Guideline: Companion handbook to the WHO guidelines for the programmatic</span>
-<span class="co"># management of drug-resistant tuberculosis</span>
-<span class="co"># Author(s): WHO (World Health Organization)</span>
-<span class="co"># Version: WHO/HTM/TB/2014.11, 2014</span>
-<span class="co"># Source: https://www.who.int/publications/i/item/9789241548809</span></code></pre></div>
-<p>Create a frequency table of the results:</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span><span class="op">)</span></code></pre></div>
-<p><strong>Frequency table</strong></p>
-<p>Class: factor > ordered (numeric)<br>
-Length: 5,000<br>
-Levels: 5: Negative < Mono-resistant < Poly-resistant <
-Multi-drug-resistant <…<br>
-Available: 5,000 (100%, NA: 0 = 0%)<br>
-Unique: 5</p>
-<table style="width:100%;" class="table">
-<colgroup>
-<col width="4%">
-<col width="38%">
-<col width="9%">
-<col width="12%">
-<col width="16%">
-<col width="19%">
-</colgroup>
-<thead><tr class="header">
-<th align="left"></th>
-<th align="left">Item</th>
-<th align="right">Count</th>
-<th align="right">Percent</th>
-<th align="right">Cum. Count</th>
-<th align="right">Cum. Percent</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">1</td>
-<td align="left">Mono-resistant</td>
-<td align="right">3218</td>
-<td align="right">64.36%</td>
-<td align="right">3218</td>
-<td align="right">64.36%</td>
-</tr>
-<tr class="even">
-<td align="left">2</td>
-<td align="left">Negative</td>
-<td align="right">979</td>
-<td align="right">19.58%</td>
-<td align="right">4197</td>
-<td align="right">83.94%</td>
-</tr>
-<tr class="odd">
-<td align="left">3</td>
-<td align="left">Multi-drug-resistant</td>
-<td align="right">458</td>
-<td align="right">9.16%</td>
-<td align="right">4655</td>
-<td align="right">93.10%</td>
-</tr>
-<tr class="even">
-<td align="left">4</td>
-<td align="left">Poly-resistant</td>
-<td align="right">237</td>
-<td align="right">4.74%</td>
-<td align="right">4892</td>
-<td align="right">97.84%</td>
-</tr>
-<tr class="odd">
-<td align="left">5</td>
-<td align="left">Extensively drug-resistant</td>
-<td align="right">108</td>
-<td align="right">2.16%</td>
-<td align="right">5000</td>
-<td align="right">100.00%</td>
-</tr>
-</tbody>
-</table>
-</div>
- </div>
-
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/articles/MDR_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/MDR_files/accessible-code-block-0.0.1/empty-anchor.js
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-// Hide empty <a> tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
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diff --git a/docs/articles/PCA.html b/docs/articles/PCA.html
deleted file mode 100644
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- <h1 data-toc-skip>How to conduct principal component analysis
-(PCA) for AMR</h1>
-
-
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small>
- <div class="hidden name"><code>PCA.Rmd</code></div>
-
- </div>
-
-
-
-<p><strong>NOTE: This page will be updated soon, as the pca() function
-is currently being developed.</strong></p>
-<div class="section level2">
-<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
-</h2>
-</div>
-<div class="section level2">
-<h2 id="transforming">Transforming<a class="anchor" aria-label="anchor" href="#transforming"></a>
-</h2>
-<p>For PCA, we need to transform our AMR data first. This is what the
-<code>example_isolates</code> data set in this package looks like:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span>
-<span class="fu"><a href="https://dplyr.tidyverse.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
-<span class="co"># Rows: 2,000</span>
-<span class="co"># Columns: 49</span>
-<span class="co"># $ date <span style="color: #949494; font-style: italic;"><date></span> 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002-…</span>
-<span class="co"># $ hospital_id <span style="color: #949494; font-style: italic;"><fct></span> D, D, B, B, B, B, D, D, B, B, D, D, D, D, D, B, B, B, …</span>
-<span class="co"># $ ward_icu <span style="color: #949494; font-style: italic;"><lgl></span> FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TR…</span>
-<span class="co"># $ ward_clinical <span style="color: #949494; font-style: italic;"><lgl></span> TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FA…</span>
-<span class="co"># $ ward_outpatient <span style="color: #949494; font-style: italic;"><lgl></span> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE…</span>
-<span class="co"># $ age <span style="color: #949494; font-style: italic;"><dbl></span> 65, 65, 45, 45, 45, 45, 78, 78, 45, 79, 67, 67, 71, 71…</span>
-<span class="co"># $ gender <span style="color: #949494; font-style: italic;"><chr></span> "F", "F", "F", "F", "F", "F", "M", "M", "F", "F", "M",…</span>
-<span class="co"># $ patient_id <span style="color: #949494; font-style: italic;"><chr></span> "A77334", "A77334", "067927", "067927", "067927", "067…</span>
-<span class="co"># $ mo <span style="color: #949494; font-style: italic;"><mo></span> "B_ESCHR_COLI", "B_ESCHR_COLI", "B_STPHY_EPDR", "B_STPH…</span>
-<span class="co"># $ PEN <span style="color: #949494; font-style: italic;"><rsi></span> R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, …</span>
-<span class="co"># $ OXA <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ FLC <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, R, R, R, R, S, S, R, S, S, S, NA, NA, NA, NA, …</span>
-<span class="co"># $ AMX <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, …</span>
-<span class="co"># $ AMC <span style="color: #949494; font-style: italic;"><rsi></span> I, I, NA, NA, NA, NA, S, S, NA, NA, S, S, I, I, R, I, …</span>
-<span class="co"># $ AMP <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, …</span>
-<span class="co"># $ TZP <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ CZO <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ FEP <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ CXM <span style="color: #949494; font-style: italic;"><rsi></span> I, I, R, R, R, R, S, S, R, S, S, S, S, S, NA, S, S, R,…</span>
-<span class="co"># $ FOX <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ CTX <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, …</span>
-<span class="co"># $ CAZ <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, S, S…</span>
-<span class="co"># $ CRO <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, …</span>
-<span class="co"># $ GEN <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ TOB <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, S, S, NA…</span>
-<span class="co"># $ AMK <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ KAN <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ TMP <span style="color: #949494; font-style: italic;"><rsi></span> R, R, S, S, R, R, R, R, S, S, NA, NA, S, S, S, S, S, R…</span>
-<span class="co"># $ SXT <span style="color: #949494; font-style: italic;"><rsi></span> R, R, S, S, NA, NA, NA, NA, S, S, NA, NA, S, S, S, S, …</span>
-<span class="co"># $ NIT <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ FOS <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ LNZ <span style="color: #949494; font-style: italic;"><rsi></span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R,…</span>
-<span class="co"># $ CIP <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, …</span>
-<span class="co"># $ MFX <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ VAN <span style="color: #949494; font-style: italic;"><rsi></span> R, R, S, S, S, S, S, S, S, S, NA, NA, R, R, R, R, R, S…</span>
-<span class="co"># $ TEC <span style="color: #949494; font-style: italic;"><rsi></span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R,…</span>
-<span class="co"># $ TCY <span style="color: #949494; font-style: italic;"><rsi></span> R, R, S, S, S, S, S, S, S, I, S, S, NA, NA, I, R, R, S…</span>
-<span class="co"># $ TGC <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, …</span>
-<span class="co"># $ DOX <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, …</span>
-<span class="co"># $ ERY <span style="color: #949494; font-style: italic;"><rsi></span> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, …</span>
-<span class="co"># $ CLI <span style="color: #949494; font-style: italic;"><rsi></span> R, R, NA, NA, NA, R, NA, NA, NA, NA, NA, NA, R, R, R, …</span>
-<span class="co"># $ AZM <span style="color: #949494; font-style: italic;"><rsi></span> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, …</span>
-<span class="co"># $ IPM <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, …</span>
-<span class="co"># $ MEM <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ MTR <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ CHL <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ COL <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, R…</span>
-<span class="co"># $ MUP <span style="color: #949494; font-style: italic;"><rsi></span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
-<span class="co"># $ RIF <span style="color: #949494; font-style: italic;"><rsi></span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R,…</span></code></pre></div>
-<p>Now to transform this to a data set with only resistance percentages
-per taxonomic order and genus:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">resistance_data</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>order <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, <span class="co"># group on anything, like order</span>
- genus <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># and genus as we do here</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html" class="external-link">summarise_if</a></span><span class="op">(</span><span class="va">is.rsi</span>, <span class="va">resistance</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># then get resistance of all drugs</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">order</span>, <span class="va">genus</span>, <span class="va">AMC</span>, <span class="va">CXM</span>, <span class="va">CTX</span>,
- <span class="va">CAZ</span>, <span class="va">GEN</span>, <span class="va">TOB</span>, <span class="va">TMP</span>, <span class="va">SXT</span><span class="op">)</span> <span class="co"># and select only relevant columns</span>
-
-<span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
-<span class="co"># <span style="color: #949494;"># A tibble: 6 × 10</span></span>
-<span class="co"># <span style="color: #949494;"># Groups: order [5]</span></span>
-<span class="co"># order genus AMC CXM CTX CAZ GEN TOB TMP SXT</span>
-<span class="co"># <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><dbl></span></span>
-<span class="co"># <span style="color: #BCBCBC;">1</span> (unknown order) (unknown ge… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span>
-<span class="co"># <span style="color: #BCBCBC;">2</span> Actinomycetales Schaalia <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span>
-<span class="co"># <span style="color: #BCBCBC;">3</span> Bacteroidales Bacteroides <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span>
-<span class="co"># <span style="color: #BCBCBC;">4</span> Campylobacterales Campylobact… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span>
-<span class="co"># <span style="color: #BCBCBC;">5</span> Caryophanales Gemella <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span>
-<span class="co"># <span style="color: #BCBCBC;">6</span> Caryophanales Listeria <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span></code></pre></div>
-</div>
-<div class="section level2">
-<h2 id="perform-principal-component-analysis">Perform principal component analysis<a class="anchor" aria-label="anchor" href="#perform-principal-component-analysis"></a>
-</h2>
-<p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows
-that contain numeric values in all selected variables, so we now only
-need to do:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">pca_result</span> <span class="op"><-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
-<span class="co"># ℹ Columns selected for PCA: "AMC", "CAZ", "CTX", "CXM", "GEN", "SXT", "TMP"</span>
-<span class="co"># and "TOB". Total observations available: 7.</span></code></pre></div>
-<p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code>
-function:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span>
-<span class="co"># Groups (n=4, named as 'order'):</span>
-<span class="co"># [1] "Caryophanales" "Enterobacterales" "Lactobacillales" "Pseudomonadales"</span>
-<span class="co"># Importance of components:</span>
-<span class="co"># PC1 PC2 PC3 PC4 PC5 PC6 PC7</span>
-<span class="co"># Standard deviation 2.1539 1.6807 0.6138 0.33879 0.20808 0.03140 5.674e-17</span>
-<span class="co"># Proportion of Variance 0.5799 0.3531 0.0471 0.01435 0.00541 0.00012 0.000e+00</span>
-<span class="co"># Cumulative Proportion 0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00</span></code></pre></div>
-<pre><code><span class="co"># Groups (n=4, named as 'order'):</span>
-<span class="co"># [1] "Caryophanales" "Enterobacterales" "Lactobacillales" "Pseudomonadales"</span></code></pre>
-<p>Good news. The first two components explain a total of 93.3% of the
-variance (see the PC1 and PC2 values of the <em>Proportion of
-Variance</em>. We can create a so-called biplot with the base R
-<code><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot()</a></code> function, to see which antimicrobial resistance
-per drug explain the difference per microorganism.</p>
-</div>
-<div class="section level2">
-<h2 id="plotting-the-results">Plotting the results<a class="anchor" aria-label="anchor" href="#plotting-the-results"></a>
-</h2>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div>
-<p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" width="750"></p>
-<p>But we can’t see the explanation of the points. Perhaps this works
-better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that
-automatically adds the right labels and even groups:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div>
-<p><img src="PCA_files/figure-html/unnamed-chunk-6-1.png" width="750"></p>
-<p>You can also print an ellipse per group, and edit the appearance:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span>, ellipse <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"An AMR/PCA biplot!"</span><span class="op">)</span></code></pre></div>
-<p><img src="PCA_files/figure-html/unnamed-chunk-7-1.png" width="750"></p>
-</div>
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- <h1 data-toc-skip>How to import data from SPSS / SAS / Stata</h1>
- <h4 data-toc-skip class="author">Dr. Matthijs
-Berends</h4>
-
- <h4 data-toc-skip class="date">11 mei 2022</h4>
-
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/SPSS.Rmd" class="external-link"><code>vignettes/SPSS.Rmd</code></a></small>
- <div class="hidden name"><code>SPSS.Rmd</code></div>
-
- </div>
-
-
-
-<div class="section level2">
-<h2 id="spss-sas-stata">SPSS / SAS / Stata<a class="anchor" aria-label="anchor" href="#spss-sas-stata"></a>
-</h2>
-<p>SPSS (Statistical Package for the Social Sciences) is probably the
-most well-known software package for statistical analysis. SPSS is
-easier to learn than R, because in SPSS you only have to click a menu to
-run parts of your analysis. Because of its user-friendliness, it is
-taught at universities and particularly useful for students who are new
-to statistics. From my experience, I would guess that pretty much all
-(bio)medical students know it at the time they graduate. SAS and Stata
-are comparable statistical packages popular in big industries.</p>
-</div>
-<div class="section level2">
-<h2 id="compared-to-r">Compared to R<a class="anchor" aria-label="anchor" href="#compared-to-r"></a>
-</h2>
-<p>As said, SPSS is easier to learn than R. But SPSS, SAS and Stata come
-with major downsides when comparing it with R:</p>
-<ul>
-<li>
-<p><strong>R is highly modular.</strong></p>
-<p>The <a href="https://cran.r-project.org/" class="external-link">official R network
-(CRAN)</a> features more than 16,000 packages at the time of writing,
-our <code>AMR</code> package being one of them. All these packages were
-peer-reviewed before publication. Aside from this official channel,
-there are also developers who choose not to submit to CRAN, but rather
-keep it on their own public repository, like GitHub. So there may even
-be a lot more than 14,000 packages out there.</p>
-<p>Bottom line is, you can really extend it yourself or ask somebody to
-do this for you. Take for example our <code>AMR</code> package. Among
-other things, it adds reliable reference data to R to help you with the
-data cleaning and analysis. SPSS, SAS and Stata will never know what a
-valid MIC value is or what the Gram stain of <em>E. coli</em> is. Or
-that all species of <em>Klebiella</em> are resistant to amoxicillin and
-that Floxapen<sup>®</sup> is a trade name of flucloxacillin. These facts
-and properties are often needed to clean existing data, which would be
-very inconvenient in a software package without reliable reference data.
-See below for a demonstration.</p>
-</li>
-<li>
-<p><strong>R is extremely flexible.</strong></p>
-<p>Because you write the syntax yourself, you can do anything you want.
-The flexibility in transforming, arranging, grouping and summarising
-data, or drawing plots, is endless - with SPSS, SAS or Stata you are
-bound to their algorithms and format styles. They may be a bit flexible,
-but you can probably never create that very specific publication-ready
-plot without using other (paid) software. If you sometimes write
-syntaxes in SPSS to run a complete analysis or to ‘automate’ some of
-your work, you could do this a lot less time in R. You will notice that
-writing syntaxes in R is a lot more nifty and clever than in SPSS.
-Still, as working with any statistical package, you will have to have
-knowledge about what you are doing (statistically) and what you are
-willing to accomplish.</p>
-</li>
-<li>
-<p><strong>R can be easily automated.</strong></p>
-<p>Over the last years, <a href="https://rmarkdown.rstudio.com/" class="external-link">R
-Markdown</a> has really made an interesting development. With R
-Markdown, you can very easily produce reports, whether the format has to
-be Word, PowerPoint, a website, a PDF document or just the raw data to
-Excel. It even allows the use of a reference file containing the layout
-style (e.g. fonts and colours) of your organisation. I use this a lot to
-generate weekly and monthly reports automatically. Just write the code
-once and enjoy the automatically updated reports at any interval you
-like.</p>
-<p>For an even more professional environment, you could create <a href="https://shiny.rstudio.com/" class="external-link">Shiny apps</a>: live manipulation of
-data using a custom made website. The webdesign knowledge needed
-(JavaScript, CSS, HTML) is almost <em>zero</em>.</p>
-</li>
-<li>
-<p><strong>R has a huge community.</strong></p>
-<p>Many R users just ask questions on websites like <a href="https://stackoverflow.com" class="external-link">StackOverflow.com</a>, the largest
-online community for programmers. At the time of writing, <a href="https://stackoverflow.com/questions/tagged/r?sort=votes" class="external-link">447,735
-R-related questions</a> have already been asked on this platform (that
-covers questions and answers for any programming language). In my own
-experience, most questions are answered within a couple of
-minutes.</p>
-</li>
-<li>
-<p><strong>R understands any data type, including
-SPSS/SAS/Stata.</strong></p>
-<p>And that’s not vice versa I’m afraid. You can import data from any
-source into R. For example from SPSS, SAS and Stata (<a href="https://haven.tidyverse.org/" class="external-link">link</a>), from Minitab, Epi Info
-and EpiData (<a href="https://cran.r-project.org/package=foreign" class="external-link">link</a>), from Excel
-(<a href="https://readxl.tidyverse.org/" class="external-link">link</a>), from flat files like
-CSV, TXT or TSV (<a href="https://readr.tidyverse.org/" class="external-link">link</a>), or
-directly from databases and datawarehouses from anywhere on the world
-(<a href="https://dbplyr.tidyverse.org/" class="external-link">link</a>). You can even scrape
-websites to download tables that are live on the internet (<a href="https://github.com/hadley/rvest" class="external-link">link</a>) or get the results of
-an API call and transform it into data in only one command (<a href="https://github.com/Rdatatable/data.table/wiki/Convenience-features-of-fread" class="external-link">link</a>).</p>
-<p>And the best part - you can export from R to most data formats as
-well. So you can import an SPSS file, do your analysis neatly in R and
-export the resulting tables to Excel files for sharing.</p>
-</li>
-<li>
-<p><strong>R is completely free and open-source.</strong></p>
-<p>No strings attached. It was created and is being maintained by
-volunteers who believe that (data) science should be open and publicly
-available to everybody. SPSS, SAS and Stata are quite expensive. IBM
-SPSS Staticstics only comes with subscriptions nowadays, varying <a href="https://www.ibm.com/products/spss-statistics/pricing" class="external-link">between USD
-1,300 and USD 8,500</a> per user <em>per year</em>. SAS Analytics Pro
-costs <a href="https://www.sas.com/store/products-solutions/sas-analytics-pro/prodPERSANL.html" class="external-link">around
-USD 10,000</a> per computer. Stata also has a business model with
-subscription fees, varying <a href="https://www.stata.com/order/new/bus/single-user-licenses/dl/" class="external-link">between
-USD 600 and USD 2,800</a> per computer per year, but lower prices come
-with a limitation of the number of variables you can work with. And
-still they do not offer the above benefits of R.</p>
-<p>If you are working at a midsized or small company, you can save it
-tens of thousands of dollars by using R instead of e.g. SPSS - gaining
-even more functions and flexibility. And all R enthousiasts can do as
-much PR as they want (like I do here), because nobody is officially
-associated with or affiliated by R. It is really free.</p>
-</li>
-<li>
-<p><strong>R is (nowadays) the preferred analysis software in
-academic papers.</strong></p>
-<p>At present, R is among the world most powerful statistical languages,
-and it is generally very popular in science (Bollmann <em>et al.</em>,
-2017). For all the above reasons, the number of references to R as an
-analysis method in academic papers <a href="https://r4stats.com/2014/08/20/r-passes-spss-in-scholarly-use-stata-growing-rapidly/" class="external-link">is
-rising continuously</a> and has even surpassed SPSS for academic use
-(Muenchen, 2014).</p>
-<p>I believe that the thing with SPSS is, that it has always had a great
-user interface which is very easy to learn and use. Back when they
-developed it, they had very little competition, let alone from R. R
-didn’t even had a professional user interface until the last decade
-(called RStudio, see below). How people used R between the nineties and
-2010 is almost completely incomparable to how R is being used now. The
-language itself <a href="https://www.tidyverse.org/packages/" class="external-link">has been
-restyled completely</a> by volunteers who are dedicated professionals in
-the field of data science. SPSS was great when there was nothing else
-that could compete. But now in 2022, I don’t see any reason why SPSS
-would be of any better use than R.</p>
-</li>
-</ul>
-<p>To demonstrate the first point:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># not all values are valid MIC values:</span>
-<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span><span class="op">(</span><span class="fl">0.125</span><span class="op">)</span>
-<span class="co"># Class <mic></span>
-<span class="co"># [1] 0.125</span>
-<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span><span class="op">(</span><span class="st">"testvalue"</span><span class="op">)</span>
-<span class="co"># Class <mic></span>
-<span class="co"># [1] <NA></span>
-
-<span class="co"># the Gram stain is available for all bacteria:</span>
-<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
-<span class="co"># [1] "Gram-negative"</span>
-
-<span class="co"># Klebsiella is intrinsic resistant to amoxicillin, according to EUCAST:</span>
-<span class="va">klebsiella_test</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="st">"klebsiella"</span>,
- amox <span class="op">=</span> <span class="st">"S"</span>,
- stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-<span class="va">klebsiella_test</span> <span class="co"># (our original data)</span>
-<span class="co"># mo amox</span>
-<span class="co"># 1 klebsiella S</span>
-<span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">klebsiella_test</span>, info <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span> <span class="co"># (the edited data by EUCAST rules)</span>
-<span class="co"># mo amox</span>
-<span class="co"># 1 klebsiella R</span>
-
-<span class="co"># hundreds of trade names can be translated to a name, trade name or an ATC code:</span>
-<span class="fu"><a href="../reference/ab_property.html">ab_name</a></span><span class="op">(</span><span class="st">"floxapen"</span><span class="op">)</span>
-<span class="co"># [1] "Flucloxacillin"</span>
-<span class="fu"><a href="../reference/ab_property.html">ab_tradenames</a></span><span class="op">(</span><span class="st">"floxapen"</span><span class="op">)</span>
-<span class="co"># [1] "floxacillin" "floxapen" "floxapen sodium salt"</span>
-<span class="co"># [4] "fluclox" "flucloxacilina" "flucloxacillin" </span>
-<span class="co"># [7] "flucloxacilline" "flucloxacillinum" "fluorochloroxacillin"</span>
-<span class="fu"><a href="../reference/ab_property.html">ab_atc</a></span><span class="op">(</span><span class="st">"floxapen"</span><span class="op">)</span>
-<span class="co"># [1] "J01CF05"</span></code></pre></div>
-</div>
-<div class="section level2">
-<h2 id="import-data-from-spsssasstata">Import data from SPSS/SAS/Stata<a class="anchor" aria-label="anchor" href="#import-data-from-spsssasstata"></a>
-</h2>
-<div class="section level3">
-<h3 id="rstudio">RStudio<a class="anchor" aria-label="anchor" href="#rstudio"></a>
-</h3>
-<p>To work with R, probably the best option is to use <a href="https://www.rstudio.com/products/rstudio/" class="external-link">RStudio</a>. It is an
-open-source and free desktop environment which not only allows you to
-run R code, but also supports project management, version management,
-package management and convenient import menus to work with other data
-sources. You can also install <a href="https://www.rstudio.com/products/rstudio/" class="external-link">RStudio Server</a> on a
-private or corporate server, which brings nothing less than the complete
-RStudio software to you as a website (at home or at work).</p>
-<p>To import a data file, just click <em>Import Dataset</em> in the
-Environment tab:</p>
-<p><img src="https://github.com/msberends/AMR/raw/main/docs/import1.png"></p>
-<p>If additional packages are needed, RStudio will ask you if they
-should be installed on beforehand.</p>
-<p>In the the window that opens, you can define all options (parameters)
-that should be used for import and you’re ready to go:</p>
-<p><img src="https://github.com/msberends/AMR/raw/main/docs/import2.png"></p>
-<p>If you want named variables to be imported as factors so it resembles
-SPSS more, use <code><a href="https://haven.tidyverse.org/reference/as_factor.html" class="external-link">as_factor()</a></code>.</p>
-<p>The difference is this:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">SPSS_data</span>
-<span class="co"># # A tibble: 4,203 x 4</span>
-<span class="co"># v001 sex status statusage</span>
-<span class="co"># <dbl> <dbl+lbl> <dbl+lbl> <dbl></span>
-<span class="co"># 1 10002 1 1 76.6</span>
-<span class="co"># 2 10004 0 1 59.1</span>
-<span class="co"># 3 10005 1 1 54.5</span>
-<span class="co"># 4 10006 1 1 54.1</span>
-<span class="co"># 5 10007 1 1 57.7</span>
-<span class="co"># 6 10008 1 1 62.8</span>
-<span class="co"># 7 10010 0 1 63.7</span>
-<span class="co"># 8 10011 1 1 73.1</span>
-<span class="co"># 9 10017 1 1 56.7</span>
-<span class="co"># 10 10018 0 1 66.6</span>
-<span class="co"># # ... with 4,193 more rows</span>
-
-<span class="fu">as_factor</span><span class="op">(</span><span class="va">SPSS_data</span><span class="op">)</span>
-<span class="co"># # A tibble: 4,203 x 4</span>
-<span class="co"># v001 sex status statusage</span>
-<span class="co"># <dbl> <fct> <fct> <dbl></span>
-<span class="co"># 1 10002 Male alive 76.6</span>
-<span class="co"># 2 10004 Female alive 59.1</span>
-<span class="co"># 3 10005 Male alive 54.5</span>
-<span class="co"># 4 10006 Male alive 54.1</span>
-<span class="co"># 5 10007 Male alive 57.7</span>
-<span class="co"># 6 10008 Male alive 62.8</span>
-<span class="co"># 7 10010 Female alive 63.7</span>
-<span class="co"># 8 10011 Male alive 73.1</span>
-<span class="co"># 9 10017 Male alive 56.7</span>
-<span class="co"># 10 10018 Female alive 66.6</span>
-<span class="co"># # ... with 4,193 more rows</span></code></pre></div>
-</div>
-<div class="section level3">
-<h3 id="base-r">Base R<a class="anchor" aria-label="anchor" href="#base-r"></a>
-</h3>
-<p>To import data from SPSS, SAS or Stata, you can use the <a href="https://haven.tidyverse.org/" class="external-link">great <code>haven</code> package</a>
-yourself:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># download and install the latest version:</span>
-<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"haven"</span><span class="op">)</span>
-<span class="co"># load the package you just installed:</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://haven.tidyverse.org" class="external-link">haven</a></span><span class="op">)</span> </code></pre></div>
-<p>You can now import files as follows:</p>
-<div class="section level4">
-<h4 id="spss">SPSS<a class="anchor" aria-label="anchor" href="#spss"></a>
-</h4>
-<p>To read files from SPSS into R:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># read any SPSS file based on file extension (best way):</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">read_spss</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
-
-<span class="co"># read .sav or .zsav file:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">read_sav</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
-
-<span class="co"># read .por file:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">read_por</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></code></pre></div>
-<p>Do not forget about <code><a href="https://haven.tidyverse.org/reference/as_factor.html" class="external-link">as_factor()</a></code>, as mentioned above.</p>
-<p>To export your R objects to the SPSS file format:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># save as .sav file:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">write_sav</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
-
-<span class="co"># save as compressed .zsav file:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">write_sav</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, compress <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div>
-</div>
-<div class="section level4">
-<h4 id="sas">SAS<a class="anchor" aria-label="anchor" href="#sas"></a>
-</h4>
-<p>To read files from SAS into R:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># read .sas7bdat + .sas7bcat files:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html" class="external-link">read_sas</a></span><span class="op">(</span>data_file <span class="op">=</span> <span class="st">"path/to/file"</span>, catalog_file <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span>
-
-<span class="co"># read SAS transport files (version 5 and version 8):</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html" class="external-link">read_xpt</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></code></pre></div>
-<p>To export your R objects to the SAS file format:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># save as regular SAS file:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html" class="external-link">write_sas</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
-
-<span class="co"># the SAS transport format is an open format </span>
-<span class="co"># (required for submission of the data to the FDA)</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html" class="external-link">write_xpt</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, version <span class="op">=</span> <span class="fl">8</span><span class="op">)</span></code></pre></div>
-</div>
-<div class="section level4">
-<h4 id="stata">Stata<a class="anchor" aria-label="anchor" href="#stata"></a>
-</h4>
-<p>To read files from Stata into R:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># read .dta file:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html" class="external-link">read_stata</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span>
-
-<span class="co"># works exactly the same:</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html" class="external-link">read_dta</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span></code></pre></div>
-<p>To export your R objects to the Stata file format:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># save as .dta file, Stata version 14:</span>
-<span class="co"># (supports Stata v8 until v15 at the time of writing)</span>
-<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html" class="external-link">write_dta</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"/path/to/file"</span>, version <span class="op">=</span> <span class="fl">14</span><span class="op">)</span></code></pre></div>
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- <h1 data-toc-skip>How to work with WHONET data</h1>
-
-
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/WHONET.Rmd" class="external-link"><code>vignettes/WHONET.Rmd</code></a></small>
- <div class="hidden name"><code>WHONET.Rmd</code></div>
-
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-
-<div class="section level3">
-<h3 id="import-of-data">Import of data<a class="anchor" aria-label="anchor" href="#import-of-data"></a>
-</h3>
-<p>This tutorial assumes you already imported the WHONET data with
-e.g. the <a href="https://readxl.tidyverse.org/" class="external-link"><code>readxl</code>
-package</a>. In RStudio, this can be done using the menu button ‘Import
-Dataset’ in the tab ‘Environment’. Choose the option ‘From Excel’ and
-select your exported file. Make sure date fields are imported
-correctly.</p>
-<p>An example syntax could look like this:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://readxl.tidyverse.org" class="external-link">readxl</a></span><span class="op">)</span>
-<span class="va">data</span> <span class="op"><-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html" class="external-link">read_excel</a></span><span class="op">(</span>path <span class="op">=</span> <span class="st">"path/to/your/file.xlsx"</span><span class="op">)</span></code></pre></div>
-<p>This package comes with an <a href="https://msberends.github.io/AMR/reference/WHONET.html">example
-data set <code>WHONET</code></a>. We will use it for this analysis.</p>
-</div>
-<div class="section level3">
-<h3 id="preparation">Preparation<a class="anchor" aria-label="anchor" href="#preparation"></a>
-</h3>
-<p>First, load the relevant packages if you did not yet did this. I use
-the tidyverse for all of my analyses. All of them. If you don’t know it
-yet, I suggest you read about it on their website: <a href="https://www.tidyverse.org/" class="external-link uri">https://www.tidyverse.org/</a>.</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span> <span class="co"># this package</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
-<p>We will have to transform some variables to simplify and automate the
-analysis:</p>
-<ul>
-<li>Microorganisms should be transformed to our own microorganism codes
-(called an <code>mo</code>) using <a href="https://msberends.github.io/AMR/reference/catalogue_of_life">our
-Catalogue of Life reference data set</a>, which contains all ~70,000
-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>
-</ul>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># transform variables</span>
-<span class="va">data</span> <span class="op"><-</span> <span class="va">WHONET</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># get microbial ID based on given organism</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">Organism</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMP_ND10</span><span class="op">:</span><span class="va">CIP_EE</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span></code></pre></div>
-<p>No errors or warnings, so all values are transformed succesfully.</p>
-<p>We also created a package dedicated to data cleaning and checking,
-called the <code>cleaner</code> package. Its <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq()</a></code>
-function can be used to create frequency tables.</p>
-<p>So let’s check our data, with a couple of frequency tables:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># our newly created `mo` variable, put in the mo_name() function</span>
-<span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, nmax <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></code></pre></div>
-<p><strong>Frequency table</strong></p>
-<p>Class: character<br>
-Length: 500<br>
-Available: 500 (100%, NA: 0 = 0%)<br>
-Unique: 37</p>
-<p>Shortest: 11<br>
-Longest: 40</p>
-<table class="table">
-<colgroup>
-<col width="4%">
-<col width="47%">
-<col width="7%">
-<col width="10%">
-<col width="13%">
-<col width="15%">
-</colgroup>
-<thead><tr class="header">
-<th align="left"></th>
-<th align="left">Item</th>
-<th align="right">Count</th>
-<th align="right">Percent</th>
-<th align="right">Cum. Count</th>
-<th align="right">Cum. Percent</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">1</td>
-<td align="left">Escherichia coli</td>
-<td align="right">245</td>
-<td align="right">49.0%</td>
-<td align="right">245</td>
-<td align="right">49.0%</td>
-</tr>
-<tr class="even">
-<td align="left">2</td>
-<td align="left">Coagulase-negative Staphylococcus (CoNS)</td>
-<td align="right">74</td>
-<td align="right">14.8%</td>
-<td align="right">319</td>
-<td align="right">63.8%</td>
-</tr>
-<tr class="odd">
-<td align="left">3</td>
-<td align="left">Staphylococcus epidermidis</td>
-<td align="right">38</td>
-<td align="right">7.6%</td>
-<td align="right">357</td>
-<td align="right">71.4%</td>
-</tr>
-<tr class="even">
-<td align="left">4</td>
-<td align="left">Streptococcus pneumoniae</td>
-<td align="right">31</td>
-<td align="right">6.2%</td>
-<td align="right">388</td>
-<td align="right">77.6%</td>
-</tr>
-<tr class="odd">
-<td align="left">5</td>
-<td align="left">Staphylococcus hominis</td>
-<td align="right">21</td>
-<td align="right">4.2%</td>
-<td align="right">409</td>
-<td align="right">81.8%</td>
-</tr>
-<tr class="even">
-<td align="left">6</td>
-<td align="left">Proteus mirabilis</td>
-<td align="right">9</td>
-<td align="right">1.8%</td>
-<td align="right">418</td>
-<td align="right">83.6%</td>
-</tr>
-<tr class="odd">
-<td align="left">7</td>
-<td align="left">Enterococcus faecium</td>
-<td align="right">8</td>
-<td align="right">1.6%</td>
-<td align="right">426</td>
-<td align="right">85.2%</td>
-</tr>
-<tr class="even">
-<td align="left">8</td>
-<td align="left">Staphylococcus capitis</td>
-<td align="right">8</td>
-<td align="right">1.6%</td>
-<td align="right">434</td>
-<td align="right">86.8%</td>
-</tr>
-<tr class="odd">
-<td align="left">9</td>
-<td align="left">Enterobacter cloacae</td>
-<td align="right">5</td>
-<td align="right">1.0%</td>
-<td align="right">439</td>
-<td align="right">87.8%</td>
-</tr>
-<tr class="even">
-<td align="left">10</td>
-<td align="left">Streptococcus anginosus</td>
-<td align="right">5</td>
-<td align="right">1.0%</td>
-<td align="right">444</td>
-<td align="right">88.8%</td>
-</tr>
-</tbody>
-</table>
-<p>(omitted 27 entries, n = 56 [11.2%])</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># our transformed antibiotic columns</span>
-<span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span>
-<span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="va">AMC_ND2</span><span class="op">)</span></code></pre></div>
-<p><strong>Frequency table</strong></p>
-<p>Class: factor > ordered > rsi (numeric)<br>
-Length: 500<br>
-Levels: 3: S < I < R<br>
-Available: 481 (96.2%, NA: 19 = 3.8%)<br>
-Unique: 3</p>
-<p>Drug: Amoxicillin/clavulanic acid (AMC, J01CR02)<br>
-Drug group: Beta-lactams/penicillins<br>
-%SI: 78.59%</p>
-<table class="table">
-<thead><tr class="header">
-<th align="left"></th>
-<th align="left">Item</th>
-<th align="right">Count</th>
-<th align="right">Percent</th>
-<th align="right">Cum. Count</th>
-<th align="right">Cum. Percent</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">1</td>
-<td align="left">S</td>
-<td align="right">356</td>
-<td align="right">74.01%</td>
-<td align="right">356</td>
-<td align="right">74.01%</td>
-</tr>
-<tr class="even">
-<td align="left">2</td>
-<td align="left">R</td>
-<td align="right">103</td>
-<td align="right">21.41%</td>
-<td align="right">459</td>
-<td align="right">95.43%</td>
-</tr>
-<tr class="odd">
-<td align="left">3</td>
-<td align="left">I</td>
-<td align="right">22</td>
-<td align="right">4.57%</td>
-<td align="right">481</td>
-<td align="right">100.00%</td>
-</tr>
-</tbody>
-</table>
-</div>
-<div class="section level3">
-<h3 id="a-first-glimpse-at-results">A first glimpse at results<a class="anchor" aria-label="anchor" href="#a-first-glimpse-at-results"></a>
-</h3>
-<p>An easy <code>ggplot</code> will already give a lot of information,
-using the included <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> function:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Country</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">Country</span>, <span class="va">AMP_ND2</span>, <span class="va">AMC_ED20</span>, <span class="va">CAZ_ED10</span>, <span class="va">CIP_ED5</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/ggplot_rsi.html">ggplot_rsi</a></span><span class="op">(</span>translate_ab <span class="op">=</span> <span class="st">'ab'</span>, facet <span class="op">=</span> <span class="st">"Country"</span>, datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
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- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/benchmarks.Rmd" class="external-link"><code>vignettes/benchmarks.Rmd</code></a></small>
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-<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> (CoL) and the <a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN). We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the microbial taxonomy.</p>
-<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/" class="external-link">microbenchmark</a></span><span class="op">)</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></code></pre></div>
-<p>In the next test, we try to ‘coerce’ different input values into the microbial code of <em>Staphylococcus aureus</em>. Coercion is a computational process of forcing output based on an input. For microorganism names, coercing user input to taxonomically valid microorganism names is crucial to ensure correct interpretation and to enable grouping based on taxonomic properties.</p>
-<p>The actual result is the same every time: it returns its microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for <em>Bacteria</em>, its taxonomic kingdom).</p>
-<p>But the calculation time differs a lot:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">S.aureus</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"sau"</span><span class="op">)</span>, <span class="co"># WHONET code</span>
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"stau"</span><span class="op">)</span>,
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"STAU"</span><span class="op">)</span>,
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"staaur"</span><span class="op">)</span>,
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>,
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"S aureus"</span><span class="op">)</span>,
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span>, <span class="co"># official taxonomic name</span>
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus (MRSA)"</span><span class="op">)</span>, <span class="co"># additional text</span>
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"Sthafilokkockus aaureuz"</span><span class="op">)</span>, <span class="co"># incorrect spelling</span>
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"MRSA"</span><span class="op">)</span>, <span class="co"># Methicillin Resistant S. aureus</span>
- <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"VISA"</span><span class="op">)</span>, <span class="co"># Vancomycin Intermediate S. aureus</span>
- times <span class="op">=</span> <span class="fl">25</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>
-<span class="co"># Unit: milliseconds</span>
-<span class="co"># expr min lq mean median uq max neval</span>
-<span class="co"># as.mo("sau") 19.0 20.0 25.0 20.0 26.0 55 25</span>
-<span class="co"># as.mo("stau") 94.0 95.0 110.0 100.0 130.0 140 25</span>
-<span class="co"># as.mo("STAU") 92.0 97.0 110.0 110.0 120.0 140 25</span>
-<span class="co"># as.mo("staaur") 19.0 19.0 24.0 20.0 21.0 56 25</span>
-<span class="co"># as.mo("STAAUR") 19.0 20.0 21.0 20.0 20.0 49 25</span>
-<span class="co"># as.mo("S. aureus") 54.0 57.0 72.0 64.0 86.0 96 25</span>
-<span class="co"># as.mo("S aureus") 55.0 55.0 72.0 57.0 90.0 100 25</span>
-<span class="co"># as.mo("Staphylococcus aureus") 5.6 5.7 8.5 5.8 6.2 40 25</span>
-<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 360.0 370.0 400.0 400.0 420.0 550 25</span>
-<span class="co"># as.mo("Sthafilokkockus aaureuz") 280.0 290.0 300.0 300.0 320.0 350 25</span>
-<span class="co"># as.mo("MRSA") 19.0 20.0 24.0 20.0 21.0 51 25</span>
-<span class="co"># as.mo("VISA") 34.0 34.0 48.0 36.0 65.0 73 25</span></code></pre></div>
-<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="750"></p>
-<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 200 milliseconds, this is only 5 input values per second. It is clear that accepted taxonomic names are extremely fast, but some variations are up to 69 times slower to determine.</p>
-<p>To improve performance, we implemented two important algorithms to save unnecessary calculations: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
-<div class="section level3">
-<h3 id="repetitive-results">Repetitive results<a class="anchor" aria-label="anchor" href="#repetitive-results"></a>
-</h3>
-<p>Repetitive results are values that are present more than once in a vector. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. So running <code>as.mo(c("E. coli", "E. coli"))</code> will check the value <code>"E. coli"</code> only once.</p>
-<p>To prove this, we will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for testing - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="co"># start with the example_isolates data set</span>
-<span class="va">x</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># take all MO codes from the 'mo' column</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># and copy them a thousand times</span>
- <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="fl">1000</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># then scramble them</span>
- <span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="op">)</span>
-
-<span class="co"># what do these values look like? They are of class <mo>:</span>
-<span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-<span class="co"># Class <mo></span>
-<span class="co"># [1] B_ENTRBC_CLOC B_ESCHR_COLI B_STRPT_PYGN B_STPHY_AURS B_ESCHR_COLI </span>
-<span class="co"># [6] B_STRPT_PNMN</span>
-
-<span class="co"># as the example_isolates data set has 2,000 rows, we should have 2 million items</span>
-<span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-<span class="co"># [1] 2000000</span>
-
-<span class="co"># and how many unique values do we have?</span>
-<span class="fu"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-<span class="co"># [1] 90</span>
-
-<span class="co"># now let's see:</span>
-<span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>,
- times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
-<span class="co"># Unit: milliseconds</span>
-<span class="co"># expr min lq mean median uq max neval</span>
-<span class="co"># mo_name(x) 259 264 357 299 451 509 10</span></code></pre></div>
-<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.299 seconds. That is 149 nanoseconds on average. You only lose time on your unique input values.</p>
-</div>
-<div class="section level3">
-<h3 id="precalculated-results">Precalculated results<a class="anchor" aria-label="anchor" href="#precalculated-results"></a>
-</h3>
-<p>What about precalculated results? If the input is an already precalculated result of a helper function such as <code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesn’t take any time at all. In other words, if you run <code><a href="../reference/mo_property.html">mo_name()</a></code> on a valid taxonomic name, it will return the results immediately (see ‘C’ below):</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
- B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>,
- C <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span>,
- times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
-<span class="co"># Unit: milliseconds</span>
-<span class="co"># expr min lq mean median uq max neval</span>
-<span class="co"># A 11.90 12.10 13.0 13.50 13.70 13.80 10</span>
-<span class="co"># B 60.90 61.20 67.7 66.20 66.90 99.70 10</span>
-<span class="co"># C 2.91 2.94 3.2 3.32 3.38 3.46 10</span></code></pre></div>
-<p>So going from <code>mo_name("Staphylococcus aureus")</code> to <code>"Staphylococcus aureus"</code> takes 0.0033 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>,
- B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"Staphylococcus"</span><span class="op">)</span>,
- C <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span>,
- D <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="st">"Staphylococcaceae"</span><span class="op">)</span>,
- E <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="st">"Bacillales"</span><span class="op">)</span>,
- F <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_class</a></span><span class="op">(</span><span class="st">"Bacilli"</span><span class="op">)</span>,
- G <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_phylum</a></span><span class="op">(</span><span class="st">"Firmicutes"</span><span class="op">)</span>,
- H <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_kingdom</a></span><span class="op">(</span><span class="st">"Bacteria"</span><span class="op">)</span>,
- times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
-<span class="co"># Unit: milliseconds</span>
-<span class="co"># expr min lq mean median uq max neval</span>
-<span class="co"># A 2.92 2.93 3.02 2.94 3.02 3.40 10</span>
-<span class="co"># B 2.87 2.90 3.14 3.09 3.32 3.71 10</span>
-<span class="co"># C 2.91 2.94 3.15 3.12 3.33 3.46 10</span>
-<span class="co"># D 2.86 2.90 3.05 2.96 3.27 3.30 10</span>
-<span class="co"># E 2.87 2.88 3.03 2.96 3.16 3.29 10</span>
-<span class="co"># F 2.92 2.95 3.08 2.98 3.29 3.35 10</span>
-<span class="co"># G 2.89 2.96 3.04 2.99 3.11 3.29 10</span>
-<span class="co"># H 2.85 2.95 3.11 3.08 3.31 3.38 10</span></code></pre></div>
-<p>Of course, when running <code>mo_phylum("Firmicutes")</code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> anyway, there is no point in calculating the result. And because this package contains all phyla of all known bacteria, it can just return the initial value immediately.</p>
-</div>
-<div class="section level3">
-<h3 id="results-in-other-languages">Results in other languages<a class="anchor" aria-label="anchor" href="#results-in-other-languages"></a>
-</h3>
-<p>When the system language is non-English and supported by this <code>AMR</code> package, some functions will have a translated result. This almost does’t take extra time (compare “en” from the table below with the other languages):</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">CoNS</span> <span class="op"><-</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"CoNS"</span><span class="op">)</span>
-<span class="va">CoNS</span>
-<span class="co"># Class <mo></span>
-<span class="co"># [1] B_STPHY_CONS</span>
-
-<span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span> <span class="co"># or just mo_name(CoNS) on an English system</span>
-<span class="co"># [1] "Coagulase-negative Staphylococcus (CoNS)"</span>
-
-<span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span> <span class="co"># or just mo_name(CoNS) on a Spanish system</span>
-<span class="co"># [1] "Staphylococcus coagulasa negativo (SCN)"</span>
-
-<span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"nl"</span><span class="op">)</span> <span class="co"># or just mo_name(CoNS) on a Dutch system</span>
-<span class="co"># [1] "Coagulase-negatieve Staphylococcus (CNS)"</span>
-
-<span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>da <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"da"</span><span class="op">)</span>,
- de <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"de"</span><span class="op">)</span>,
- en <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span>,
- es <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span>,
- fr <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"fr"</span><span class="op">)</span>,
- it <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"it"</span><span class="op">)</span>,
- nl <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"nl"</span><span class="op">)</span>,
- pt <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"pt"</span><span class="op">)</span>,
- ru <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"ru"</span><span class="op">)</span>,
- sv <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">CoNS</span>, language <span class="op">=</span> <span class="st">"sv"</span><span class="op">)</span>,
- times <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span>
-<span class="co"># Unit: milliseconds</span>
-<span class="co"># expr min lq mean median uq max neval</span>
-<span class="co"># da 3.546 3.643 4.072 3.704 3.832 35.930 100</span>
-<span class="co"># de 3.597 3.659 4.422 3.734 3.839 36.400 100</span>
-<span class="co"># en 1.672 1.726 1.804 1.767 1.794 2.259 100</span>
-<span class="co"># es 3.609 3.685 4.496 3.760 3.843 36.540 100</span>
-<span class="co"># fr 3.484 3.567 3.725 3.654 3.713 6.281 100</span>
-<span class="co"># it 3.523 3.615 4.419 3.720 3.787 36.720 100</span>
-<span class="co"># nl 3.614 3.676 3.805 3.732 3.838 4.703 100</span>
-<span class="co"># pt 3.512 3.595 4.077 3.659 3.789 37.310 100</span>
-<span class="co"># ru 3.556 3.647 4.057 3.680 3.812 35.230 100</span>
-<span class="co"># sv 3.540 3.642 4.093 3.732 3.803 36.340 100</span></code></pre></div>
-<p>Currently supported languages are Danish, Dutch, English, French, German, Italian, Portuguese, Russian, Spanish and Swedish.</p>
-</div>
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- <h1 data-toc-skip>Data sets for download / own use</h1>
-
- <h4 data-toc-skip class="date">12 August 2022</h4>
-
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
- <div class="hidden name"><code>datasets.Rmd</code></div>
-
- </div>
-
-
-
-<p>All reference data (about microorganisms, antibiotics, R/SI
-interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are
-reliable, up-to-date and freely available. We continually export our
-data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also
-supply tab separated files that are machine-readable and suitable for
-input in any software program, such as laboratory information
-systems.</p>
-<p>On this page, we explain how to download them and how the structure
-of the data sets look like.</p>
-<p class="dataset-within-r">
-If you are reading this page from within R, please
-<a href="https://msberends.github.io/AMR/articles/datasets.html">visit
-our website</a>, which is automatically updated with every code change.
-</p>
-<div class="section level2">
-<h2 id="microorganisms-currently-accepted-names">Microorganisms (currently accepted names)<a class="anchor" aria-label="anchor" href="#microorganisms-currently-accepted-names"></a>
-</h2>
-<p>A data set with 70,760 rows and 16 columns, containing the following
-column names:<br><em>mo</em>, <em>fullname</em>, <em>kingdom</em>, <em>phylum</em>,
-<em>class</em>, <em>order</em>, <em>family</em>, <em>genus</em>,
-<em>species</em>, <em>subspecies</em>, <em>rank</em>, <em>ref</em>,
-<em>species_id</em>, <em>source</em>, <em>prevalence</em> and
-<em>snomed</em>.</p>
-<p>This data set is in R available as <code>microorganisms</code>, after
-you load the <code>AMR</code> package.</p>
-<p>It was last updated on 13 June 2022 13:55:27 UTC. Find more info
-about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.html">here</a>.</p>
-<p><strong>Direct download links:</strong></p>
-<ul>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.rds" class="external-link">R
-file</a> (1.3 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.xlsx" class="external-link">Excel
-file</a> (4.8 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.txt" class="external-link">plain
-text file</a> (13.1 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.sas" class="external-link">SAS
-file</a> (30.7 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.sav" class="external-link">SPSS
-file</a> (16.3 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.dta" class="external-link">Stata
-file</a> (27.5 MB)</li>
-</ul>
-<p><strong>NOTE: The exported files for SAS, SPSS and Stata do not
-contain SNOMED codes, as their file size would exceed 100 MB; the file
-size limit of GitHub.</strong> Advice? Use R instead.</p>
-<div class="section level3">
-<h3 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a>
-</h3>
-<p>Our full taxonomy of microorganisms is based on the authoritative and
-comprehensive:</p>
-<ul>
-<li>
-<a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a>
-(included version: 2019)</li>
-<li>
-<a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with
-Standing in Nomenclature</a> (LPSN, last updated: 5 October 2021)</li>
-<li>US Edition of SNOMED CT from 1 September 2020, retrieved from the <a href="https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009" class="external-link">Public
-Health Information Network Vocabulary Access and Distribution System
-(PHIN VADS)</a>, OID 2.16.840.1.114222.4.11.1009, version 12</li>
-</ul>
-</div>
-<div class="section level3">
-<h3 id="example-content">Example content<a class="anchor" aria-label="anchor" href="#example-content"></a>
-</h3>
-<p>Included (sub)species per taxonomic kingdom:</p>
-<table class="table">
-<thead><tr class="header">
-<th align="center">Kingdom</th>
-<th align="center">Number of (sub)species</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">(unknown kingdom)</td>
-<td align="center">1</td>
-</tr>
-<tr class="even">
-<td align="center">Animalia</td>
-<td align="center">2,153</td>
-</tr>
-<tr class="odd">
-<td align="center">Archaea</td>
-<td align="center">694</td>
-</tr>
-<tr class="even">
-<td align="center">Bacteria</td>
-<td align="center">22,852</td>
-</tr>
-<tr class="odd">
-<td align="center">Chromista</td>
-<td align="center">32,167</td>
-</tr>
-<tr class="even">
-<td align="center">Fungi</td>
-<td align="center">9,582</td>
-</tr>
-</tbody>
-</table>
-<p>Example rows when filtering on genus <em>Escherichia</em>:</p>
-<table style="width:100%;" class="table">
-<colgroup>
-<col width="5%">
-<col width="8%">
-<col width="3%">
-<col width="5%">
-<col width="7%">
-<col width="6%">
-<col width="7%">
-<col width="4%">
-<col width="4%">
-<col width="4%">
-<col width="3%">
-<col width="9%">
-<col width="4%">
-<col width="2%">
-<col width="4%">
-<col width="16%">
-</colgroup>
-<thead><tr class="header">
-<th align="center">mo</th>
-<th align="center">fullname</th>
-<th align="center">kingdom</th>
-<th align="center">phylum</th>
-<th align="center">class</th>
-<th align="center">order</th>
-<th align="center">family</th>
-<th align="center">genus</th>
-<th align="center">species</th>
-<th align="center">subspecies</th>
-<th align="center">rank</th>
-<th align="center">ref</th>
-<th align="center">species_id</th>
-<th align="center">source</th>
-<th align="center">prevalence</th>
-<th align="center">snomed</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">B_ESCHR</td>
-<td align="center">Escherichia</td>
-<td align="center">Bacteria</td>
-<td align="center">Proteobacteria</td>
-<td align="center">Gammaproteobacteria</td>
-<td align="center">Enterobacterales</td>
-<td align="center">Enterobacteriaceae</td>
-<td align="center">Escherichia</td>
-<td align="center"></td>
-<td align="center"></td>
-<td align="center">genus</td>
-<td align="center"></td>
-<td align="center">515602</td>
-<td align="center">LPSN</td>
-<td align="center">1</td>
-<td align="center">64735005</td>
-</tr>
-<tr class="even">
-<td align="center">B_ESCHR_ALBR</td>
-<td align="center">Escherichia albertii</td>
-<td align="center">Bacteria</td>
-<td align="center">Proteobacteria</td>
-<td align="center">Gammaproteobacteria</td>
-<td align="center">Enterobacterales</td>
-<td align="center">Enterobacteriaceae</td>
-<td align="center">Escherichia</td>
-<td align="center">albertii</td>
-<td align="center"></td>
-<td align="center">species</td>
-<td align="center">Huys et al., 2003</td>
-<td align="center">776053</td>
-<td align="center">LPSN</td>
-<td align="center">1</td>
-<td align="center">419388003</td>
-</tr>
-<tr class="odd">
-<td align="center">B_ESCHR_COLI</td>
-<td align="center">Escherichia coli</td>
-<td align="center">Bacteria</td>
-<td align="center">Proteobacteria</td>
-<td align="center">Gammaproteobacteria</td>
-<td align="center">Enterobacterales</td>
-<td align="center">Enterobacteriaceae</td>
-<td align="center">Escherichia</td>
-<td align="center">coli</td>
-<td align="center"></td>
-<td align="center">species</td>
-<td align="center">Castellani et al., 1919</td>
-<td align="center">776057</td>
-<td align="center">LPSN</td>
-<td align="center">1</td>
-<td align="center">1095001000112106, 715307006, 737528008, …</td>
-</tr>
-<tr class="even">
-<td align="center">B_ESCHR_FRGS</td>
-<td align="center">Escherichia fergusonii</td>
-<td align="center">Bacteria</td>
-<td align="center">Proteobacteria</td>
-<td align="center">Gammaproteobacteria</td>
-<td align="center">Enterobacterales</td>
-<td align="center">Enterobacteriaceae</td>
-<td align="center">Escherichia</td>
-<td align="center">fergusonii</td>
-<td align="center"></td>
-<td align="center">species</td>
-<td align="center">Farmer et al., 1985</td>
-<td align="center">776059</td>
-<td align="center">LPSN</td>
-<td align="center">1</td>
-<td align="center">72461005</td>
-</tr>
-<tr class="odd">
-<td align="center">B_ESCHR_HRMN</td>
-<td align="center">Escherichia hermannii</td>
-<td align="center">Bacteria</td>
-<td align="center">Proteobacteria</td>
-<td align="center">Gammaproteobacteria</td>
-<td align="center">Enterobacterales</td>
-<td align="center">Enterobacteriaceae</td>
-<td align="center">Escherichia</td>
-<td align="center">hermannii</td>
-<td align="center"></td>
-<td align="center">species</td>
-<td align="center">Brenner et al., 1983</td>
-<td align="center">776060</td>
-<td align="center">LPSN</td>
-<td align="center">1</td>
-<td align="center">85786000</td>
-</tr>
-<tr class="even">
-<td align="center">B_ESCHR_MRMT</td>
-<td align="center">Escherichia marmotae</td>
-<td align="center">Bacteria</td>
-<td align="center">Proteobacteria</td>
-<td align="center">Gammaproteobacteria</td>
-<td align="center">Enterobacterales</td>
-<td align="center">Enterobacteriaceae</td>
-<td align="center">Escherichia</td>
-<td align="center">marmotae</td>
-<td align="center"></td>
-<td align="center">species</td>
-<td align="center">Liu et al., 2015</td>
-<td align="center">792928</td>
-<td align="center">LPSN</td>
-<td align="center">1</td>
-<td align="center">14961000146107</td>
-</tr>
-</tbody>
-</table>
-</div>
-</div>
-<div class="section level2">
-<h2 id="microorganisms-previously-accepted-names">Microorganisms (previously accepted names)<a class="anchor" aria-label="anchor" href="#microorganisms-previously-accepted-names"></a>
-</h2>
-<p>A data set with 14,338 rows and 4 columns, containing the following
-column names:<br><em>fullname</em>, <em>fullname_new</em>, <em>ref</em> and
-<em>prevalence</em>.</p>
-<p><strong>Note:</strong> remember that the ‘ref’ columns contains the
-scientific reference to the old taxonomic entries, i.e. of column
-<em>‘fullname’</em>. For the scientific reference of the new names,
-i.e. of column <em>‘fullname_new’</em>, see the
-<code>microorganisms</code> data set.</p>
-<p>This data set is in R available as <code>microorganisms.old</code>,
-after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 3 June 2022 11:18:30 UTC. Find more info about
-the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.old.html">here</a>.</p>
-<p><strong>Direct download links:</strong></p>
-<ul>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.old.rds" class="external-link">R
-file</a> (0.2 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.old.xlsx" class="external-link">Excel
-file</a> (0.5 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.old.txt" class="external-link">plain
-text file</a> (1 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.old.sas" class="external-link">SAS
-file</a> (2.1 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.old.sav" class="external-link">SPSS
-file</a> (1.3 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.old.dta" class="external-link">Stata
-file</a> (2 MB)</li>
-</ul>
-<div class="section level3">
-<h3 id="source-1">Source<a class="anchor" aria-label="anchor" href="#source-1"></a>
-</h3>
-<p>This data set contains old, previously accepted taxonomic names. The
-data sources are the same as the <code>microorganisms</code> data
-set:</p>
-<ul>
-<li>
-<a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a>
-(included version: 2019)</li>
-<li>
-<a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with
-Standing in Nomenclature</a> (LPSN, last updated: 5 October 2021)</li>
-</ul>
-</div>
-<div class="section level3">
-<h3 id="example-content-1">Example content<a class="anchor" aria-label="anchor" href="#example-content-1"></a>
-</h3>
-<p>Example rows when filtering on <em>Escherichia</em>:</p>
-<table style="width:100%;" class="table">
-<colgroup>
-<col width="31%">
-<col width="30%">
-<col width="24%">
-<col width="13%">
-</colgroup>
-<thead><tr class="header">
-<th align="center">fullname</th>
-<th align="center">fullname_new</th>
-<th align="center">ref</th>
-<th align="center">prevalence</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">Escherichia adecarboxylata</td>
-<td align="center">Leclercia adecarboxylata</td>
-<td align="center">Leclerc, 1962</td>
-<td align="center">1</td>
-</tr>
-<tr class="even">
-<td align="center">Escherichia blattae</td>
-<td align="center">Shimwellia blattae</td>
-<td align="center">Burgess et al., 1973</td>
-<td align="center">1</td>
-</tr>
-<tr class="odd">
-<td align="center">Escherichia vulneris</td>
-<td align="center">Pseudescherichia vulneris</td>
-<td align="center">Brenner et al., 1983</td>
-<td align="center">1</td>
-</tr>
-</tbody>
-</table>
-</div>
-</div>
-<div class="section level2">
-<h2 id="antibiotic-agents">Antibiotic agents<a class="anchor" aria-label="anchor" href="#antibiotic-agents"></a>
-</h2>
-<p>A data set with 464 rows and 14 columns, containing the following
-column names:<br><em>ab</em>, <em>cid</em>, <em>name</em>, <em>group</em>, <em>atc</em>,
-<em>atc_group1</em>, <em>atc_group2</em>, <em>abbreviations</em>,
-<em>synonyms</em>, <em>oral_ddd</em>, <em>oral_units</em>,
-<em>iv_ddd</em>, <em>iv_units</em> and <em>loinc</em>.</p>
-<p>This data set is in R available as <code>antibiotics</code>, after
-you load the <code>AMR</code> package.</p>
-<p>It was last updated on 14 December 2021 21:59:33 UTC. Find more info
-about the structure of this data set <a href="https://msberends.github.io/AMR/reference/antibiotics.html">here</a>.</p>
-<p><strong>Direct download links:</strong></p>
-<ul>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antibiotics.rds" class="external-link">R
-file</a> (33 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antibiotics.xlsx" class="external-link">Excel
-file</a> (65 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antibiotics.txt" class="external-link">plain
-text file</a> (0.1 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antibiotics.sas" class="external-link">SAS
-file</a> (1.8 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antibiotics.sav" class="external-link">SPSS
-file</a> (0.3 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antibiotics.dta" class="external-link">Stata
-file</a> (0.3 MB)</li>
-</ul>
-<div class="section level3">
-<h3 id="source-2">Source<a class="anchor" aria-label="anchor" href="#source-2"></a>
-</h3>
-<p>This data set contains all EARS-Net and ATC codes gathered from WHO
-and WHONET, and all compound IDs from PubChem. It also contains all
-brand names (synonyms) as found on PubChem and Defined Daily Doses
-(DDDs) for oral and parenteral administration.</p>
-<ul>
-<li>
-<a href="https://www.whocc.no/atc_ddd_index/" class="external-link">ATC/DDD index from WHO
-Collaborating Centre for Drug Statistics Methodology</a> (note: this may
-not be used for commercial purposes, but is freely available from the
-WHO CC website for personal use)</li>
-<li><a href="https://pubchem.ncbi.nlm.nih.gov" class="external-link">PubChem by the US
-National Library of Medicine</a></li>
-<li><a href="https://whonet.org" class="external-link">WHONET software 2019</a></li>
-</ul>
-</div>
-<div class="section level3">
-<h3 id="example-content-2">Example content<a class="anchor" aria-label="anchor" href="#example-content-2"></a>
-</h3>
-<table style="width:100%;" class="table">
-<colgroup>
-<col width="1%">
-<col width="2%">
-<col width="8%">
-<col width="7%">
-<col width="7%">
-<col width="13%">
-<col width="17%">
-<col width="6%">
-<col width="13%">
-<col width="2%">
-<col width="3%">
-<col width="2%">
-<col width="2%">
-<col width="9%">
-</colgroup>
-<thead><tr class="header">
-<th align="center">ab</th>
-<th align="center">cid</th>
-<th align="center">name</th>
-<th align="center">group</th>
-<th align="center">atc</th>
-<th align="center">atc_group1</th>
-<th align="center">atc_group2</th>
-<th align="center">abbreviations</th>
-<th align="center">synonyms</th>
-<th align="center">oral_ddd</th>
-<th align="center">oral_units</th>
-<th align="center">iv_ddd</th>
-<th align="center">iv_units</th>
-<th align="center">loinc</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">AMK</td>
-<td align="center">37768</td>
-<td align="center">Amikacin</td>
-<td align="center">Aminoglycosides</td>
-<td align="center">D06AX12, J01GB06, S01AA21</td>
-<td align="center">Aminoglycoside antibacterials</td>
-<td align="center">Other aminoglycosides</td>
-<td align="center">ak, ami, amik, …</td>
-<td align="center">amicacin, amikacillin, amikacin, …</td>
-<td align="center"></td>
-<td align="center"></td>
-<td align="center">1.0</td>
-<td align="center">g</td>
-<td align="center">13546-7, 15098-7, 17798-0, …</td>
-</tr>
-<tr class="even">
-<td align="center">AMX</td>
-<td align="center">33613</td>
-<td align="center">Amoxicillin</td>
-<td align="center">Beta-lactams/penicillins</td>
-<td align="center">J01CA04</td>
-<td align="center">Beta-lactam antibacterials, penicillins</td>
-<td align="center">Penicillins with extended spectrum</td>
-<td align="center">ac, amox, amx</td>
-<td align="center">actimoxi, amoclen, amolin, …</td>
-<td align="center">1.5</td>
-<td align="center">g</td>
-<td align="center">3.0</td>
-<td align="center">g</td>
-<td align="center">16365-9, 25274-2, 3344-9, …</td>
-</tr>
-<tr class="odd">
-<td align="center">AMC</td>
-<td align="center">23665637</td>
-<td align="center">Amoxicillin/clavulanic acid</td>
-<td align="center">Beta-lactams/penicillins</td>
-<td align="center">J01CR02</td>
-<td align="center">Beta-lactam antibacterials, penicillins</td>
-<td align="center">Combinations of penicillins, incl. beta-lactamase
-inhibitors</td>
-<td align="center">a/c, amcl, aml, …</td>
-<td align="center">amocla, amoclan, amoclav, …</td>
-<td align="center">1.5</td>
-<td align="center">g</td>
-<td align="center">3.0</td>
-<td align="center">g</td>
-<td align="center"></td>
-</tr>
-<tr class="even">
-<td align="center">AMP</td>
-<td align="center">6249</td>
-<td align="center">Ampicillin</td>
-<td align="center">Beta-lactams/penicillins</td>
-<td align="center">J01CA01, S01AA19</td>
-<td align="center">Beta-lactam antibacterials, penicillins</td>
-<td align="center">Penicillins with extended spectrum</td>
-<td align="center">am, amp, ampi</td>
-<td align="center">acillin, adobacillin, amblosin, …</td>
-<td align="center">2.0</td>
-<td align="center">g</td>
-<td align="center">6.0</td>
-<td align="center">g</td>
-<td align="center">21066-6, 3355-5, 33562-0, …</td>
-</tr>
-<tr class="odd">
-<td align="center">AZM</td>
-<td align="center">447043</td>
-<td align="center">Azithromycin</td>
-<td align="center">Macrolides/lincosamides</td>
-<td align="center">J01FA10, S01AA26</td>
-<td align="center">Macrolides, lincosamides and streptogramins</td>
-<td align="center">Macrolides</td>
-<td align="center">az, azi, azit, …</td>
-<td align="center">aritromicina, azasite, azenil, …</td>
-<td align="center">0.3</td>
-<td align="center">g</td>
-<td align="center">0.5</td>
-<td align="center">g</td>
-<td align="center">16420-2, 25233-8</td>
-</tr>
-<tr class="even">
-<td align="center">PEN</td>
-<td align="center">5904</td>
-<td align="center">Benzylpenicillin</td>
-<td align="center">Beta-lactams/penicillins</td>
-<td align="center">J01CE01, S01AA14</td>
-<td align="center">Combinations of antibacterials</td>
-<td align="center">Combinations of antibacterials</td>
-<td align="center">bepe, pen, peni, …</td>
-<td align="center">abbocillin, ayercillin, bencilpenicilina, …</td>
-<td align="center"></td>
-<td align="center"></td>
-<td align="center">3.6</td>
-<td align="center">g</td>
-<td align="center">3913-1</td>
-</tr>
-</tbody>
-</table>
-</div>
-</div>
-<div class="section level2">
-<h2 id="antiviral-agents">Antiviral agents<a class="anchor" aria-label="anchor" href="#antiviral-agents"></a>
-</h2>
-<p>A data set with 102 rows and 9 columns, containing the following
-column names:<br><em>atc</em>, <em>cid</em>, <em>name</em>, <em>atc_group</em>,
-<em>synonyms</em>, <em>oral_ddd</em>, <em>oral_units</em>,
-<em>iv_ddd</em> and <em>iv_units</em>.</p>
-<p>This data set is in R available as <code>antivirals</code>, after you
-load the <code>AMR</code> package.</p>
-<p>It was last updated on 29 August 2020 19:53:07 UTC. Find more info
-about the structure of this data set <a href="https://msberends.github.io/AMR/reference/antibiotics.html">here</a>.</p>
-<p><strong>Direct download links:</strong></p>
-<ul>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antivirals.rds" class="external-link">R
-file</a> (5 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antivirals.xlsx" class="external-link">Excel
-file</a> (14 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antivirals.txt" class="external-link">plain
-text file</a> (16 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antivirals.sas" class="external-link">SAS
-file</a> (80 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antivirals.sav" class="external-link">SPSS
-file</a> (68 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antivirals.dta" class="external-link">Stata
-file</a> (67 kB)</li>
-</ul>
-<div class="section level3">
-<h3 id="source-3">Source<a class="anchor" aria-label="anchor" href="#source-3"></a>
-</h3>
-<p>This data set contains all ATC codes gathered from WHO and all
-compound IDs from PubChem. It also contains all brand names (synonyms)
-as found on PubChem and Defined Daily Doses (DDDs) for oral and
-parenteral administration.</p>
-<ul>
-<li>
-<a href="https://www.whocc.no/atc_ddd_index/" class="external-link">ATC/DDD index from WHO
-Collaborating Centre for Drug Statistics Methodology</a> (note: this may
-not be used for commercial purposes, but is freely available from the
-WHO CC website for personal use)</li>
-<li><a href="https://pubchem.ncbi.nlm.nih.gov" class="external-link">PubChem by the US
-National Library of Medicine</a></li>
-</ul>
-</div>
-<div class="section level3">
-<h3 id="example-content-3">Example content<a class="anchor" aria-label="anchor" href="#example-content-3"></a>
-</h3>
-<table class="table">
-<colgroup>
-<col width="4%">
-<col width="5%">
-<col width="9%">
-<col width="32%">
-<col width="30%">
-<col width="4%">
-<col width="5%">
-<col width="3%">
-<col width="4%">
-</colgroup>
-<thead><tr class="header">
-<th align="center">atc</th>
-<th align="center">cid</th>
-<th align="center">name</th>
-<th align="center">atc_group</th>
-<th align="center">synonyms</th>
-<th align="center">oral_ddd</th>
-<th align="center">oral_units</th>
-<th align="center">iv_ddd</th>
-<th align="center">iv_units</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">J05AF06</td>
-<td align="center">441300</td>
-<td align="center">Abacavir</td>
-<td align="center">Nucleoside and nucleotide reverse transcriptase
-inhibitors</td>
-<td align="center">Abacavir, Abacavir sulfate, Ziagen</td>
-<td align="center">0.6</td>
-<td align="center">g</td>
-<td align="center"></td>
-<td align="center"></td>
-</tr>
-<tr class="even">
-<td align="center">J05AB01</td>
-<td align="center">135398513</td>
-<td align="center">Aciclovir</td>
-<td align="center">Nucleosides and nucleotides excl. reverse
-transcriptase inhibitors</td>
-<td align="center">Acicloftal, Aciclovier, Aciclovir, …</td>
-<td align="center">4.0</td>
-<td align="center">g</td>
-<td align="center">4</td>
-<td align="center">g</td>
-</tr>
-<tr class="odd">
-<td align="center">J05AF08</td>
-<td align="center">60871</td>
-<td align="center">Adefovir dipivoxil</td>
-<td align="center">Nucleoside and nucleotide reverse transcriptase
-inhibitors</td>
-<td align="center">Adefovir di ester, Adefovir dipivoxil, Adefovir
-Dipivoxil, …</td>
-<td align="center">10.0</td>
-<td align="center">mg</td>
-<td align="center"></td>
-<td align="center"></td>
-</tr>
-<tr class="even">
-<td align="center">J05AE05</td>
-<td align="center">65016</td>
-<td align="center">Amprenavir</td>
-<td align="center">Protease inhibitors</td>
-<td align="center">Agenerase, Amprenavir, Amprenavirum, …</td>
-<td align="center">1.2</td>
-<td align="center">g</td>
-<td align="center"></td>
-<td align="center"></td>
-</tr>
-<tr class="odd">
-<td align="center">J05AP06</td>
-<td align="center">16076883</td>
-<td align="center">Asunaprevir</td>
-<td align="center">Antivirals for treatment of HCV infections</td>
-<td align="center">Asunaprevir, Sunvepra</td>
-<td align="center"></td>
-<td align="center"></td>
-<td align="center"></td>
-<td align="center"></td>
-</tr>
-<tr class="even">
-<td align="center">J05AE08</td>
-<td align="center">148192</td>
-<td align="center">Atazanavir</td>
-<td align="center">Protease inhibitors</td>
-<td align="center">Atazanavir, Atazanavir Base, Latazanavir, …</td>
-<td align="center">0.3</td>
-<td align="center">g</td>
-<td align="center"></td>
-<td align="center"></td>
-</tr>
-</tbody>
-</table>
-</div>
-</div>
-<div class="section level2">
-<h2 id="interpretation-from-mic-values-disk-diameters-to-rsi">Interpretation from MIC values / disk diameters to R/SI<a class="anchor" aria-label="anchor" href="#interpretation-from-mic-values-disk-diameters-to-rsi"></a>
-</h2>
-<p>A data set with 20,369 rows and 11 columns, containing the following
-column names:<br><em>guideline</em>, <em>method</em>, <em>site</em>, <em>mo</em>,
-<em>rank_index</em>, <em>ab</em>, <em>ref_tbl</em>, <em>disk_dose</em>,
-<em>breakpoint_S</em>, <em>breakpoint_R</em> and <em>uti</em>.</p>
-<p>This data set is in R available as <code>rsi_translation</code>,
-after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 10 May 2022 19:42:39 UTC. Find more info about
-the structure of this data set <a href="https://msberends.github.io/AMR/reference/rsi_translation.html">here</a>.</p>
-<p><strong>Direct download links:</strong></p>
-<ul>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/rsi_translation.rds" class="external-link">R
-file</a> (49 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/rsi_translation.xlsx" class="external-link">Excel
-file</a> (0.9 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/rsi_translation.txt" class="external-link">plain
-text file</a> (2 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/rsi_translation.sas" class="external-link">SAS
-file</a> (4 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/rsi_translation.sav" class="external-link">SPSS
-file</a> (2.6 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/rsi_translation.dta" class="external-link">Stata
-file</a> (3.8 MB)</li>
-</ul>
-<div class="section level3">
-<h3 id="source-4">Source<a class="anchor" aria-label="anchor" href="#source-4"></a>
-</h3>
-<p>This data set contains interpretation rules for MIC values and disk
-diffusion diameters. Included guidelines are CLSI (2011-2022) and EUCAST
-(2011-2022).</p>
-</div>
-<div class="section level3">
-<h3 id="example-content-4">Example content<a class="anchor" aria-label="anchor" href="#example-content-4"></a>
-</h3>
-<table style="width:100%;" class="table">
-<colgroup>
-<col width="8%">
-<col width="5%">
-<col width="3%">
-<col width="8%">
-<col width="14%">
-<col width="7%">
-<col width="3%">
-<col width="10%">
-<col width="8%">
-<col width="7%">
-<col width="8%">
-<col width="8%">
-<col width="4%">
-</colgroup>
-<thead><tr class="header">
-<th align="center">guideline</th>
-<th align="center">method</th>
-<th align="center">site</th>
-<th align="center">mo</th>
-<th align="center">mo_name</th>
-<th align="center">rank_index</th>
-<th align="center">ab</th>
-<th align="center">ab_name</th>
-<th align="center">ref_tbl</th>
-<th align="center">disk_dose</th>
-<th align="center">breakpoint_S</th>
-<th align="center">breakpoint_R</th>
-<th align="center">uti</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">EUCAST 2022</td>
-<td align="center">MIC</td>
-<td align="center"></td>
-<td align="center">F_ASPRG_MGTS</td>
-<td align="center">Aspergillus fumigatus</td>
-<td align="center">2</td>
-<td align="center">AMB</td>
-<td align="center">Amphotericin B</td>
-<td align="center">Aspergillus</td>
-<td align="center"></td>
-<td align="center">1</td>
-<td align="center">1</td>
-<td align="center">FALSE</td>
-</tr>
-<tr class="even">
-<td align="center">EUCAST 2022</td>
-<td align="center">MIC</td>
-<td align="center"></td>
-<td align="center">F_ASPRG_NIGR</td>
-<td align="center">Aspergillus niger</td>
-<td align="center">2</td>
-<td align="center">AMB</td>
-<td align="center">Amphotericin B</td>
-<td align="center">Aspergillus</td>
-<td align="center"></td>
-<td align="center">1</td>
-<td align="center">1</td>
-<td align="center">FALSE</td>
-</tr>
-<tr class="odd">
-<td align="center">EUCAST 2022</td>
-<td align="center">MIC</td>
-<td align="center"></td>
-<td align="center">F_CANDD</td>
-<td align="center">Candida</td>
-<td align="center">3</td>
-<td align="center">AMB</td>
-<td align="center">Amphotericin B</td>
-<td align="center">Candida</td>
-<td align="center"></td>
-<td align="center">1</td>
-<td align="center">1</td>
-<td align="center">FALSE</td>
-</tr>
-<tr class="even">
-<td align="center">EUCAST 2022</td>
-<td align="center">MIC</td>
-<td align="center"></td>
-<td align="center">F_CANDD_ALBC</td>
-<td align="center">Candida albicans</td>
-<td align="center">2</td>
-<td align="center">AMB</td>
-<td align="center">Amphotericin B</td>
-<td align="center">Candida</td>
-<td align="center"></td>
-<td align="center">1</td>
-<td align="center">1</td>
-<td align="center">FALSE</td>
-</tr>
-<tr class="odd">
-<td align="center">EUCAST 2022</td>
-<td align="center">MIC</td>
-<td align="center"></td>
-<td align="center">F_CANDD_DBLN</td>
-<td align="center">Candida dubliniensis</td>
-<td align="center">2</td>
-<td align="center">AMB</td>
-<td align="center">Amphotericin B</td>
-<td align="center">Candida</td>
-<td align="center"></td>
-<td align="center">1</td>
-<td align="center">1</td>
-<td align="center">FALSE</td>
-</tr>
-<tr class="even">
-<td align="center">EUCAST 2022</td>
-<td align="center">MIC</td>
-<td align="center"></td>
-<td align="center">F_CANDD_KRUS</td>
-<td align="center">Candida krusei</td>
-<td align="center">2</td>
-<td align="center">AMB</td>
-<td align="center">Amphotericin B</td>
-<td align="center">Candida</td>
-<td align="center"></td>
-<td align="center">1</td>
-<td align="center">1</td>
-<td align="center">FALSE</td>
-</tr>
-</tbody>
-</table>
-</div>
-</div>
-<div class="section level2">
-<h2 id="intrinsic-bacterial-resistance">Intrinsic bacterial resistance<a class="anchor" aria-label="anchor" href="#intrinsic-bacterial-resistance"></a>
-</h2>
-<p>A data set with 134,956 rows and 2 columns, containing the following
-column names:<br><em>mo</em> and <em>ab</em>.</p>
-<p>This data set is in R available as <code>intrinsic_resistant</code>,
-after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 14 December 2021 21:59:33 UTC. Find more info
-about the structure of this data set <a href="https://msberends.github.io/AMR/reference/intrinsic_resistant.html">here</a>.</p>
-<p><strong>Direct download links:</strong></p>
-<ul>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.rds" class="external-link">R
-file</a> (78 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.xlsx" class="external-link">Excel
-file</a> (1.3 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.txt" class="external-link">plain
-text file</a> (5.1 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.sas" class="external-link">SAS
-file</a> (10.4 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.sav" class="external-link">SPSS
-file</a> (7.4 MB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.dta" class="external-link">Stata
-file</a> (10.2 MB)</li>
-</ul>
-<div class="section level3">
-<h3 id="source-5">Source<a class="anchor" aria-label="anchor" href="#source-5"></a>
-</h3>
-<p>This data set contains all defined intrinsic resistance by EUCAST of
-all bug-drug combinations, and is based on <a href="https://www.eucast.org/expert_rules_and_expected_phenotypes/" class="external-link">‘EUCAST
-Expert Rules’ and ‘EUCAST Intrinsic Resistance and Unusual Phenotypes’
-v3.3</a> (2021).</p>
-</div>
-<div class="section level3">
-<h3 id="example-content-5">Example content<a class="anchor" aria-label="anchor" href="#example-content-5"></a>
-</h3>
-<p>Example rows when filtering on <em>Enterobacter cloacae</em>:</p>
-<table class="table">
-<thead><tr class="header">
-<th align="center">microorganism</th>
-<th align="center">antibiotic</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Acetylmidecamycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Acetylspiramycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Amoxicillin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Amoxicillin/clavulanic acid</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Ampicillin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Ampicillin/sulbactam</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Avoparcin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Azithromycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Benzylpenicillin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Cadazolid</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Cefadroxil</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Cefazolin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Cefoxitin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Cephalexin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Cephalothin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Clarithromycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Clindamycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Cycloserine</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Dalbavancin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Dirithromycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Erythromycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Flurithromycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Fusidic acid</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Gamithromycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Josamycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Kitasamycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Lincomycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Linezolid</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Meleumycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Midecamycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Miocamycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Nafithromycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Norvancomycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Oleandomycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Oritavancin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Pirlimycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Primycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Pristinamycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Quinupristin/dalfopristin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Ramoplanin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Rifampicin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Rokitamycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Roxithromycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Solithromycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Spiramycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Tedizolid</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Teicoplanin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Telavancin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Telithromycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Thiacetazone</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Tildipirosin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Tilmicosin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Troleandomycin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Tulathromycin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Tylosin</td>
-</tr>
-<tr class="even">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Tylvalosin</td>
-</tr>
-<tr class="odd">
-<td align="center">Enterobacter cloacae</td>
-<td align="center">Vancomycin</td>
-</tr>
-</tbody>
-</table>
-</div>
-</div>
-<div class="section level2">
-<h2 id="dosage-guidelines-from-eucast">Dosage guidelines from EUCAST<a class="anchor" aria-label="anchor" href="#dosage-guidelines-from-eucast"></a>
-</h2>
-<p>A data set with 169 rows and 9 columns, containing the following
-column names:<br><em>ab</em>, <em>name</em>, <em>type</em>, <em>dose</em>,
-<em>dose_times</em>, <em>administration</em>, <em>notes</em>,
-<em>original_txt</em> and <em>eucast_version</em>.</p>
-<p>This data set is in R available as <code>dosage</code>, after you
-load the <code>AMR</code> package.</p>
-<p>It was last updated on 25 January 2021 20:58:20 UTC. Find more info
-about the structure of this data set <a href="https://msberends.github.io/AMR/reference/dosage.html">here</a>.</p>
-<p><strong>Direct download links:</strong></p>
-<ul>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/dosage.rds" class="external-link">R
-file</a> (3 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/dosage.xlsx" class="external-link">Excel
-file</a> (14 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/dosage.txt" class="external-link">plain
-text file</a> (15 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/dosage.sas" class="external-link">SAS
-file</a> (52 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/dosage.sav" class="external-link">SPSS
-file</a> (45 kB)<br>
-</li>
-<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/dosage.dta" class="external-link">Stata
-file</a> (44 kB)</li>
-</ul>
-<div class="section level3">
-<h3 id="source-6">Source<a class="anchor" aria-label="anchor" href="#source-6"></a>
-</h3>
-<p>EUCAST breakpoints used in this package are based on the dosages in
-this data set.</p>
-<p>Currently included dosages in the data set are meant for: <a href="https://www.eucast.org/clinical_breakpoints/" class="external-link">‘EUCAST Clinical
-Breakpoint Tables’ v11.0</a> (2021).</p>
-</div>
-<div class="section level3">
-<h3 id="example-content-6">Example content<a class="anchor" aria-label="anchor" href="#example-content-6"></a>
-</h3>
-<table class="table">
-<colgroup>
-<col width="4%">
-<col width="10%">
-<col width="15%">
-<col width="10%">
-<col width="9%">
-<col width="13%">
-<col width="5%">
-<col width="16%">
-<col width="13%">
-</colgroup>
-<thead><tr class="header">
-<th align="center">ab</th>
-<th align="center">name</th>
-<th align="center">type</th>
-<th align="center">dose</th>
-<th align="center">dose_times</th>
-<th align="center">administration</th>
-<th align="center">notes</th>
-<th align="center">original_txt</th>
-<th align="center">eucast_version</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="center">AMK</td>
-<td align="center">Amikacin</td>
-<td align="center">standard_dosage</td>
-<td align="center">25-30 mg/kg</td>
-<td align="center">1</td>
-<td align="center">iv</td>
-<td align="center"></td>
-<td align="center">25-30 mg/kg x 1 iv</td>
-<td align="center">11</td>
-</tr>
-<tr class="even">
-<td align="center">AMX</td>
-<td align="center">Amoxicillin</td>
-<td align="center">high_dosage</td>
-<td align="center">2 g</td>
-<td align="center">6</td>
-<td align="center">iv</td>
-<td align="center"></td>
-<td align="center">2 g x 6 iv</td>
-<td align="center">11</td>
-</tr>
-<tr class="odd">
-<td align="center">AMX</td>
-<td align="center">Amoxicillin</td>
-<td align="center">standard_dosage</td>
-<td align="center">1 g</td>
-<td align="center">3</td>
-<td align="center">iv</td>
-<td align="center"></td>
-<td align="center">1 g x 3-4 iv</td>
-<td align="center">11</td>
-</tr>
-<tr class="even">
-<td align="center">AMX</td>
-<td align="center">Amoxicillin</td>
-<td align="center">high_dosage</td>
-<td align="center">0.75-1 g</td>
-<td align="center">3</td>
-<td align="center">oral</td>
-<td align="center"></td>
-<td align="center">0.75-1 g x 3 oral</td>
-<td align="center">11</td>
-</tr>
-<tr class="odd">
-<td align="center">AMX</td>
-<td align="center">Amoxicillin</td>
-<td align="center">standard_dosage</td>
-<td align="center">0.5 g</td>
-<td align="center">3</td>
-<td align="center">oral</td>
-<td align="center"></td>
-<td align="center">0.5 g x 3 oral</td>
-<td align="center">11</td>
-</tr>
-<tr class="even">
-<td align="center">AMX</td>
-<td align="center">Amoxicillin</td>
-<td align="center">uncomplicated_uti</td>
-<td align="center">0.5 g</td>
-<td align="center">3</td>
-<td align="center">oral</td>
-<td align="center"></td>
-<td align="center">0.5 g x 3 oral</td>
-<td align="center">11</td>
-</tr>
-</tbody>
-</table>
-</div>
-</div>
- </div>
-
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-
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- <h1 data-toc-skip>How to predict antimicrobial resistance</h1>
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- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/resistance_predict.Rmd" class="external-link"><code>vignettes/resistance_predict.Rmd</code></a></small>
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-<div class="section level2">
-<h2 id="needed-r-packages">Needed R packages<a class="anchor" aria-label="anchor" href="#needed-r-packages"></a>
-</h2>
-<p>As with many uses in R, we need some additional packages for AMR data analysis. Our package works closely together with the <a href="https://www.tidyverse.org" class="external-link">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/" class="external-link"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org" class="external-link"><code>ggplot2</code></a> by Dr Hadley Wickham. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.</p>
-<p>Our <code>AMR</code> package depends on these packages and even extends their use and functions.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span>
-<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
-
-<span class="co"># (if not yet installed, install with:)</span>
-<span class="co"># install.packages(c("tidyverse", "AMR"))</span></code></pre></div>
-</div>
-<div class="section level2">
-<h2 id="prediction-analysis">Prediction analysis<a class="anchor" aria-label="anchor" href="#prediction-analysis"></a>
-</h2>
-<p>Our package contains a function <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>, which takes the same input as functions for <a href="./AMR.html">other AMR data analysis</a>. Based on a date column, it calculates cases per year and uses a regression model to predict antimicrobial resistance.</p>
-<p>It is basically as easy as:</p>
-<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true"></a><span class="co"># resistance prediction of piperacillin/tazobactam (TZP):</span></span>
-<span id="cb2-2"><a href="#cb2-2" aria-hidden="true"></a><span class="kw">resistance_predict</span>(<span class="dt">tbl =</span> example_isolates, <span class="dt">col_date =</span> <span class="st">"date"</span>, <span class="dt">col_ab =</span> <span class="st">"TZP"</span>, <span class="dt">model =</span> <span class="st">"binomial"</span>)</span>
-<span id="cb2-3"><a href="#cb2-3" aria-hidden="true"></a></span>
-<span id="cb2-4"><a href="#cb2-4" aria-hidden="true"></a><span class="co"># or:</span></span>
-<span id="cb2-5"><a href="#cb2-5" aria-hidden="true"></a>example_isolates <span class="op">%>%</span><span class="st"> </span></span>
-<span id="cb2-6"><a href="#cb2-6" aria-hidden="true"></a><span class="st"> </span><span class="kw">resistance_predict</span>(<span class="dt">col_ab =</span> <span class="st">"TZP"</span>,</span>
-<span id="cb2-7"><a href="#cb2-7" aria-hidden="true"></a> model <span class="st">"binomial"</span>)</span>
-<span id="cb2-8"><a href="#cb2-8" aria-hidden="true"></a></span>
-<span id="cb2-9"><a href="#cb2-9" aria-hidden="true"></a><span class="co"># to bind it to object 'predict_TZP' for example:</span></span>
-<span id="cb2-10"><a href="#cb2-10" aria-hidden="true"></a>predict_TZP <-<span class="st"> </span>example_isolates <span class="op">%>%</span><span class="st"> </span></span>
-<span id="cb2-11"><a href="#cb2-11" aria-hidden="true"></a><span class="st"> </span><span class="kw">resistance_predict</span>(<span class="dt">col_ab =</span> <span class="st">"TZP"</span>,</span>
-<span id="cb2-12"><a href="#cb2-12" aria-hidden="true"></a> <span class="dt">model =</span> <span class="st">"binomial"</span>)</span></code></pre></div>
-<p>The function will look for a date column itself if <code>col_date</code> is not set.</p>
-<p>When running any of these commands, a summary of the regression model will be printed unless using <code>resistance_predict(..., info = FALSE)</code>.</p>
-<pre><code><span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre>
-<p>This text is only a printed summary - the actual result (output) of the function is a <code>data.frame</code> containing for each year: the number of observations, the actual observed resistance, the estimated resistance and the standard error below and above the estimation:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">predict_TZP</span>
-<span class="co"># year value se_min se_max observations observed estimated</span>
-<span class="co"># 1 2002 0.20000000 NA NA 15 0.20000000 0.05616378</span>
-<span class="co"># 2 2003 0.06250000 NA NA 32 0.06250000 0.06163839</span>
-<span class="co"># 3 2004 0.08536585 NA NA 82 0.08536585 0.06760841</span>
-<span class="co"># 4 2005 0.05000000 NA NA 60 0.05000000 0.07411100</span>
-<span class="co"># 5 2006 0.05084746 NA NA 59 0.05084746 0.08118454</span>
-<span class="co"># 6 2007 0.12121212 NA NA 66 0.12121212 0.08886843</span>
-<span class="co"># 7 2008 0.04166667 NA NA 72 0.04166667 0.09720264</span>
-<span class="co"># 8 2009 0.01639344 NA NA 61 0.01639344 0.10622731</span>
-<span class="co"># 9 2010 0.05660377 NA NA 53 0.05660377 0.11598223</span>
-<span class="co"># 10 2011 0.18279570 NA NA 93 0.18279570 0.12650615</span>
-<span class="co"># 11 2012 0.30769231 NA NA 65 0.30769231 0.13783610</span>
-<span class="co"># 12 2013 0.06896552 NA NA 58 0.06896552 0.15000651</span>
-<span class="co"># 13 2014 0.10000000 NA NA 60 0.10000000 0.16304829</span>
-<span class="co"># 14 2015 0.23636364 NA NA 55 0.23636364 0.17698785</span>
-<span class="co"># 15 2016 0.22619048 NA NA 84 0.22619048 0.19184597</span>
-<span class="co"># 16 2017 0.16279070 NA NA 86 0.16279070 0.20763675</span>
-<span class="co"># 17 2018 0.22436641 0.1938710 0.2548618 NA NA 0.22436641</span>
-<span class="co"># 18 2019 0.24203228 0.2062911 0.2777735 NA NA 0.24203228</span>
-<span class="co"># 19 2020 0.26062172 0.2191758 0.3020676 NA NA 0.26062172</span>
-<span class="co"># 20 2021 0.28011130 0.2325557 0.3276669 NA NA 0.28011130</span>
-<span class="co"># 21 2022 0.30046606 0.2464567 0.3544755 NA NA 0.30046606</span>
-<span class="co"># 22 2023 0.32163907 0.2609011 0.3823771 NA NA 0.32163907</span>
-<span class="co"># 23 2024 0.34357130 0.2759081 0.4112345 NA NA 0.34357130</span>
-<span class="co"># 24 2025 0.36619175 0.2914934 0.4408901 NA NA 0.36619175</span>
-<span class="co"># 25 2026 0.38941799 0.3076686 0.4711674 NA NA 0.38941799</span>
-<span class="co"># 26 2027 0.41315710 0.3244399 0.5018743 NA NA 0.41315710</span>
-<span class="co"># 27 2028 0.43730688 0.3418075 0.5328063 NA NA 0.43730688</span>
-<span class="co"># 28 2029 0.46175755 0.3597639 0.5637512 NA NA 0.46175755</span>
-<span class="co"># 29 2030 0.48639359 0.3782932 0.5944939 NA NA 0.48639359</span>
-<span class="co"># 30 2031 0.51109592 0.3973697 0.6248221 NA NA 0.51109592</span>
-<span class="co"># 31 2032 0.53574417 0.4169574 0.6545309 NA NA 0.53574417</span></code></pre></div>
-<p>The function <code>plot</code> is available in base R, and can be extended by other packages to depend the output based on the type of input. We extended its function to cope with resistance predictions:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-4-1.png" width="720"></p>
-<p>This is the fastest way to plot the result. It automatically adds the right axes, error bars, titles, number of available observations and type of model.</p>
-<p>We also support the <code>ggplot2</code> package with our custom function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> to create more appealing plots:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-1.png" width="720"></p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R">
-<span class="co"># choose for error bars instead of a ribbon</span>
-<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span>, ribbon <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-2.png" width="720"></p>
-<div class="section level3">
-<h3 id="choosing-the-right-model">Choosing the right model<a class="anchor" aria-label="anchor" href="#choosing-the-right-model"></a>
-</h3>
-<p>Resistance is not easily predicted; if we look at vancomycin resistance in Gram-positive bacteria, the spread (i.e. standard error) is enormous:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span>
-<span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-6-1.png" width="720"></p>
-<p>Vancomycin resistance could be 100% in ten years, but might also stay around 0%.</p>
-<p>You can define the model with the <code>model</code> parameter. The model chosen above is a generalised linear regression model using a binomial distribution, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance.</p>
-<p>Valid values are:</p>
-<table class="table">
-<colgroup>
-<col width="32%">
-<col width="25%">
-<col width="42%">
-</colgroup>
-<thead><tr class="header">
-<th>Input values</th>
-<th>Function used by R</th>
-<th>Type of model</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td>
-<code>"binomial"</code> or <code>"binom"</code> or <code>"logit"</code>
-</td>
-<td><code>glm(..., family = binomial)</code></td>
-<td>Generalised linear model with binomial distribution</td>
-</tr>
-<tr class="even">
-<td>
-<code>"loglin"</code> or <code>"poisson"</code>
-</td>
-<td><code>glm(..., family = poisson)</code></td>
-<td>Generalised linear model with poisson distribution</td>
-</tr>
-<tr class="odd">
-<td>
-<code>"lin"</code> or <code>"linear"</code>
-</td>
-<td><code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm()</a></code></td>
-<td>Linear model</td>
-</tr>
-</tbody>
-</table>
-<p>For the vancomycin resistance in Gram-positive bacteria, a linear model might be more appropriate since no binomial distribution is to be expected based on the observed years:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"linear"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span>
-<span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
-<p>This seems more likely, doesn’t it?</p>
-<p>The model itself is also available from the object, as an <code>attribute</code>:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span class="va">model</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html" class="external-link">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span>
-
-<span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">family</span>
-<span class="co"># </span>
-<span class="co"># Family: binomial </span>
-<span class="co"># Link function: logit</span>
-
-<span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">coefficients</span>
-<span class="co"># Estimate Std. Error z value Pr(>|z|)</span>
-<span class="co"># (Intercept) -200.67944891 46.17315349 -4.346237 1.384932e-05</span>
-<span class="co"># year 0.09883005 0.02295317 4.305725 1.664395e-05</span></code></pre></div>
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diff --git a/docs/articles/resistance_predict_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/resistance_predict_files/accessible-code-block-0.0.1/empty-anchor.js
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- <h1 data-toc-skip>Welcome to the <code>AMR</code> package</h1>
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- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/welcome_to_AMR.Rmd" class="external-link"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
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-<p>Note: to keep the package size as small as possible, we only included this vignette on CRAN. You can read more vignettes on our website about how to conduct AMR data analysis, determine MDRO’s, find explanation of EUCAST rules, and much more: <a href="https://msberends.github.io/AMR/articles/" class="uri">https://msberends.github.io/AMR/articles/</a>.</p>
-<hr>
-<p><code>AMR</code> is a free, open-source and independent R package (see <a href="https://msberends.github.io/AMR/#copyright">Copyright</a>) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
-<p>After installing this package, R knows ~71,000 distinct microbial species and all ~570 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
-<p>The <code>AMR</code> package is available in Danish, Dutch, English, French, German, Italian, Portuguese, Russian, Spanish and Swedish. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.</p>
-<p>This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. Since its first public release in early 2018, this package has been downloaded from more than 175 countries.</p>
-<p>This package can be used for:</p>
-<ul>
-<li>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life and List of Prokaryotic names with Standing in Nomenclature</li>
-<li>Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines</li>
-<li>Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records</li>
-<li>Determining first isolates to be used for AMR data analysis</li>
-<li>Calculating antimicrobial resistance</li>
-<li>Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)</li>
-<li>Calculating (empirical) susceptibility of both mono therapy and combination therapies</li>
-<li>Predicting future antimicrobial resistance using regression models</li>
-<li>Getting properties for any microorganism (like Gram stain, species, genus or family)</li>
-<li>Getting properties for any antibiotic (like name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)</li>
-<li>Plotting antimicrobial resistance</li>
-<li>Applying EUCAST expert rules</li>
-<li>Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code</li>
-<li>Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code</li>
-<li>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI</li>
-<li>Principal component analysis for AMR</li>
-</ul>
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
-<p>This R package was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>. This R package formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">DOI 10.33612/diss.177417131</a> and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">DOI 10.33612/diss.192486375</a>) but is actively and durably maintained (see <a href="https://msberends.github.io/AMR/news/index.html">changelog)</a>) by two public healthcare organisations in the Netherlands.</p>
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diff --git a/docs/articles/welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js
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-// Hide empty <a> tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
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diff --git a/docs/authors.html b/docs/authors.html
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--- a/docs/authors.html
+++ /dev/null
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-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Authors and Citation • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link href="https://cdnjs.cloudflare.com/ajax/libs/bootswatch/3.4.0/flatly/bootstrap.min.css" rel="stylesheet" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="bootstrap-toc.css"><script src="bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="pkgdown.css" rel="stylesheet"><script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet"><script src="extra.js"></script><meta property="og:title" content="Authors and Citation"><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@univgroningen"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--></head><body data-spy="scroll" data-target="#toc">
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- <div class="container template-citation-authors">
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- <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">1.8.1.9014</span>
- </span>
- </div>
-
- <div id="navbar" class="navbar-collapse collapse">
- <ul class="nav navbar-nav"><li>
- <a href="index.html">
- <span class="fa fa-home"></span>
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- Home
- </a>
-</li>
-<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">
- <span class="fa fa-question-circle"></span>
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- </a>
- <ul class="dropdown-menu" role="menu"><li>
- <a href="articles/AMR.html">
- <span class="fa fa-directions"></span>
-
- Conduct AMR analysis
- </a>
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- <li>
- <a href="articles/resistance_predict.html">
- <span class="fa fa-dice"></span>
-
- Predict antimicrobial resistance
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- Conduct principal component analysis for AMR
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- Determine multi-drug resistance (MDR)
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- <span class="fa fa-file-upload"></span>
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- Import data from SPSS/SAS/Stata
- </a>
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- <a href="articles/EUCAST.html">
- <span class="fa fa-exchange-alt"></span>
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- Apply EUCAST rules
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- <span class="fa fa-bug"></span>
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- Get properties of a microorganism
- </a>
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- <span class="fa fa-capsules"></span>
-
- Get properties of an antibiotic
- </a>
- </li>
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- <span class="fa fa-shipping-fast"></span>
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- </div><!--/.container -->
-</div><!--/.navbar -->
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- </header><div class="row">
- <div class="contents col-md-9">
- <div class="section level2 authors-section">
- <div class="page-header">
- <h1>Authors</h1>
- </div>
-
-
- <ul class="list-unstyled"><li>
- <p><strong>Matthijs S. Berends</strong>. Author, maintainer. <a href="https://orcid.org/0000-0001-7620-1800" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Christian F. Luz</strong>. Author, contributor. <a href="https://orcid.org/0000-0001-5809-5995" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Dennis Souverein</strong>. Author, contributor. <a href="https://orcid.org/0000-0003-0455-0336" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Erwin E. A. Hassing</strong>. Author, contributor.
- </p>
- </li>
- <li>
- <p><strong>Casper J. Albers</strong>. Thesis advisor. <a href="https://orcid.org/0000-0002-9213-6743" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Judith M. Fonville</strong>. Contributor.
- </p>
- </li>
- <li>
- <p><strong>Alex W. Friedrich</strong>. Thesis advisor. <a href="https://orcid.org/0000-0003-4881-038X" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Corinna Glasner</strong>. Thesis advisor. <a href="https://orcid.org/0000-0003-1241-1328" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Eric H. L. C. M. Hazenberg</strong>. Contributor.
- </p>
- </li>
- <li>
- <p><strong>Gwen Knight</strong>. Contributor. <a href="https://orcid.org/0000-0002-7263-9896" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Annick Lenglet</strong>. Contributor. <a href="https://orcid.org/0000-0003-2013-8405" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Bart C. Meijer</strong>. Contributor.
- </p>
- </li>
- <li>
- <p><strong>Sofia Ny</strong>. Contributor. <a href="https://orcid.org/0000-0002-2017-1363" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Rogier P. Schade</strong>. Contributor.
- </p>
- </li>
- <li>
- <p><strong>Bhanu N. M. Sinha</strong>. Thesis advisor. <a href="https://orcid.org/0000-0003-1634-0010" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- <li>
- <p><strong>Anthony Underwood</strong>. Contributor. <a href="https://orcid.org/0000-0002-8547-4277" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
- </p>
- </li>
- </ul></div>
- <div class="section level2 citation-section">
- <div>
- <h1 id="citation">Citation</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/inst/CITATION" class="external-link"><code>inst/CITATION</code></a></small>
- </div>
- </div>
-
-
- <p>Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2021). AMR - An R Package for Working with
-Antimicrobial Resistance Data. Journal of Statistical Software (accepted for publication), https://www.biorxiv.org/content/10.1101/810622, doi: 10.1101/810622.</p>
- <pre>@Article{,
- title = {AMR - An R Package for Working with Antimicrobial Resistance Data},
- author = {M S Berends and C F Luz and A W Friedrich and B N M Sinha and C J Albers and C Glasner},
- doi = {10.1101/810622},
- journal = {Journal of Statistical Software},
- pages = {Accepted for publication},
- year = {2021},
- url = {https://www.biorxiv.org/content/10.1101/810622},
-}</pre>
- <p>Berends, MS (2021). A New Instrument for Microbial Epidemiology: Empowering Antimicrobial Resistance Data Analysis (PhD thesis). University of Groningen, doi: 10.33612/diss.177417131.</p>
- <pre>@PhdThesis{,
- title = {A New Instrument for Microbial Epidemiology: Empowering Antimicrobial Resistance Data Analysis},
- author = {M S Berends},
- publisher = {University of Groningen},
- school = {University of Groningen},
- doi = {10.33612/diss.177417131},
- pages = {287},
- year = {2021},
-}</pre>
- <p>Luz, CF (2021). Data Science for Infection Management & Antimicrobial Stewardship (PhD thesis). University of Groningen, doi: 10.33612/diss.192486375.</p>
- <pre>@PhdThesis{,
- title = {Data Science for Infection Management & Antimicrobial Stewardship},
- author = {C F Luz},
- publisher = {University of Groningen},
- school = {University of Groningen},
- doi = {10.33612/diss.192486375},
- pages = {326},
- year = {2021},
-}</pre>
-
- </div>
-
-</div>
-
-
-
- <footer><div class="copyright">
- <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p>
-</div>
-
-<div class="pkgdown">
- <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p>
-</div>
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-
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index b35504cd3..000000000
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diff --git a/docs/extra.css b/docs/extra.css
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-/*
-# ==================================================================== #
-# TITLE #
-# Antimicrobial Resistance (AMR) Data Analysis for R #
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-# LICENCE #
-# (c) 2018-2022 Berends MS, Luz CF et al. #
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-# Diagnostics & Advice, and University Medical Center Groningen. #
-# #
-# This R package is free software; you can freely use and distribute #
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-# the Free Software Foundation. #
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-# Visit our website for the full manual and a complete tutorial about #
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-# ==================================================================== #
-*/
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-# We created this package for both routine data analysis and academic #
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-<div class="page-header"><h1 id="amr-for-r-">
-<code>AMR</code> (for R) <img src="./logo.svg" align="right"><a class="anchor" aria-label="anchor" href="#amr-for-r-"></a>
-</h1></div>
-<blockquote>
-<p>Update May 2022: EUCAST 2022 and CLSI 2022 guidelines have been added for <code><a href="reference/as.rsi.html">as.rsi()</a></code>!</p>
-<p>Updates to the AMR interpretation rules (such as by EUCAST and CLSI), the microbial taxonomy, and the antibiotic dosages will all be updated every 6 to 12 months.</p>
-</blockquote>
-<div class="section level3">
-<h3 id="what-is-amr-for-r">What is <code>AMR</code> (for R)?<a class="anchor" aria-label="anchor" href="#what-is-amr-for-r"></a>
-</h3>
-<p><code>AMR</code> is a free, open-source and independent <a href="https://www.r-project.org" class="external-link">R package</a> (see <a href="#copyright">Copyright</a>) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
-<p>After installing this package, R knows <a href="./reference/microorganisms.html"><strong>~71,000 distinct microbial species</strong></a> and all <a href="./reference/antibiotics.html"><strong>~570 antibiotic, antimycotic and antiviral drugs</strong></a> by name and code (including ATC, WHONET/EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
-<p>The <code>AMR</code> package is available in <img src="lang_da.svg" style="height: 11px !important; vertical-align: initial !important;"> Danish, <img src="lang_nl.svg" style="height: 11px !important; vertical-align: initial !important;"> Dutch, <img src="lang_en.svg" style="height: 11px !important; vertical-align: initial !important;"> English, <img src="lang_fr.svg" style="height: 11px !important; vertical-align: initial !important;"> French, <img src="lang_de.svg" style="height: 11px !important; vertical-align: initial !important;"> German, <img src="lang_it.svg" style="height: 11px !important; vertical-align: initial !important;"> Italian, <img src="lang_pt.svg" style="height: 11px !important; vertical-align: initial !important;"> Portuguese, <img src="lang_ru.svg" style="height: 11px !important; vertical-align: initial !important;"> Russian, <img src="lang_es.svg" style="height: 11px !important; vertical-align: initial !important;"> Spanish and <img src="lang_sv.svg" style="height: 11px !important; vertical-align: initial !important;"> Swedish. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.</p>
-<p>This package is <a href="https://en.wikipedia.org/wiki/Dependency_hell" class="external-link">fully independent of any other R package</a> and works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>. This R package formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">DOI 10.33612/diss.177417131</a> and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">DOI 10.33612/diss.192486375</a>) but is <a href="./news">actively and durably maintained</a> by two public healthcare organisations in the Netherlands.</p>
-<div class="main-content" style="display: inline-block;">
-<p>
-<a href="./countries_large.png" target="_blank"><img src="./countries.png" class="countries_map"></a> <strong>Used in 175 countries</strong><br> Since its first public release in early 2018, this R package has been used in almost all countries in the world. Click the map to enlarge and to see the country names.
-</p>
-</div>
-<div class="section level5">
-<h5 id="with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side">With <code>AMR</code> (for R), there’s always a knowledgeable microbiologist by your side!<a class="anchor" aria-label="anchor" href="#with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side"></a>
-</h5>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># AMR works great with dplyr, but it's not required or neccesary</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>bacteria <span class="op">=</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span>,</span>
-<span> <span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">bacteria</span>,</span>
-<span> <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>,</span>
-<span> <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-<p>With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (<code><a href="reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><a href="reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>) and a column selection on two antibiotic groups (<code><a href="reference/antibiotic_class_selectors.html">aminoglycosides()</a></code> and <code><a href="reference/antibiotic_class_selectors.html">carbapenems()</a></code>), the reference data about <a href="./reference/microorganisms.html">all microorganisms</a> and <a href="./reference/antibiotics.html">all antibiotics</a> in the <code>AMR</code> package make sure you get what you meant:</p>
-<table class="table">
-<thead><tr class="header">
-<th align="left">bacteria</th>
-<th align="center">GEN</th>
-<th align="center">TOB</th>
-<th align="center">AMK</th>
-<th align="center">KAN</th>
-<th align="center">IPM</th>
-<th align="center">MEM</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left"><em>Pseudomonas aeruginosa</em></td>
-<td align="center">I</td>
-<td align="center">S</td>
-<td align="center"></td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center"></td>
-</tr>
-<tr class="even">
-<td align="left"><em>Pseudomonas aeruginosa</em></td>
-<td align="center">I</td>
-<td align="center">S</td>
-<td align="center"></td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center"></td>
-</tr>
-<tr class="odd">
-<td align="left"><em>Pseudomonas aeruginosa</em></td>
-<td align="center">I</td>
-<td align="center">S</td>
-<td align="center"></td>
-<td align="center">R</td>
-<td align="center">S</td>
-<td align="center"></td>
-</tr>
-<tr class="even">
-<td align="left"><em>Pseudomonas aeruginosa</em></td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center"></td>
-<td align="center">S</td>
-</tr>
-<tr class="odd">
-<td align="left"><em>Pseudomonas aeruginosa</em></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>
-</tr>
-<tr class="even">
-<td align="left"><em>Pseudomonas aeruginosa</em></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>
-</tr>
-<tr class="odd">
-<td align="left"><em>Stenotrophomonas maltophilia</em></td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">R</td>
-<td align="center">R</td>
-</tr>
-<tr class="even">
-<td align="left"><em>Pseudomonas aeruginosa</em></td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center"></td>
-<td align="center">S</td>
-</tr>
-<tr class="odd">
-<td align="left"><em>Pseudomonas aeruginosa</em></td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center"></td>
-<td align="center">S</td>
-</tr>
-<tr class="even">
-<td align="left"><em>Pseudomonas aeruginosa</em></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>
-</tr>
-</tbody>
-</table>
-<p>A base R equivalent would be, giving the exact same results:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">example_isolates</span><span class="op">$</span><span class="va">bacteria</span> <span class="op"><-</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">mo</span><span class="op">)</span></span>
-<span><span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&</span></span>
-<span> <span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span>,</span>
-<span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"bacteria"</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">]</span></span></code></pre></div>
-</div>
-<div class="section level4">
-<h4 id="partners">Partners<a class="anchor" aria-label="anchor" href="#partners"></a>
-</h4>
-<p>The development of this package is part of, related to, or made possible by:</p>
-<div align="center">
-<p><a href="https://www.rug.nl" title="University of Groningen" class="external-link"><img src="./logo_rug.png" class="partner_logo"></a> <a href="https://www.umcg.nl" title="University Medical Center Groningen" class="external-link"><img src="./logo_umcg.png" class="partner_logo"></a> <a href="https://www.certe.nl" title="Certe Medical Diagnostics and Advice Foundation" class="external-link"><img src="./logo_certe.png" class="partner_logo"></a> <a href="https://www.deutschland-nederland.eu" title="EurHealth-1-Health" class="external-link"><img src="./logo_eh1h.png" class="partner_logo"></a> <a href="https://www.deutschland-nederland.eu" title="INTERREG" class="external-link"><img src="./logo_interreg.png" class="partner_logo"></a></p>
-</div>
-</div>
-</div>
-<div class="section level3">
-<h3 id="what-can-you-do-with-this-package">What can you do with this package?<a class="anchor" aria-label="anchor" href="#what-can-you-do-with-this-package"></a>
-</h3>
-<p>This package can be used for:</p>
-<ul>
-<li>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the <a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> and <a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with Standing in Nomenclature</a> (<a href="./reference/mo_property.html">manual</a>)</li>
-<li>Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines (<a href="./reference/as.rsi.html">manual</a>)</li>
-<li>Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records (<a href="./reference/ab_from_text.html">manual</a>)</li>
-<li>Determining first isolates to be used for AMR data analysis (<a href="./reference/first_isolate.html">manual</a>)</li>
-<li>Calculating antimicrobial resistance (<a href="./articles/AMR.html">tutorial</a>)</li>
-<li>Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO) (<a href="./articles/MDR.html">tutorial</a>)</li>
-<li>Calculating (empirical) susceptibility of both mono therapy and combination therapies (<a href="./articles/AMR.html">tutorial</a>)</li>
-<li>Predicting future antimicrobial resistance using regression models (<a href="./articles/resistance_predict.html">tutorial</a>)</li>
-<li>Getting properties for any microorganism (like Gram stain, species, genus or family) (<a href="./reference/mo_property.html">manual</a>)</li>
-<li>Getting properties for any antibiotic (like name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name) (<a href="./reference/ab_property.html">manual</a>)</li>
-<li>Plotting antimicrobial resistance (<a href="./articles/AMR.html">tutorial</a>)</li>
-<li>Applying EUCAST expert rules (<a href="./reference/eucast_rules.html">manual</a>)</li>
-<li>Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code (<a href="./reference/mo_property.html">manual</a>)</li>
-<li>Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code (<a href="./reference/ab_property.html">manual</a>)</li>
-<li>Machine reading the EUCAST and CLSI guidelines from 2011-2021 to translate MIC values and disk diffusion diameters to R/SI (<a href="./articles/datasets.html">link</a>)</li>
-<li>Principal component analysis for AMR (<a href="./articles/PCA.html">tutorial</a>)</li>
-</ul>
-</div>
-<div class="section level3">
-<h3 id="get-this-package">Get this package<a class="anchor" aria-label="anchor" href="#get-this-package"></a>
-</h3>
-<div class="section level4">
-<h4 id="latest-released-version">Latest released version<a class="anchor" aria-label="anchor" href="#latest-released-version"></a>
-</h4>
-<p><a href="https://cran.r-project.org/package=AMR" class="external-link"><img src="https://www.r-pkg.org/badges/version-ago/AMR" alt="CRAN"></a> <a href="https://cran.r-project.org/package=AMR" class="external-link"><img src="https://cranlogs.r-pkg.org/badges/grand-total/AMR" alt="CRANlogs"></a></p>
-<p>This package is available <a href="https://cran.r-project.org/package=AMR" class="external-link">here on the official R network (CRAN)</a>. Install this package in R from CRAN by using the command:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"AMR"</span><span class="op">)</span></span></code></pre></div>
-<p>It will be downloaded and installed automatically. For RStudio, click on the menu <em>Tools</em> > <em>Install Packages…</em> and then type in “AMR” and press <kbd>Install</kbd>.</p>
-<p><strong>Note:</strong> Not all functions on this website may be available in this latest release. To use all functions and data sets mentioned on this website, install the latest development version.</p>
-</div>
-<div class="section level4">
-<h4 id="latest-development-version">Latest development version<a class="anchor" aria-label="anchor" href="#latest-development-version"></a>
-</h4>
-<p><a href="https://codecov.io/gh/msberends/AMR?branch=main" class="external-link"><img src="https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=main" alt="R-code-check"></a> <a href="https://www.codefactor.io/repository/github/msberends/amr" class="external-link"><img src="https://www.codefactor.io/repository/github/msberends/amr/badge" alt="CodeFactor"></a> <a href="https://codecov.io/gh/msberends/AMR?branch=main" class="external-link"><img src="https://codecov.io/gh/msberends/AMR/branch/main/graph/badge.svg" alt="Codecov"></a></p>
-<p>The latest and unpublished development version can be installed from GitHub in two ways:</p>
-<ol style="list-style-type: decimal">
-<li>
-<p>Manually, using:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"remotes"</span><span class="op">)</span> <span class="co"># if you haven't already</span></span>
-<span><span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html" class="external-link">install_github</a></span><span class="op">(</span><span class="st">"msberends/AMR"</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li>
-<p>Automatically, using the <a href="https://ropensci.org/r-universe/" class="external-link">rOpenSci R-universe platform</a>, by adding <a href="https://msberends.r-universe.dev" class="external-link">our R-universe address</a> to your list of repositories (‘repos’):</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">options</a></span><span class="op">(</span>repos <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"repos"</span><span class="op">)</span>,</span>
-<span> msberends <span class="op">=</span> <span class="st">"https://msberends.r-universe.dev"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-<p>After this, you can install and update this <code>AMR</code> package like any official release (e.g., using <code>install.packages("AMR")</code> or in RStudio via <em>Tools</em> > <em>Check for Package Updates…</em>).</p>
-</li>
-</ol>
-<p>You can also download the latest build from our repository: <a href="https://github.com/msberends/AMR/raw/main/data-raw/AMR_latest.tar.gz" class="external-link uri">https://github.com/msberends/AMR/raw/main/data-raw/AMR_latest.tar.gz</a></p>
-</div>
-</div>
-<div class="section level3">
-<h3 id="get-started">Get started<a class="anchor" aria-label="anchor" href="#get-started"></a>
-</h3>
-<p>To find out how to conduct AMR data analysis, please <a href="./articles/AMR.html">continue reading here to get started</a> or click a link in the <a href="https://msberends.github.io/AMR/articles/">‘How to’ menu</a>.</p>
-</div>
-<div class="section level3">
-<h3 id="short-introduction">Short introduction<a class="anchor" aria-label="anchor" href="#short-introduction"></a>
-</h3>
-<div class="section level4">
-<h4 id="microbial-taxonomic-reference-data">Microbial (taxonomic) reference data<a class="anchor" aria-label="anchor" href="#microbial-taxonomic-reference-data"></a>
-</h4>
-<p>This package contains the complete taxonomic tree of almost all ~71,000 microorganisms from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org" class="external-link">www.catalogueoflife.org</a>), supplemented by data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de" class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/Sp2000/colplus" class="external-link">CoL+ project</a> is finished, which we await. With <code><a href="reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code> can be checked which version of the CoL is included in this package.</p>
-<p>Read more about which data from the Catalogue of Life <a href="./reference/catalogue_of_life.html">in our manual</a>.</p>
-</div>
-<div class="section level4">
-<h4 id="antimicrobial-reference-data">Antimicrobial reference data<a class="anchor" aria-label="anchor" href="#antimicrobial-reference-data"></a>
-</h4>
-<p>This package contains <strong>all ~570 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD, oral and IV) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://www.whocc.no" class="external-link uri">https://www.whocc.no</a>) and the <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">Pharmaceuticals Community Register of the European Commission</a>.</p>
-<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See <a href="https://www.whocc.no/copyright_disclaimer/" class="external-link uri">https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
-<p>Read more about the data from WHOCC <a href="./reference/WHOCC.html">in our manual</a>.</p>
-</div>
-<div class="section level4">
-<h4 id="whonet--ears-net">WHONET / EARS-Net<a class="anchor" aria-label="anchor" href="#whonet--ears-net"></a>
-</h4>
-<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 as a WHONET export file. Furthermore, this package also contains a <a href="./reference/antibiotics.html">data set antibiotics</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>
-</div>
-<div class="section level4">
-<h4 id="overview-of-functions">Overview of functions<a class="anchor" aria-label="anchor" href="#overview-of-functions"></a>
-</h4>
-<p>The <code>AMR</code> package basically does four important things:</p>
-<ol style="list-style-type: decimal">
-<li>
-<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 intelligent rules to guess results that you would expect:</p>
-<ul>
-<li>Use <code><a href="reference/as.mo.html">as.mo()</a></code> to get a microbial ID. The IDs are human readable for the trained eye - the ID of <em>Klebsiella pneumoniae</em> is “B_KLBSL_PNMN” (B stands for Bacteria) and the ID of <em>S. aureus</em> is “B_STPHY_AURS”. 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 intelligent rules combined with the included Catalogue of Life data set. It only takes milliseconds to find results, 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.ab.html">as.ab()</a></code> to get an antibiotic ID. Like microbial IDs, these IDs are also human readable based on those used by EARS-Net. For example, the ID of amoxicillin is <code>AMX</code> and the ID of gentamicin is <code>GEN</code>. The <code><a href="reference/as.ab.html">as.ab()</a></code> function also uses intelligent rules to find results like accepting misspelling, trade names and abbrevations used in many laboratory systems. For instance, the values “Furabid”, “Furadantin”, “nitro” all return the ID of Nitrofurantoine. To accomplish this, the package contains a database with most LIS codes, official names, trade names, ATC codes, defined daily doses (DDD) and drug categories of antibiotics.</li>
-<li>Use <code><a href="reference/as.rsi.html">as.rsi()</a></code> to get antibiotic interpretations based on raw MIC values (in mg/L) or disk diffusion values (in mm), or transform existing values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like “<=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 “<=0.002; S” (combined MIC/RSI) will result in “<=0.002”.</li>
-</ul>
-</li>
-<li>
-<p>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</p>
-<ul>
-<li>Use <code><a href="reference/eucast_rules.html">eucast_rules()</a></code> to apply <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">EUCAST expert rules to isolates</a> (not the translation from MIC to R/SI values, use <code><a href="reference/as.rsi.html">as.rsi()</a></code> for that).</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/" class="external-link">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
-<ul>
-<li>You can also identify first <em>weighted</em> isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them.</li>
-</ul>
-</li>
-<li>Use <code><a href="reference/mdro.html">mdro()</a></code> to determine which micro-organisms are multi-drug resistant organisms (MDRO). It supports a variety of international guidelines, such as the MDR-paper by Magiorakos <em>et al.</em> (2012, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=21793988" class="external-link">PMID 21793988</a>), the exceptional phenotype definitions of EUCAST and the WHO guideline on multi-drug resistant TB. It also supports the national guidelines of the Netherlands and Germany.</li>
-<li>The <a href="./reference/microorganisms.html">data set microorganisms</a> contains the complete taxonomic tree of ~70,000 microorganisms. Furthermore, some colloquial names and all Gram stains 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>. Use <code><a href="reference/mo_property.html">mo_snomed()</a></code> to look up any SNOMED CT code associated with a microorganism. As all these function use <code><a href="reference/as.mo.html">as.mo()</a></code> internally, they also use the same intelligent rules for determination. For example, <code>mo_genus("MRSA")</code> and <code>mo_genus("S. aureus")</code> will both return <code>"Staphylococcus"</code>. They also come with support for German, Danish, 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 antibiotics</a> contains ~450 antimicrobial drugs with their EARS-Net code, ATC code, PubChem compound ID, LOINC code, official name, common LIS codes and DDDs of both oral and parenteral administration. It also contains all (thousands of) trade names found in PubChem. Use functions like <code><a href="reference/ab_property.html">ab_name()</a></code>, <code><a href="reference/ab_property.html">ab_group()</a></code>, <code><a href="reference/ab_property.html">ab_atc()</a></code>, <code><a href="reference/ab_property.html">ab_loinc()</a></code> and <code><a href="reference/ab_property.html">ab_tradenames()</a></code> to look up values. The <code>ab_*</code> functions use <code><a href="reference/as.ab.html">as.ab()</a></code> internally so they support the same intelligent rules to guess the most probable result. For example, <code>ab_name("Fluclox")</code>, <code>ab_name("Floxapen")</code> and <code>ab_name("J01CF05")</code> will all return <code>"Flucloxacillin"</code>. These functions can again be used to add new variables to your data.</li>
-</ul>
-</li>
-<li>
-<p>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</p>
-<ul>
-<li>Calculate the microbial susceptibility or resistance (and even co-resistance) with the <code><a href="reference/proportion.html">susceptibility()</a></code> and <code><a href="reference/proportion.html">resistance()</a></code> functions, or be even more specific with the <code><a href="reference/proportion.html">proportion_R()</a></code>, <code><a href="reference/proportion.html">proportion_IR()</a></code>, <code><a href="reference/proportion.html">proportion_I()</a></code>, <code><a href="reference/proportion.html">proportion_SI()</a></code> and <code><a href="reference/proportion.html">proportion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><a href="reference/count.html">count_resistant()</a></code>, <code><a href="reference/count.html">count_susceptible()</a></code> and <code><a href="reference/count.html">count_all()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g. in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></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>Predict antimicrobial resistance for the nextcoming years using logistic regression models with the <code><a href="reference/resistance_predict.html">resistance_predict()</a></code> function</li>
-</ul>
-</li>
-<li>
-<p>It <strong>teaches the user</strong> how to use all the above actions.</p>
-<ul>
-<li>Aside from this website with many tutorials, the package itself contains extensive help pages with many examples for all functions.</li>
-<li>The package also contains example data sets:
-<ul>
-<li>The <a href="./reference/example_isolates.html"><code>example_isolates</code> data set</a>. This data set contains 2,000 microbial isolates with their full antibiograms. It reflects reality and can be used to practice AMR data analysis.</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>
-</li>
-</ul>
-</li>
-</ol>
-</div>
-</div>
-<div class="section level3">
-<h3 id="copyright">Copyright<a class="anchor" aria-label="anchor" href="#copyright"></a>
-</h3>
-<p>This R package is free, open-source software and licensed under the <a href="./LICENSE-text.html">GNU General Public License v2.0 (GPL-2)</a>. In a nutshell, this means that this package:</p>
-<ul>
-<li><p>May be used for commercial purposes</p></li>
-<li><p>May be used for private purposes</p></li>
-<li><p>May <strong>not</strong> be used for patent purposes</p></li>
-<li>
-<p>May be modified, although:</p>
-<ul>
-<li>Modifications <strong>must</strong> be released under the same license when distributing the package</li>
-<li>Changes made to the code <strong>must</strong> be documented</li>
-</ul>
-</li>
-<li>
-<p>May be distributed, although:</p>
-<ul>
-<li>Source code <strong>must</strong> be made available when the package is distributed</li>
-<li>A copy of the license and copyright notice <strong>must</strong> be included with the package.</li>
-</ul>
-</li>
-<li><p>Comes with a LIMITATION of liability</p></li>
-<li><p>Comes with NO warranty</p></li>
-</ul>
-</div>
-</div>
- </div>
-
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
- <div class="links">
-<h2 data-toc-skip>Links</h2>
-<ul class="list-unstyled">
-<li><a href="https://cloud.r-project.org/package=AMR" class="external-link">View on CRAN</a></li>
-<li><a href="https://github.com/msberends/AMR/" class="external-link">Browse source code</a></li>
-<li><a href="https://github.com/msberends/AMR/issues" class="external-link">Report a bug</a></li>
-</ul>
-</div>
-
-<div class="license">
-<h2 data-toc-skip>License</h2>
-<ul class="list-unstyled">
-<li>
-<a href="https://www.r-project.org/Licenses/GPL-2" class="external-link">GPL-2</a> | file <a href="LICENSE-text.html">LICENSE</a>
-</li>
-</ul>
-</div>
-
-
-<div class="citation">
-<h2 data-toc-skip>Citation</h2>
-<ul class="list-unstyled">
-<li><a href="authors.html#citation">Citing AMR</a></li>
-</ul>
-</div>
-
-<div class="developers">
-<h2 data-toc-skip>Developers</h2>
-<ul class="list-unstyled">
-<li>Matthijs S. Berends <br><small class="roles"> Author, maintainer </small> <a href="https://orcid.org/0000-0001-7620-1800" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
-<li>Christian F. Luz <br><small class="roles"> Author, contributor </small> <a href="https://orcid.org/0000-0001-5809-5995" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
-<li>Dennis Souverein <br><small class="roles"> Author, contributor </small> <a href="https://orcid.org/0000-0003-0455-0336" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
-<li>Erwin E. A. Hassing <br><small class="roles"> Author, contributor </small> </li>
-<li><a href="authors.html">More about authors...</a></li>
-</ul>
-</div>
-
-
-
- </div>
-</div>
-
-
- <footer><div class="copyright">
- <p></p>
-<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p>
-</div>
-
-<div class="pkgdown">
- <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p>
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- <h1 data-toc-skip>Changelog <small></small></h1>
- <small>Source: <a href="https://github.com/msberends/AMR/blob/HEAD/NEWS.md" class="external-link"><code>NEWS.md</code></a></small>
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- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.8.1.9014" id="amr-1819014">
-<code>AMR</code> 1.8.1.9014<a class="anchor" aria-label="anchor" href="#amr-1819014"></a></h2>
-<div class="section level3">
-<h3 id="last-updated-august-1-8-1-9014"><small>Last updated: 12 August 2022</small><a class="anchor" aria-label="anchor" href="#last-updated-august-1-8-1-9014"></a></h3>
-<div class="section level4">
-<h4 id="new-1-8-1-9014">New<a class="anchor" aria-label="anchor" href="#new-1-8-1-9014"></a></h4>
-<ul><li>EUCAST 2022 and CLSI 2022 guidelines have been added for <code><a href="../reference/as.rsi.html">as.rsi()</a></code>. EUCAST 2022 is now the new default guideline for all MIC and disks diffusion interpretations.</li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-1-8-1-9014">Changed<a class="anchor" aria-label="anchor" href="#changed-1-8-1-9014"></a></h4>
-<ul><li>Fix for <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on certain EUCAST breakpoints for MIC values</li>
-<li>Removed <code><a href="https://rdrr.io/r/base/integer.html" class="external-link">as.integer()</a></code> for MIC values, since MIC are not integer values and running <code><a href="https://rdrr.io/r/base/table.html" class="external-link">table()</a></code> on MIC values consequently failed for not being able to retrieve the level position (as that’s how normally <code><a href="https://rdrr.io/r/base/integer.html" class="external-link">as.integer()</a></code> on <code>factor</code>s work)</li>
-<li>
-<code><a href="https://rdrr.io/r/base/droplevels.html" class="external-link">droplevels()</a></code> on MIC will now return a common <code>factor</code> at default and will lose the <code><mic></code> class. Use <code>droplevels(..., as.mic = TRUE)</code> to keep the <code><mic></code> class.</li>
-<li>Small fix for using <code><a href="../reference/ab_from_text.html">ab_from_text()</a></code>
-</li>
-<li>Fixes for reading in text files using <code><a href="../reference/mo_source.html">set_mo_source()</a></code>, which now also allows the source file to contain valid taxonomic names instead of only valid microorganism ID of this package</li>
-<li>Using any <code>random_*()</code> function (such as <code><a href="../reference/random.html">random_mic()</a></code>) is now possible by directly calling the package without loading it first: <code>AMR::random_mic(10)</code>
-</li>
-<li>Added <em>Toxoplasma gondii</em> (<code>P_TXPL_GOND</code>) to the <code>microorganisms</code> data set, together with its genus, family, and order</li>
-<li>Changed value in column <code>prevalence</code> of the <code>microorganisms</code> data set from 3 to 2 for these genera: <em>Acholeplasma</em>, <em>Alistipes</em>, <em>Alloprevotella</em>, <em>Bergeyella</em>, <em>Borrelia</em>, <em>Brachyspira</em>, <em>Butyricimonas</em>, <em>Cetobacterium</em>, <em>Chlamydia</em>, <em>Chlamydophila</em>, <em>Deinococcus</em>, <em>Dysgonomonas</em>, <em>Elizabethkingia</em>, <em>Empedobacter</em>, <em>Haloarcula</em>, <em>Halobacterium</em>, <em>Halococcus</em>, <em>Myroides</em>, <em>Odoribacter</em>, <em>Ornithobacterium</em>, <em>Parabacteroides</em>, <em>Pedobacter</em>, <em>Phocaeicola</em>, <em>Porphyromonas</em>, <em>Riemerella</em>, <em>Sphingobacterium</em>, <em>Streptobacillus</em>, <em>Tenacibaculum</em>, <em>Terrimonas</em>, <em>Victivallis</em>, <em>Wautersiella</em>, <em>Weeksella</em>
-</li>
-</ul></div>
-</div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.8.1" id="amr-181">
-<code>AMR</code> 1.8.1<small>2022-03-24</small><a class="anchor" aria-label="anchor" href="#amr-181"></a></h2>
-<div class="section level4">
-<h4 id="changed-1-8-1">Changed<a class="anchor" aria-label="anchor" href="#changed-1-8-1"></a></h4>
-<ul><li><p>Fix for using <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on values containing capped values (such as <code>>=</code>), sometimes leading to <code>NA</code></p></li>
-<li><p>Support for antibiotic interpretations of the MIPS laboratory system: <code>"U"</code> for S (‘susceptible urine’), <code>"D"</code> for I (‘susceptible dose-dependent’)</p></li>
-<li>
-<p>Improved algorithm of <code><a href="../reference/as.mo.html">as.mo()</a></code>, especially for ignoring non-taxonomic text, such as:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"methicillin-resistant S. aureus (MRSA)"</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "Staphylococcus aureus"</span></span></code></pre></div>
-</li>
-<li><p>More informative warning messages</p></li>
-<li><p>Added 192 as valid MIC</p></li>
-<li><p>Updated MIC printing in tibbles</p></li>
-<li><p>Increased speed for loading the package</p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-8-1">Other<a class="anchor" aria-label="anchor" href="#other-1-8-1"></a></h4>
-<ul><li>Fix for unit testing on R 3.3</li>
-<li>Fix for size of some image elements, as requested by CRAN</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.8.0" id="amr-180">
-<code>AMR</code> 1.8.0<small>2022-01-07</small><a class="anchor" aria-label="anchor" href="#amr-180"></a></h2>
-<div class="section level4">
-<h4 id="breaking-changes-1-8-0">Breaking changes<a class="anchor" aria-label="anchor" href="#breaking-changes-1-8-0"></a></h4>
-<ul><li>Removed <code>p_symbol()</code> and all <code>filter_*()</code> functions (except for <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>), which were all deprecated in a previous package version</li>
-<li>Removed the <code>key_antibiotics()</code> and <code>key_antibiotics_equal()</code> functions, which were deprecated and superseded by <code><a href="../reference/key_antimicrobials.html">key_antimicrobials()</a></code> and <code><a href="../reference/key_antimicrobials.html">antimicrobials_equal()</a></code>
-</li>
-<li>Removed all previously implemented <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot2::ggplot()</a></code> generics for classes <code><mic></code>, <code><disk></code>, <code><rsi></code> and <code><resistance_predict></code> as they did not follow the <code>ggplot2</code> logic. They were replaced with <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">ggplot2::autoplot()</a></code> generics.</li>
-<li>Renamed function <code>get_locale()</code> to <code><a href="../reference/translate.html">get_AMR_locale()</a></code> to prevent conflicts with other packages</li>
-</ul></div>
-<div class="section level4">
-<h4 id="new-1-8-0">New<a class="anchor" aria-label="anchor" href="#new-1-8-0"></a></h4>
-<ul><li><p>Support for the CLSI 2021 guideline for interpreting MIC/disk diffusion values, which are incorporated in the <code>rsi_translation</code> data set. This data set now more strictly follows the WHONET software as well.</p></li>
-<li><p>Support for EUCAST Intrinsic Resistance and Unusual Phenotypes v3.3 (October 2021). This is now the default EUCAST guideline in the package (all older guidelines are still available) for <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>, <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> and <code><a href="../reference/mdro.html">mdro()</a></code>. The <code>intrinsic_resistant</code> data set was also updated accordingly.</p></li>
-<li><p>Support for all antimicrobial drug (group) names and colloquial microorganism names in Danish, Dutch, English, French, German, Italian, Portuguese, Russian, Spanish and Swedish</p></li>
-<li>
-<p>Function <code><a href="../reference/ab_property.html">set_ab_names()</a></code> to rename data set columns that resemble antimicrobial drugs. This allows for quickly renaming columns to official names, ATC codes, etc. Its second argument can be a tidyverse way of selecting:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="../reference/ab_property.html">set_ab_names</a></span><span class="op">(</span><span class="fu">where</span><span class="op">(</span><span class="va">is.rsi</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="../reference/ab_property.html">set_ab_names</a></span><span class="op">(</span><span class="va">AMC</span><span class="op">:</span><span class="va">GEN</span>, property <span class="op">=</span> <span class="st">"atc"</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li><p>Function <code><a href="../reference/mo_property.html">mo_lpsn()</a></code> to retrieve the <a href="https://lpsn.dsmz.de" class="external-link">LPSN</a> record ID</p></li>
-<li><p>Function <code><a href="../reference/ab_property.html">ab_ddd_units()</a></code> to get units of DDDs (daily defined doses), deprecating the use of <code>ab_ddd(..., units = TRUE)</code> to be more consistent in data types of function output</p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-1-8-0">Changed<a class="anchor" aria-label="anchor" href="#changed-1-8-0"></a></h4>
-<ul><li>Updated the bacterial taxonomy to 5 October 2021 (according to <a href="https://lpsn.dsmz.de" class="external-link">LPSN</a>), including all 11 new staphylococcal species named since 1 January last year</li>
-<li>The <code>antibiotics</code> data set now contains <strong>all ATC codes</strong> that are available through the <a href="https://www.whocc.no" class="external-link">WHOCC website</a>, regardless of drugs being present in more than one ATC group. This means that:
-<ul><li>Some drugs now contain multiple ATC codes (e.g., metronidazole contains 5)</li>
-<li>
-<code>antibiotics$atc</code> is now a <code>list</code> containing <code>character</code> vectors, and this <code>atc</code> column was moved to the 5th position of the <code>antibiotics</code> data set</li>
-<li>
-<code><a href="../reference/ab_property.html">ab_atc()</a></code> does not always return a character vector of length 1, and returns a <code>list</code> if the input is larger than length 1</li>
-<li>
-<code><a href="../reference/ab_property.html">ab_info()</a></code> has a slightly different output</li>
-<li>Some DDDs (daily defined doses) were added or updated according to newly included ATC codes</li>
-</ul></li>
-<li>Antibiotic selectors
-<ul><li><p>They now also work in R-3.0 and R-3.1, supporting every version of R since 2013 like the rest of the package</p></li>
-<li><p>Added more selectors for antibiotic classes: <code><a href="../reference/antibiotic_class_selectors.html">aminopenicillins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">antifungals()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">antimycobacterials()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lincosamides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lipoglycopeptides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">polymyxins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">quinolones()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">streptogramins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">trimethoprims()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">ureidopenicillins()</a></code></p></li>
-<li>
-<p>Added specific selectors for certain types for treatment: <code><a href="../reference/antibiotic_class_selectors.html">administrable_per_os()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">administrable_iv()</a></code>, which are based on available Defined Daily Doses (DDDs), as defined by the WHOCC. These are ideal for e.g. analysing pathogens in primary care where IV treatment is not an option. They can be combined with other AB selectors, e.g. to select penicillins that are only administrable per os (i.e., orally):</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">example_isolates</span><span class="op">[</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">penicillins</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&</span> <span class="fu"><a href="../reference/antibiotic_class_selectors.html">administrable_per_os</a></span><span class="op">(</span><span class="op">)</span><span class="op">]</span> <span class="co"># base R</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">penicillins</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&</span> <span class="fu"><a href="../reference/antibiotic_class_selectors.html">administrable_per_os</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co"># dplyr</span></span></code></pre></div>
-</li>
-<li>
-<p>Added the selector <code><a href="../reference/antibiotic_class_selectors.html">ab_selector()</a></code>, which accepts a filter to be used internally on the <code>antibiotics</code> data set, yielding great flexibility on drug properties, such as selecting antibiotic columns with an oral DDD of at least 1 gram:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">example_isolates</span><span class="op">[</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">ab_selector</a></span><span class="op">(</span><span class="va">oral_ddd</span> <span class="op">></span> <span class="fl">1</span> <span class="op">&</span> <span class="va">oral_units</span> <span class="op">==</span> <span class="st">"g"</span><span class="op">)</span><span class="op">]</span> <span class="co"># base R</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">ab_selector</a></span><span class="op">(</span><span class="va">oral_ddd</span> <span class="op">></span> <span class="fl">1</span> <span class="op">&</span> <span class="va">oral_units</span> <span class="op">==</span> <span class="st">"g"</span><span class="op">)</span><span class="op">)</span> <span class="co"># dplyr</span></span></code></pre></div>
-</li>
-<li><p>Added the selector <code><a href="../reference/antibiotic_class_selectors.html">not_intrinsic_resistant()</a></code>, which only keeps antibiotic columns that are not intrinsic resistant for all microorganisms in a data set, based on the latest EUCAST guideline on intrinsic resistance. For example, if a data set contains only microorganism codes or names of <em>E. coli</em> and <em>K. pneumoniae</em> and contains a column “vancomycin”, this column will be removed (or rather, unselected) using this function.</p></li>
-<li><p>Added argument <code>only_treatable</code>, which defaults to <code>TRUE</code> and will exclude drugs that are only for laboratory tests and not for treating patients (such as imipenem/EDTA and gentamicin-high)</p></li>
-<li><p>Fix for using selectors multiple times in one call (e.g., using them in <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">dplyr::filter()</a></code> and immediately after in <code><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">dplyr::select()</a></code>)</p></li>
-<li><p>Fix for using having multiple columns that are coerced to the same antibiotic agent</p></li>
-<li><p>Fixed for using <code><a href="https://rdrr.io/r/base/all.html" class="external-link">all()</a></code> or <code><a href="https://rdrr.io/r/base/any.html" class="external-link">any()</a></code> on antibiotic selectors in an R Markdown file</p></li>
-</ul></li>
-<li>Added the following antimicrobial agents that are now covered by the WHO: aztreonam/nacubactam (ANC), cefepime/nacubactam (FNC), exebacase (EXE), ozenoxacin (OZN), zoliflodacin (ZFD), manogepix (MGX), ibrexafungerp (IBX), and rezafungin (RZF). None of these agents have an ATC code yet.</li>
-<li>Fixed the Gram stain (<code><a href="../reference/mo_property.html">mo_gramstain()</a></code>) determination of the taxonomic class Negativicutes within the phylum of Firmicutes - they were considered Gram-positives because of their phylum but are actually Gram-negative. This impacts 137 taxonomic species, genera and families, such as <em>Negativicoccus</em> and <em>Veillonella</em>.</li>
-<li>Dramatic speed improvement for <code><a href="../reference/first_isolate.html">first_isolate()</a></code>
-</li>
-<li>Fix to prevent introducing <code>NA</code>s for old MO codes when running <code><a href="../reference/as.mo.html">as.mo()</a></code> on them</li>
-<li>Added more informative error messages when any of the <code>proportion_*()</code> and <code>count_*()</code> functions fail</li>
-<li>When printing a tibble with any old MO code, a warning will be thrown that old codes should be updated using <code><a href="../reference/as.mo.html">as.mo()</a></code>
-</li>
-<li>Improved automatic column selector when <code>col_*</code> arguments are left blank, e.g. in <code><a href="../reference/first_isolate.html">first_isolate()</a></code>
-</li>
-<li>The right input types for <code><a href="../reference/random.html">random_mic()</a></code>, <code><a href="../reference/random.html">random_disk()</a></code> and <code><a href="../reference/random.html">random_rsi()</a></code> are now enforced</li>
-<li>
-<code><a href="../reference/as.rsi.html">as.rsi()</a></code> has an improved algorithm and can now also correct for textual input (such as “Susceptible”, “Resistant”) in all supported languages</li>
-<li>
-<code><a href="../reference/as.mic.html">as.mic()</a></code> has an improved algorithm</li>
-<li>When warnings are thrown because of too few isolates in any <code>count_*()</code>, <code>proportion_*()</code> function (or <code>resistant()</code> or <code>susceptible()</code>), the <code>dplyr</code> group will be shown, if available</li>
-<li>Fix for legends created with <code><a href="../reference/ggplot_rsi.html">scale_rsi_colours()</a></code> when using <code>ggplot2</code> v3.3.4 or higher (this is ggplot2 bug 4511, soon to be fixed)</li>
-<li>Fix for minor translation errors</li>
-<li>Fix for the MIC interpretation of <em>Morganellaceae</em> (such as <em>Morganella</em> and <em>Proteus</em>) when using the EUCAST 2021 guideline</li>
-<li>Improved algorithm of <code><a href="../reference/as.mo.html">as.mo()</a></code>
-</li>
-<li>Improved algorithm for generating random MICs with <code><a href="../reference/random.html">random_mic()</a></code>
-</li>
-<li>Improved plot legends for MICs and disk diffusion values</li>
-<li>Improved speed of <code><a href="../reference/as.ab.html">as.ab()</a></code> and all <code>ab_*()</code> functions</li>
-<li>Added <code>fortify()</code> extensions for plotting methods</li>
-<li>
-<code>NA</code> values of the classes <code><mic></code>, <code><disk></code> and <code><rsi></code> are now exported objects of this package, e.g. <code>NA_mic_</code> is an <code>NA</code> of class <code>mic</code> (just like the base R <code>NA_character_</code> is an <code>NA</code> of class <code>character</code>)</li>
-<li>The <code><a href="../reference/proportion.html">proportion_df()</a></code>, <code><a href="../reference/count.html">count_df()</a></code> and <code><a href="../reference/proportion.html">rsi_df()</a></code> functions now return with the additional S3 class ‘rsi_df’ so they can be extended by other packages</li>
-<li>The <code><a href="../reference/mdro.html">mdro()</a></code> function now returns <code>NA</code> for all rows that have no test results</li>
-<li>The <code>species_id</code> column in the <code>microorganisms</code> data set now only contains LPSN record numbers. For this reason, this column is now numeric instead of a character, and <code><a href="../reference/mo_property.html">mo_url()</a></code> has been updated to reflect this change.</li>
-<li>Fixed a small bug in the functions <code><a href="../reference/get_episode.html">get_episode()</a></code> and <code><a href="../reference/get_episode.html">is_new_episode()</a></code>
-</li>
-<li>
-<code><a href="../reference/get_episode.html">get_episode()</a></code> and <code><a href="../reference/get_episode.html">is_new_episode()</a></code> can now cope with <code>NA</code>s</li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-8-0">Other<a class="anchor" aria-label="anchor" href="#other-1-8-0"></a></h4>
-<ul><li>This package is now being maintained by two epidemiologists and a data scientist from two different non-profit healthcare organisations.</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.7.1" id="amr-171">AMR 1.7.1<small>2021-06-03</small><a class="anchor" aria-label="anchor" href="#amr-171"></a></h2>
-<div class="section level4">
-<h4 id="breaking-change-1-7-1">Breaking change<a class="anchor" aria-label="anchor" href="#breaking-change-1-7-1"></a></h4>
-<ul><li>
-<p>All antibiotic class selectors (such as <code><a href="../reference/antibiotic_class_selectors.html">carbapenems()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code>) can now be used for filtering as well, making all their accompanying <code>filter_*()</code> functions redundant (such as <code>filter_carbapenems()</code>, <code>filter_aminoglycosides()</code>). These functions are now deprecated and will be removed in a next release. Examples of how the selectors can be used for filtering:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># select columns with results for carbapenems</span></span>
-<span><span class="va">example_isolates</span><span class="op">[</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">]</span> <span class="co"># base R</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co"># dplyr</span></span>
-<span></span>
-<span><span class="co"># filter rows for resistance in any carbapenem</span></span>
-<span><span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>, <span class="op">]</span> <span class="co"># base R</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span> <span class="co"># dplyr</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">if_any</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span>, <span class="op">~</span><span class="va">.x</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span> <span class="co"># dplyr (formal)</span></span>
-<span></span>
-<span><span class="co"># filter rows for resistance in all carbapenems</span></span>
-<span><span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>, <span class="op">]</span> <span class="co"># base R</span></span>
-<span><span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span>, <span class="op">]</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span> <span class="co"># dplyr</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span></span></code></pre></div>
-</li>
-</ul></div>
-<div class="section level4">
-<h4 id="new-1-7-1">New<a class="anchor" aria-label="anchor" href="#new-1-7-1"></a></h4>
-<ul><li>Support for CLSI 2020 guideline for interpreting MICs and disk diffusion values (using <code><a href="../reference/as.rsi.html">as.rsi()</a></code>)</li>
-<li>Function <code><a href="../reference/custom_eucast_rules.html">custom_eucast_rules()</a></code> that brings support for custom AMR rules in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
-</li>
-<li>Function <code><a href="../reference/italicise_taxonomy.html">italicise_taxonomy()</a></code> to make taxonomic names within a string italic, with support for markdown and ANSI</li>
-<li>Support for all four methods to determine first isolates as summarised by Hindler <em>et al.</em> (doi: <a href="https://doi.org/10.1086/511864" class="external-link">10.1086/511864</a>): isolate-based, patient-based, episode-based and phenotype-based. The last method is now the default.
-<ul><li>The <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function gained the argument <code>method</code> that has to be “phenotype-based”, “episode-based”, “patient-based”, or “isolate-based”. The old behaviour is equal to “episode-based”. The new default is “phenotype-based” if antimicrobial test results are available, and “episode-based” otherwise. This new default will yield slightly more isolates for selection (which is a good thing).</li>
-<li>Since fungal isolates can also be selected, the functions <code>key_antibiotics()</code> and <code>key_antibiotics_equal()</code> are now deprecated in favour of the <code><a href="../reference/key_antimicrobials.html">key_antimicrobials()</a></code> and <code><a href="../reference/key_antimicrobials.html">antimicrobials_equal()</a></code> functions. Also, the new <code><a href="../reference/key_antimicrobials.html">all_antimicrobials()</a></code> function works like the old <code>key_antibiotics()</code> function, but includes any column with antimicrobial test results. Using <code><a href="../reference/key_antimicrobials.html">key_antimicrobials()</a></code> still only selects six preferred antibiotics for Gram-negatives, six for Gram-positives, and six universal antibiotics. It has a new <code>antifungal</code> argument to set antifungal agents (antimycotics).</li>
-<li>Using <code>type == "points"</code> in the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function for phenotype-based selection will now consider all antimicrobial drugs in the data set, using the new <code><a href="../reference/key_antimicrobials.html">all_antimicrobials()</a></code>
-</li>
-<li>The <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function can now take a vector of values for <code>col_keyantibiotics</code> and can have an episode length of <code>Inf</code>
-</li>
-<li>Since the phenotype-based method is the new default, <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> renders the <code>filter_first_weighted_isolate()</code> function redundant. For this reason, <code>filter_first_weighted_isolate()</code> is now deprecated.</li>
-<li>The documentation of the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> and <code><a href="../reference/key_antimicrobials.html">key_antimicrobials()</a></code> functions has been completely rewritten.</li>
-</ul></li>
-<li>Function <code><a href="../reference/antibiotic_class_selectors.html">betalactams()</a></code> as additional antbiotic column selector and function <code>filter_betalactams()</code> as additional antbiotic column filter. The group of betalactams consists of all carbapenems, cephalosporins and penicillins.</li>
-<li>A <code>ggplot()</code> method for <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>
-</li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-1-7-1">Changed<a class="anchor" aria-label="anchor" href="#changed-1-7-1"></a></h4>
-<ul><li>
-<code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> now supports grouping using the <code>dplyr</code> package</li>
-<li>Custom MDRO guidelines (<code><a href="../reference/mdro.html">mdro()</a></code>, <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code>):
-<ul><li>Custom MDRO guidelines can now be combined with other custom MDRO guidelines using <code><a href="https://rdrr.io/r/base/c.html" class="external-link">c()</a></code>
-</li>
-<li>Fix for applying the rules; in previous versions, rows were interpreted according to the last matched rule. Now, rows are interpreted according to the first matched rule</li>
-</ul></li>
-<li>Fix for <code><a href="../reference/age_groups.html">age_groups()</a></code> for persons aged zero</li>
-<li>The <code>example_isolates</code> data set now contains some (fictitious) zero-year old patients</li>
-<li>Fix for minor translation errors</li>
-<li>Printing of microbial codes in a <code>data.frame</code> or <code>tibble</code> now gives a warning if the data contains old microbial codes (from a previous AMR package version)</li>
-<li>Extended the <code><a href="../reference/like.html">like()</a></code> functions:
-<ul><li><p>Now checks if <code>pattern</code> is a <em>valid</em> regular expression</p></li>
-<li>
-<p>Added <code>%unlike%</code> and <code>%unlike_case%</code> (as negations of the existing <code>%like%</code> and <code>%like_case%</code>). This greatly improves readability:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw">if</span> <span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/grep.html" class="external-link">grepl</a></span><span class="op">(</span><span class="st">"EUCAST"</span>, <span class="va">guideline</span><span class="op">)</span><span class="op">)</span> <span class="va">...</span></span>
-<span><span class="co"># same:</span></span>
-<span><span class="kw">if</span> <span class="op">(</span><span class="va">guideline</span> <span class="op"><a href="../reference/like.html">%unlike%</a></span> <span class="st">"EUCAST"</span><span class="op">)</span> <span class="va">...</span></span></code></pre></div>
-</li>
-<li><p>Altered the RStudio addin, so it now iterates over <code>%like%</code> -> <code>%unlike%</code> -> <code>%like_case%</code> -> <code>%unlike_case%</code> if you keep pressing your keyboard shortcut</p></li>
-</ul></li>
-<li>Fixed an installation error on R-3.0</li>
-<li>Added <code>info</code> argument to <code><a href="../reference/as.mo.html">as.mo()</a></code> to turn on/off the progress bar</li>
-<li>Fixed a bug where <code>col_mo</code> in some functions (esp. <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> and <code><a href="../reference/mdro.html">mdro()</a></code>) could not be a column name of the <code>microorganisms</code> data set as it would throw an error</li>
-<li>Fix for transforming numeric values to RSI (<code><a href="../reference/as.rsi.html">as.rsi()</a></code>) when the <code>vctrs</code> package is loaded (i.e., when using tidyverse)</li>
-<li>Colour fix for using <code><a href="https://rdrr.io/r/graphics/barplot.html" class="external-link">barplot()</a></code> on an RSI class</li>
-<li>Added 25 common system codes for bacteria to the <code>microorganisms.codes</code> data set</li>
-<li>Added 16 common system codes for antimicrobial agents to the <code>antibiotics</code> data set</li>
-<li>Fix for using <code><a href="https://docs.ropensci.org/skimr/reference/skim.html" class="external-link">skimr::skim()</a></code> on classes <code>mo</code>, <code>mic</code> and <code>disk</code> when using the just released <code>dplyr</code> v1.0.6</li>
-<li>Updated <code><a href="https://docs.ropensci.org/skimr/reference/skim.html" class="external-link">skimr::skim()</a></code> usage for MIC values to also include 25th and 75th percentiles</li>
-<li>Fix for plotting missing MIC/disk diffusion values</li>
-<li>Updated join functions to always use <code>dplyr</code> join functions if the <code>dplyr</code> package is installed - now also preserving grouped variables</li>
-<li>Antibiotic class selectors (such as <code><a href="../reference/antibiotic_class_selectors.html">cephalosporins()</a></code>) now maintain the column order from the original data</li>
-<li>Fix for selecting columns using <code><a href="../reference/antibiotic_class_selectors.html">fluoroquinolones()</a></code>
-</li>
-<li>
-<code><a href="../reference/age.html">age()</a></code> now vectorises over both <code>x</code> and <code>reference</code>
-</li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-7-1">Other<a class="anchor" aria-label="anchor" href="#other-1-7-1"></a></h4>
-<ul><li>As requested by CRAN administrators: decreased package size by 3 MB in costs of a slower loading time of the package</li>
-<li>All unit tests are now processed by the <code>tinytest</code> package, instead of the <code>testthat</code> package. The <code>testthat</code> package unfortunately requires tons of dependencies that are also heavy and only usable for recent R versions, disallowing developers to test a package under any R 3.* version. On the contrary, the <code>tinytest</code> package is very lightweight and dependency-free.</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.6.0" id="amr-160">AMR 1.6.0<small>2021-03-14</small><a class="anchor" aria-label="anchor" href="#amr-160"></a></h2>
-<div class="section level4">
-<h4 id="new-1-6-0">New<a class="anchor" aria-label="anchor" href="#new-1-6-0"></a></h4>
-<ul><li>
-<p>Support for EUCAST Clinical Breakpoints v11.0 (2021), effective in the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function and in <code><a href="../reference/as.rsi.html">as.rsi()</a></code> to interpret MIC and disk diffusion values. This is now the default guideline in this package.</p>
-<ul><li>Added function <code><a href="../reference/eucast_rules.html">eucast_dosage()</a></code> to get a <code>data.frame</code> with advised dosages of a certain bug-drug combination, which is based on the new <code>dosage</code> data set</li>
-<li>Added data set <code>dosage</code> to fuel the new <code><a href="../reference/eucast_rules.html">eucast_dosage()</a></code> function and to make this data available in a structured way</li>
-<li>Existing data set <code>example_isolates</code> now reflects the latest EUCAST rules</li>
-</ul></li>
-<li>
-<p>Added argument <code>only_rsi_columns</code> for some functions, which defaults to <code>FALSE</code>, to indicate if the functions must only be applied to columns that are of class <code><rsi></code> (i.e., transformed with <code><a href="../reference/as.rsi.html">as.rsi()</a></code>). This increases speed since automatic determination of antibiotic columns is not needed anymore. Affected functions are:</p>
-<ul><li>All antibiotic selector functions (<code><a href="../reference/antibiotic_class_selectors.html">ab_class()</a></code> and its wrappers, such as <code><a href="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">carbapenems()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">penicillins()</a></code>)</li>
-<li>All antibiotic filter functions (<code>filter_ab_class()</code> and its wrappers, such as <code>filter_aminoglycosides()</code>, <code>filter_carbapenems()</code>, <code>filter_penicillins()</code>)</li>
-<li><code><a href="../reference/eucast_rules.html">eucast_rules()</a></code></li>
-<li>
-<code><a href="../reference/mdro.html">mdro()</a></code> (including wrappers such as <code><a href="../reference/mdro.html">brmo()</a></code>, <code><a href="../reference/mdro.html">mrgn()</a></code> and <code><a href="../reference/mdro.html">eucast_exceptional_phenotypes()</a></code>)</li>
-<li><code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code></li>
-</ul></li>
-<li>
-<p>Functions <code><a href="../reference/antibiotic_class_selectors.html">oxazolidinones()</a></code> (an antibiotic selector function) and <code>filter_oxazolidinones()</code> (an antibiotic filter function) to select/filter on e.g. linezolid and tedizolid</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span><span class="va">x</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">date</span>, <span class="va">hospital_id</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">oxazolidinones</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#> Selecting oxazolidinones: column 'LNZ' (linezolid)</span></span>
-<span></span>
-<span><span class="va">x</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">filter_oxazolidinones</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#> Filtering on oxazolidinones: value in column `LNZ` (linezolid) is either "R", "S" or "I"</span></span></code></pre></div>
-</li>
-<li><p>Support for custom MDRO guidelines, using the new <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function, please see <code><a href="../reference/mdro.html">mdro()</a></code> for additional info</p></li>
-<li><p><code>ggplot()</code> generics for classes <code><mic></code> and <code><disk></code></p></li>
-<li>
-<p>Function <code><a href="../reference/mo_property.html">mo_is_yeast()</a></code>, which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_kingdom</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Aspergillus"</span>, <span class="st">"Candida"</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "Fungi" "Fungi"</span></span>
-<span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_is_yeast</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Aspergillus"</span>, <span class="st">"Candida"</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#> [1] FALSE TRUE</span></span>
-<span></span>
-<span><span class="co"># usage for filtering data:</span></span>
-<span><span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_is_yeast</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>, <span class="op">]</span> <span class="co"># base R</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_is_yeast</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co"># dplyr</span></span></code></pre></div>
-<p>The <code><a href="../reference/mo_property.html">mo_type()</a></code> function has also been updated to reflect this change:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_type</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Aspergillus"</span>, <span class="st">"Candida"</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co"># [1] "Fungi" "Yeasts"</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_type</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Aspergillus"</span>, <span class="st">"Candida"</span><span class="op">)</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span> <span class="co"># also supported: de, nl, fr, it, pt</span></span>
-<span><span class="co">#> [1] "Hongos" "Levaduras"</span></span></code></pre></div>
-</li>
-<li><p>Added Pretomanid (PMD, J04AK08) to the <code>antibiotics</code> data set</p></li>
-<li>
-<p>MIC values (see <code><a href="../reference/as.mic.html">as.mic()</a></code>) can now be used in any mathematical processing, such as usage inside functions <code><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">min()</a></code>, <code><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max()</a></code>, <code><a href="https://rdrr.io/r/base/range.html" class="external-link">range()</a></code>, and with binary operators (<code>+</code>, <code>-</code>, etc.). This allows for easy distribution analysis and fast filtering on MIC values:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="../reference/random.html">random_mic</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span>
-<span><span class="va">x</span></span>
-<span><span class="co">#> Class <mic></span></span>
-<span><span class="co">#> [1] 128 0.5 2 0.125 64 0.25 >=256 8 16 4</span></span>
-<span><span class="va">x</span><span class="op">[</span><span class="va">x</span> <span class="op">></span> <span class="fl">4</span><span class="op">]</span></span>
-<span><span class="co">#> Class <mic></span></span>
-<span><span class="co">#> [1] 128 64 >=256 8 16</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/range.html" class="external-link">range</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span><span class="co">#> [1] 0.125 256.000</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/range.html" class="external-link">range</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#> [1] -3 8</span></span></code></pre></div>
-</li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-1-6-0">Changed<a class="anchor" aria-label="anchor" href="#changed-1-6-0"></a></h4>
-<ul><li>Updated the bacterial taxonomy to 3 March 2021 (using <a href="https://lpsn.dsmz.de" class="external-link">LPSN</a>)
-<ul><li>Added 3,372 new species and 1,523 existing species became synomyms</li>
-<li>The URL of a bacterial species (<code><a href="../reference/mo_property.html">mo_url()</a></code>) will now lead to <a href="https://lpsn.dsmz.de" class="external-link uri">https://lpsn.dsmz.de</a>
-</li>
-</ul></li>
-<li>Big update for plotting classes <code>rsi</code>, <code><mic></code>, and <code><disk></code>:
-<ul><li>Plotting of MIC and disk diffusion values now support interpretation colouring if you supply the microorganism and antimicrobial agent</li>
-<li>All colours were updated to colour-blind friendly versions for values R, S and I for all plot methods (also applies to tibble printing)</li>
-<li>Interpretation of MIC and disk diffusion values to R/SI will now be translated if the system language is German, Dutch or Spanish (see <code>translate</code>)</li>
-<li>Plotting is now possible with base R using <code><a href="../reference/plot.html">plot()</a></code> and with ggplot2 using <code>ggplot()</code> on any vector of MIC and disk diffusion values</li>
-</ul></li>
-<li>Updated SNOMED codes to US Edition of SNOMED CT from 1 September 2020 and added the source to the help page of the <code>microorganisms</code> data set</li>
-<li>
-<code><a href="../reference/as.rsi.html">is.rsi()</a></code> and <code><a href="../reference/as.rsi.html">is.rsi.eligible()</a></code> now return a vector of <code>TRUE</code>/<code>FALSE</code> when the input is a data set, by iterating over all columns</li>
-<li>Using functions without setting a data set (e.g., <code><a href="../reference/mo_property.html">mo_is_gram_negative()</a></code>, <code><a href="../reference/mo_property.html">mo_is_gram_positive()</a></code>, <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>, <code><a href="../reference/first_isolate.html">first_isolate()</a></code>, <code><a href="../reference/mdro.html">mdro()</a></code>) now work with <code>dplyr</code>s <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> again</li>
-<li>
-<code><a href="../reference/first_isolate.html">first_isolate()</a></code> can be used with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> (also when using a dot <code>.</code> as input for the data) and now returns the names of the groups</li>
-<li>Updated the data set <code>microorganisms.codes</code> (which contains popular LIS and WHONET codes for microorganisms) for some species of <em>Mycobacterium</em> that previously incorrectly returned <em>M. africanum</em>
-</li>
-<li>WHONET code <code>"PNV"</code> will now correctly be interpreted as <code>PHN</code>, the antibiotic code for phenoxymethylpenicillin (‘peni V’)</li>
-<li>Fix for verbose output of <code>mdro(..., verbose = TRUE)</code> for German guideline (3MGRN and 4MGRN) and Dutch guideline (BRMO, only <em>P. aeruginosa</em>)</li>
-<li>
-<code><a href="../reference/as.rsi.html">is.rsi.eligible()</a></code> now detects if the column name resembles an antibiotic name or code and now returns <code>TRUE</code> immediately if the input contains any of the values “R”, “S” or “I”. This drastically improves speed, also for a lot of other functions that rely on automatic determination of antibiotic columns.</li>
-<li>Functions <code><a href="../reference/get_episode.html">get_episode()</a></code> and <code><a href="../reference/get_episode.html">is_new_episode()</a></code> now support less than a day as value for argument <code>episode_days</code> (e.g., to include one patient/test per hour)</li>
-<li>Argument <code>ampc_cephalosporin_resistance</code> in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> now also applies to value “I” (not only “S”)</li>
-<li>Functions <code><a href="https://rdrr.io/r/base/print.html" class="external-link">print()</a></code> and <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code> on a Principal Components Analysis object (<code><a href="../reference/pca.html">pca()</a></code>) now print additional group info if the original data was grouped using <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">dplyr::group_by()</a></code>
-</li>
-<li>Improved speed and reliability of <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code>. As this also internally improves the reliability of <code><a href="../reference/first_isolate.html">first_isolate()</a></code> and <code><a href="../reference/mdro.html">mdro()</a></code>, this might have a slight impact on the results of those functions.</li>
-<li>Fix for <code><a href="../reference/mo_property.html">mo_name()</a></code> when used in other languages than English</li>
-<li>The <code><a href="../reference/like.html">like()</a></code> function (and its fast alias <code>%like%</code>) now always use Perl compatibility, improving speed for many functions in this package (e.g., <code><a href="../reference/as.mo.html">as.mo()</a></code> is now up to 4 times faster)</li>
-<li>
-<em>Staphylococcus cornubiensis</em> is now correctly categorised as coagulase-positive</li>
-<li>
-<code><a href="../reference/random.html">random_disk()</a></code> and <code><a href="../reference/random.html">random_mic()</a></code> now have an expanded range in their randomisation</li>
-<li>Support for GISA (glycopeptide-intermediate <em>S. aureus</em>), so e.g. <code>mo_genus("GISA")</code> will return <code>"Staphylococcus"</code>
-</li>
-<li>Added translations of German and Spanish for more than 200 antimicrobial drugs</li>
-<li>Speed improvement for <code><a href="../reference/as.ab.html">as.ab()</a></code> when the input is an official name or ATC code</li>
-<li>Added argument <code>include_untested_rsi</code> to the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> functions (defaults to <code>TRUE</code> to keep existing behaviour), to be able to exclude rows where all R/SI values (class <code><rsi></code>, see <code><a href="../reference/as.rsi.html">as.rsi()</a></code>) are empty</li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-6-0">Other<a class="anchor" aria-label="anchor" href="#other-1-6-0"></a></h4>
-<ul><li>Big documentation updates</li>
-<li>Loading the package (i.e., <code><a href="https://msberends.github.io/AMR/">library(AMR)</a></code>) now is ~50 times faster than before, in costs of package size (which increased by ~3 MB)</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.5.0" id="amr-150">AMR 1.5.0<small>2021-01-06</small><a class="anchor" aria-label="anchor" href="#amr-150"></a></h2>
-<div class="section level4">
-<h4 id="new-1-5-0">New<a class="anchor" aria-label="anchor" href="#new-1-5-0"></a></h4>
-<ul><li>
-<p>Functions <code><a href="../reference/get_episode.html">get_episode()</a></code> and <code><a href="../reference/get_episode.html">is_new_episode()</a></code> to determine (patient) episodes which are not necessarily based on microorganisms. The <code><a href="../reference/get_episode.html">get_episode()</a></code> function returns the index number of the episode per group, while the <code><a href="../reference/get_episode.html">is_new_episode()</a></code> function returns values <code>TRUE</code>/<code>FALSE</code> to indicate whether an item in a vector is the start of a new episode. They also support <code>dplyr</code>s grouping (i.e. using <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code>):</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">patient_id</span>, <span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/get_episode.html">is_new_episode</a></span><span class="op">(</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li><p>Functions <code><a href="../reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><a href="../reference/mo_property.html">mo_is_gram_positive()</a></code> as wrappers around <code><a href="../reference/mo_property.html">mo_gramstain()</a></code>. They always return <code>TRUE</code> or <code>FALSE</code> (except when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>), thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p></li>
-<li><p>Function <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> to test for intrinsic resistance, based on EUCAST Intrinsic Resistance and Unusual Phenotypes v3.2 from 2020.</p></li>
-<li><p>Functions <code><a href="../reference/random.html">random_mic()</a></code>, <code><a href="../reference/random.html">random_disk()</a></code> and <code><a href="../reference/random.html">random_rsi()</a></code> for random value generation. The functions <code><a href="../reference/random.html">random_mic()</a></code> and <code><a href="../reference/random.html">random_disk()</a></code> take microorganism names and antibiotic names as input to make generation more realistic.</p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-1-5-0">Changed<a class="anchor" aria-label="anchor" href="#changed-1-5-0"></a></h4>
-<ul><li><p>New argument <code>ampc_cephalosporin_resistance</code> in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> to correct for AmpC de-repressed cephalosporin-resistant mutants</p></li>
-<li>
-<p>Interpretation of antimicrobial resistance - <code><a href="../reference/as.rsi.html">as.rsi()</a></code>:</p>
-<ul><li>Reference data used for <code><a href="../reference/as.rsi.html">as.rsi()</a></code> can now be set by the user, using the <code>reference_data</code> argument. This allows for using own interpretation guidelines. The user-set data must have the same structure as <code>rsi_translation</code>.</li>
-<li>Better determination of disk zones and MIC values when running <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on a data.frame</li>
-<li>Fix for using <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on a data.frame in older R versions</li>
-<li>
-<code><a href="../reference/as.rsi.html">as.rsi()</a></code> on a data.frame will not print a message anymore if the values are already clean R/SI values</li>
-<li>If using <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on MICs or disk diffusion while there is intrinsic antimicrobial resistance, a warning will be thrown to remind about this</li>
-<li>Fix for using <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on a <code>data.frame</code> that only contains one column for antibiotic interpretations</li>
-</ul></li>
-<li>
-<p>Some functions are now context-aware when used inside <code>dplyr</code> verbs, such as <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>. This means that then the data argument does not need to be set anymore. This is the case for the new functions:</p>
-<ul><li><code><a href="../reference/mo_property.html">mo_is_gram_negative()</a></code></li>
-<li><code><a href="../reference/mo_property.html">mo_is_gram_positive()</a></code></li>
-<li><code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code></li>
-</ul><p>… and for the existing functions:</p>
-<ul><li>
-<code><a href="../reference/first_isolate.html">first_isolate()</a></code>,</li>
-<li>
-<code>key_antibiotics()</code>,</li>
-<li>
-<code><a href="../reference/mdro.html">mdro()</a></code>,</li>
-<li>
-<code><a href="../reference/mdro.html">brmo()</a></code>,</li>
-<li>
-<code><a href="../reference/mdro.html">mrgn()</a></code>,</li>
-<li>
-<code><a href="../reference/mdro.html">mdr_tb()</a></code>,</li>
-<li>
-<code><a href="../reference/mdro.html">mdr_cmi2012()</a></code>,</li>
-<li><code><a href="../reference/mdro.html">eucast_exceptional_phenotypes()</a></code></li>
-</ul><div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># to select first isolates that are Gram-negative </span></span>
-<span><span class="co"># and view results of cephalosporins and aminoglycosides:</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">mo</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">cephalosporins</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://tibble.tidyverse.org/reference/as_tibble.html" class="external-link">as_tibble</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li>
-<p>For antibiotic selection functions (such as <code><a href="../reference/antibiotic_class_selectors.html">cephalosporins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code>) to select columns based on a certain antibiotic group, the dependency on the <code>tidyselect</code> package was removed, meaning that they can now also be used without the need to have this package installed and now also work in base R function calls (they rely on R 3.2 or later):</p>
-<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># above example in base R:</span></span>
-<span><span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&</span> <span class="fu"><a href="../reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>,</span>
-<span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mo"</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">cephalosporins</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">]</span></span></code></pre></div>
-</li>
-<li><p>For all function arguments in the code, it is now defined what the exact type of user input should be (inspired by the <a href="https://github.com/moodymudskipper/typed" class="external-link"><code>typed</code></a> package). If the user input for a certain function does not meet the requirements for a specific argument (such as the class or length), an informative error will be thrown. This makes the package more robust and the use of it more reproducible and reliable. In total, more than 420 arguments were defined.</p></li>
-<li><p>Fix for <code><a href="../reference/mo_source.html">set_mo_source()</a></code>, that previously would not remember the file location of the original file</p></li>
-<li><p>Deprecated function <code>p_symbol()</code> that not really fits the scope of this package. It will be removed in a future version. See <a href="https://github.com/msberends/AMR/blob/v1.4.0/R/p_symbol.R" class="external-link">here</a> for the source code to preserve it.</p></li>
-<li><p>Updated coagulase-negative staphylococci determination with Becker <em>et al.</em> 2020 (PMID 32056452), meaning that the species <em>S. argensis</em>, <em>S. caeli</em>, <em>S. debuckii</em>, <em>S. edaphicus</em> and <em>S. pseudoxylosus</em> are now all considered CoNS</p></li>
-<li><p>Fix for using argument <code>reference_df</code> in <code><a href="../reference/as.mo.html">as.mo()</a></code> and <code>mo_*()</code> functions that contain old microbial codes (from previous package versions)</p></li>
-<li><p>Fixed a bug where <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code> would not return the results based on the MO matching score</p></li>
-<li><p>Fixed a bug where <code><a href="../reference/as.mo.html">as.mo()</a></code> would not return results for known laboratory codes for microorganisms</p></li>
-<li><p>Fixed a bug where <code><a href="../reference/as.ab.html">as.ab()</a></code> would sometimes fail</p></li>
-<li><p>Better tibble printing for MIC values</p></li>
-<li><p>Fix for plotting MIC values with <code><a href="../reference/plot.html">plot()</a></code></p></li>
-<li><p>Added <code><a href="../reference/plot.html">plot()</a></code> generic to class <code><disk></code></p></li>
-<li><p>LA-MRSA and CA-MRSA are now recognised as an abbreviation for <em>Staphylococcus aureus</em>, meaning that e.g. <code>mo_genus("LA-MRSA")</code> will return <code>"Staphylococcus"</code> and <code>mo_is_gram_positive("LA-MRSA")</code> will return <code>TRUE</code>.</p></li>
-<li><p>Fix for printing class <mo> in tibbles when all values are <code>NA</code></mo></p></li>
-<li><p>Fix for <code><a href="../reference/mo_property.html">mo_shortname()</a></code> when the input contains <code>NA</code></p></li>
-<li><p>If <code><a href="../reference/as.mo.html">as.mo()</a></code> takes more than 30 seconds, some suggestions will be done to improve speed</p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-5-0">Other<a class="anchor" aria-label="anchor" href="#other-1-5-0"></a></h4>
-<ul><li>All messages and warnings thrown by this package now break sentences on whole words</li>
-<li>More extensive unit tests</li>
-<li>Internal calls to <code><a href="https://rdrr.io/r/base/options.html" class="external-link">options()</a></code> were all removed in favour of a new internal environment <code>pkg_env</code>
-</li>
-<li>Improved internal type setting (among other things: replaced all <code><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply()</a></code> calls with <code><a href="https://rdrr.io/r/base/lapply.html" class="external-link">vapply()</a></code>)</li>
-<li>Added CodeFactor as a continuous code review to this package: <a href="https://www.codefactor.io/repository/github/msberends/amr/" class="external-link uri">https://www.codefactor.io/repository/github/msberends/amr/</a>
-</li>
-<li>Added Dr. Rogier Schade as contributor</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.4.0" id="amr-140">AMR 1.4.0<small>2020-10-08</small><a class="anchor" aria-label="anchor" href="#amr-140"></a></h2>
-<div class="section level4">
-<h4 id="new-1-4-0">New<a class="anchor" aria-label="anchor" href="#new-1-4-0"></a></h4>
-<ul><li><p>Support for ‘EUCAST Expert Rules’ / ‘EUCAST Intrinsic Resistance and Unusual Phenotypes’ version 3.2 of May 2020. With this addition to the previously implemented version 3.1 of 2016, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function can now correct for more than 180 different antibiotics and the <code><a href="../reference/mdro.html">mdro()</a></code> function can determine multidrug resistance based on more than 150 different antibiotics. All previously implemented versions of the EUCAST rules are now maintained and kept available in this package. The <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function consequently gained the arguments <code>version_breakpoints</code> (at the moment defaults to v10.0, 2020) and <code>version_expertrules</code> (at the moment defaults to v3.2, 2020). The <code>example_isolates</code> data set now also reflects the change from v3.1 to v3.2. The <code><a href="../reference/mdro.html">mdro()</a></code> function now accepts <code>guideline == "EUCAST3.1"</code> and <code>guideline == "EUCAST3.2"</code>.</p></li>
-<li><p>A new vignette and website page with info about all our public and freely available data sets, that can be downloaded as flat files or in formats for use in R, SPSS, SAS, Stata and Excel: <a href="https://msberends.github.io/AMR/articles/datasets.html" class="uri">https://msberends.github.io/AMR/articles/datasets.html</a></p></li>
-<li>
-<p>Data set <code>intrinsic_resistant</code>. This data set contains all bug-drug combinations where the ‘bug’ is intrinsic resistant to the ‘drug’ according to the latest EUCAST insights. It contains just two columns: <code>microorganism</code> and <code>antibiotic</code>.</p>
-<p>Curious about which enterococci are actually intrinsic resistant to vancomycin?</p>
-<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span><span class="va">intrinsic_resistant</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">antibiotic</span> <span class="op">==</span> <span class="st">"Vancomycin"</span>, <span class="va">microorganism</span> <span class="op"><a href="../reference/like.html">%like%</a></span> <span class="st">"Enterococcus"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">microorganism</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "Enterococcus casseliflavus" "Enterococcus gallinarum" </span></span></code></pre></div>
-</li>
-<li><p>Support for veterinary ATC codes</p></li>
-<li><p>Support for skimming classes <code><rsi></code>, <code><mic></code>, <code><disk></code> and <code><mo></code> with the <code>skimr</code> package</p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-1-4-0">Changed<a class="anchor" aria-label="anchor" href="#changed-1-4-0"></a></h4>
-<ul><li><p>Although advertised that this package should work under R 3.0.0, we still had a dependency on R 3.6.0. This is fixed, meaning that our package should now work under R 3.0.0.</p></li>
-<li>
-<p>Improvements for <code><a href="../reference/as.rsi.html">as.rsi()</a></code>:</p>
-<ul><li>
-<p>Support for using <code>dplyr</code>’s <code><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across()</a></code> to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.</p>
-<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># until dplyr 1.0.0</span></span>
-<span><span class="va">your_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="va">is.mic</span>, <span class="va">as.rsi</span><span class="op">)</span></span>
-<span><span class="va">your_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="va">is.disk</span>, <span class="va">as.rsi</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># since dplyr 1.0.0</span></span>
-<span><span class="va">your_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu">where</span><span class="op">(</span><span class="va">is.mic</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="va">your_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu">where</span><span class="op">(</span><span class="va">is.disk</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li><p>Cleaning columns in a data.frame now allows you to specify those columns with tidy selection, e.g. <code>as.rsi(df, col1:col9)</code></p></li>
-<li><p>Big speed improvement for interpreting MIC values and disk zone diameters. When interpreting 5,000 MIC values of two antibiotics (10,000 values in total), our benchmarks showed a total run time going from 80.7-85.1 seconds to 1.8-2.0 seconds.</p></li>
-<li><p>Added argument ‘add_intrinsic_resistance’ (defaults to <code>FALSE</code>), that considers intrinsic resistance according to EUCAST</p></li>
-<li><p>Fixed a bug where in EUCAST rules the breakpoint for R would be interpreted as “>=” while this should have been “<”</p></li>
-</ul></li>
-<li>
-<p>Added intelligent data cleaning to <code><a href="../reference/as.disk.html">as.disk()</a></code>, so numbers can also be extracted from text and decimal numbers will always be rounded up:</p>
-<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/as.disk.html">as.disk</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"disk zone: 23.4 mm"</span>, <span class="fl">23.4</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#> Class <disk></span></span>
-<span><span class="co">#> [1] 24 24</span></span></code></pre></div>
-</li>
-<li>
-<p>Improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code>:</p>
-<ul><li>A completely new matching score for ambiguous user input, using <code><a href="../reference/mo_matching_score.html">mo_matching_score()</a></code>. Any user input value that could mean more than one taxonomic entry is now considered ‘uncertain’. Instead of a warning, a message will be thrown and the accompanying <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code> has been changed completely; it now prints all possible candidates with their matching score.</li>
-<li>Big speed improvement for already valid microorganism ID. This also means an significant speed improvement for using <code>mo_*</code> functions like <code><a href="../reference/mo_property.html">mo_name()</a></code> on microoganism IDs.</li>
-<li>Added argument <code>ignore_pattern</code> to <code><a href="../reference/as.mo.html">as.mo()</a></code> which can also be given to <code>mo_*</code> functions like <code><a href="../reference/mo_property.html">mo_name()</a></code>, to exclude known non-relevant input from analysing. This can also be set with the option <code>AMR_ignore_pattern</code>.</li>
-</ul></li>
-<li><p><code>get_locale()</code> now uses at default <code>Sys.getenv("LANG")</code> or, if <code>LANG</code> is not set, <code><a href="https://rdrr.io/r/base/locales.html" class="external-link">Sys.getlocale()</a></code>. This can be overwritten by setting the option <code>AMR_locale</code>.</p></li>
-<li><p>Big speed improvement for <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code></p></li>
-<li><p>Overall speed improvement by tweaking joining functions</p></li>
-<li><p>Function <code><a href="../reference/mo_property.html">mo_shortname()</a></code> now returns the genus for input where the species is unknown</p></li>
-<li><p>BORSA is now recognised as an abbreviation for <em>Staphylococcus aureus</em>, meaning that e.g. <code>mo_genus("BORSA")</code> will return “Staphylococcus”</p></li>
-<li><p>Added a feature from AMR 1.1.0 and earlier again, but now without other package dependencies: <code>tibble</code> printing support for classes <code><rsi></code>, <code><mic></code>, <code><disk></code>, <code><ab></code> and <code><mo></code>. When using <code>tibble</code>s containing antimicrobial columns (class <code><rsi></code>), “S” will print in green, “I” will print in yellow and “R” will print in red. Microbial IDs (class <code><mo></code>) will emphasise on the genus and species, not on the kingdom.</p></li>
-<li><p>Names of antiviral agents in data set <code>antivirals</code> now have a starting capital letter, like it is the case in the <code>antibiotics</code> data set</p></li>
-<li><p>Updated the documentation of the <code>WHONET</code> data set to clarify that all patient names are fictitious</p></li>
-<li><p>Small <code><a href="../reference/as.ab.html">as.ab()</a></code> algorithm improvements</p></li>
-<li><p>Fix for combining MIC values with raw numbers, i.e. <code>c(as.mic(2), 2)</code> previously failed but now returns a valid MIC class</p></li>
-<li><p><code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> and <code><a href="../reference/ggplot_rsi.html">geom_rsi()</a></code> gained arguments <code>minimum</code> and <code>language</code>, to influence the internal use of <code><a href="../reference/proportion.html">rsi_df()</a></code></p></li>
-<li>
-<p>Changes in the <code>antibiotics</code> data set:</p>
-<ul><li>Updated oral and parental DDDs from the WHOCC</li>
-<li>Added abbreviation “piptazo” to ‘Piperacillin/tazobactam’ (TZP)</li>
-<li>‘Penicillin G’ (for intravenous use) is now named ‘Benzylpenicillin’ (code <code>PEN</code>)</li>
-<li>‘Penicillin V’ (for oral use, code <code>PNV</code>) was removed, since its actual entry ‘Phenoxymethylpenicillin’ (code <code>PHN</code>) already existed</li>
-<li>The group name (<code>antibiotics$group</code>) of ‘Linezolid’ (<code>LNZ</code>), ‘Cycloserine’ (<code>CYC</code>), ‘Tedizolid’ (<code>TZD</code>) and ‘Thiacetazone’ (<code>THA</code>) is now “Oxazolidinones” instead of “Other antibacterials”</li>
-</ul></li>
-<li><p>Added support for using <code><a href="https://rdrr.io/r/base/unique.html" class="external-link">unique()</a></code> on classes <code><rsi></code>, <code><mic></code>, <code><disk></code>, <code><ab></code> and <code><mo></code></p></li>
-<li><p>Added argument <code>excess</code> to the <code><a href="../reference/kurtosis.html">kurtosis()</a></code> function (defaults to <code>FALSE</code>), to return the <em>excess kurtosis</em>, defined as the kurtosis minus three.</p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-4-0">Other<a class="anchor" aria-label="anchor" href="#other-1-4-0"></a></h4>
-<ul><li>Removed functions <code>portion_R()</code>, <code>portion_S()</code> and <code>portion_I()</code> that were deprecated since version 0.9.0 (November 2019) and were replaced with <code><a href="../reference/proportion.html">proportion_R()</a></code>, <code><a href="../reference/proportion.html">proportion_S()</a></code> and <code><a href="../reference/proportion.html">proportion_I()</a></code>
-</li>
-<li>Removed unnecessary references to the <code>base</code> package</li>
-<li>Added packages that could be useful for some functions to the <code>Suggests</code> field of the <code>DESCRIPTION</code> file</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.3.0" id="amr-130">AMR 1.3.0<small>2020-07-31</small><a class="anchor" aria-label="anchor" href="#amr-130"></a></h2>
-<div class="section level4">
-<h4 id="new-1-3-0">New<a class="anchor" aria-label="anchor" href="#new-1-3-0"></a></h4>
-<ul><li><p>Function <code><a href="../reference/ab_from_text.html">ab_from_text()</a></code> to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses <code><a href="../reference/as.ab.html">as.ab()</a></code> internally</p></li>
-<li>
-<p><a href="https://tidyselect.r-lib.org/reference/language.html" class="external-link">Tidyverse selection helpers</a> for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like <code><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">dplyr::select()</a></code> and <code><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html" class="external-link">tidyr::pivot_longer()</a></code>:</p>
-<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># Columns 'IPM' and 'MEM' are in the example_isolates data set</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#> Selecting carbapenems: `IPM` (imipenem), `MEM` (meropenem)</span></span></code></pre></div>
-</li>
-<li><p>Added <code><a href="../reference/mo_property.html">mo_domain()</a></code> as an alias to <code><a href="../reference/mo_property.html">mo_kingdom()</a></code></p></li>
-<li><p>Added function <code>filter_penicillins()</code> to filter isolates on a specific result in any column with a name in the antimicrobial ‘penicillins’ class (more specific: ATC subgroup <em>Beta-lactam antibacterials, penicillins</em>)</p></li>
-<li><p>Added official antimicrobial names to all <code>filter_ab_class()</code> functions, such as <code>filter_aminoglycosides()</code></p></li>
-<li><p>Added antibiotics code “FOX1” for cefoxitin screening (abbreviation “cfsc”) to the <code>antibiotics</code> data set</p></li>
-<li><p>Added Monuril as trade name for fosfomycin</p></li>
-<li><p>Added argument <code>conserve_capped_values</code> to <code><a href="../reference/as.rsi.html">as.rsi()</a></code> for interpreting MIC values - it makes sure that values starting with “<” (but not “<=”) will always return “S” and values starting with “>” (but not “>=”) will always return “R”. The default behaviour of <code><a href="../reference/as.rsi.html">as.rsi()</a></code> has not changed, so you need to specifically do <code>as.rsi(..., conserve_capped_values = TRUE)</code>.</p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-1-3-0">Changed<a class="anchor" aria-label="anchor" href="#changed-1-3-0"></a></h4>
-<ul><li>
-<p>Big speed improvement for using any function on microorganism codes from earlier package versions (prior to <code>AMR</code> v1.2.0), such as <code><a href="../reference/as.mo.html">as.mo()</a></code>, <code><a href="../reference/mo_property.html">mo_name()</a></code>, <code><a href="../reference/first_isolate.html">first_isolate()</a></code>, <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>, <code><a href="../reference/mdro.html">mdro()</a></code>, etc.</p>
-<p>As a consequence, very old microbial codes (from <code>AMR</code> v0.5.0 and lower) <strong>are not supported anymore</strong>. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> on your microorganism names or codes to transform them to current abbreviations used in this package.</p>
-</li>
-<li>
-<p>Improvements for <code><a href="../reference/proportion.html">susceptibility()</a></code> and <code><a href="../reference/proportion.html">resistance()</a></code> and all <code>count_*()</code>, <code>proportion_*()</code> functions:</p>
-<ul><li>95% speed improvement by using other base R functions for calculation</li>
-<li>Using unexisting columns wil now return an error instead of dropping them silently</li>
-<li>Using variables for column names (as well as selectors like <code><a href="https://tidyselect.r-lib.org/reference/all_of.html" class="external-link">dplyr::all_of()</a></code>) now works again</li>
-</ul></li>
-<li>
-<p>Improvements for <code><a href="../reference/as.ab.html">as.ab()</a></code>:</p>
-<ul><li>Dramatic improvement of the algorithm behind <code><a href="../reference/as.ab.html">as.ab()</a></code>, making many more input errors translatable, such as digitalised health care records, using too few or too many vowels or consonants and many more</li>
-<li>Added progress bar</li>
-<li>Fixed a bug where <code><a href="../reference/as.ab.html">as.ab()</a></code> would return an error on invalid input values</li>
-<li>The <code><a href="../reference/as.ab.html">as.ab()</a></code> function will now throw a note if more than 1 antimicrobial drug could be retrieved from a single input value.</li>
-</ul></li>
-<li><p>Fixed a bug where <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> would not work on a tibble when the <code>tibble</code> or <code>dplyr</code> package was loaded</p></li>
-<li><p>Fixed a bug for CLSI 2019 guidelines (using <code><a href="../reference/as.rsi.html">as.rsi()</a></code>), that also included results for animals. It now only contains interpretation guidelines for humans.</p></li>
-<li><p>All <code>*_join_microorganisms()</code> functions and <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> now return the original data class (e.g. <code>tibble</code>s and <code>data.table</code>s)</p></li>
-<li>
-<p>For functions <code><a href="../reference/proportion.html">rsi_df()</a></code>, <code><a href="../reference/proportion.html">proportion_df()</a></code> and <code><a href="../reference/count.html">count_df()</a></code>:</p>
-<ul><li>Fixed a bug for using grouped versions</li>
-<li>Fixed a bug where not all different antimicrobial results were added as rows</li>
-<li>Fixed a bug when only calculating counts (<code><a href="../reference/count.html">count_df()</a></code>) when all antibiotics in the data set have only <code>NA</code>s</li>
-</ul></li>
-<li><p>Improved auto-determination for columns of types <code><mo></code> and <code><Date></code></p></li>
-<li><p>Fixed a bug in <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> for when only one antibiotic was in the input data</p></li>
-<li><p>Changed the summary for class <code><rsi></code>, to highlight the %SI vs. %R</p></li>
-<li><p>Improved error handling, giving more useful info when functions return an error</p></li>
-<li><p>Any progress bar will now only show in interactive mode (i.e. not in R Markdown)</p></li>
-<li><p>Speed improvement for <code><a href="../reference/mdro.html">mdro()</a></code> and <code>filter_ab_class()</code></p></li>
-<li><p>New option <code>arrows_textangled</code> for <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> to indicate whether the text at the end of the arrows should be angled (defaults to <code>TRUE</code>, as it was in previous versions)</p></li>
-<li><p>Added parenteral DDD to benzylpenicillin</p></li>
-<li><p>Fixed a bug where <code><a href="../reference/as.mic.html">as.mic()</a></code> could not handle dots without a leading zero (like <code>"<=.25</code>)</p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-3-0">Other<a class="anchor" aria-label="anchor" href="#other-1-3-0"></a></h4>
-<ul><li>Moved primary location of this project from GitLab to <a href="https://github.com/msberends/AMR" class="external-link">GitHub</a>, giving us native support for automated syntax checking without being dependent on external services such as AppVeyor and Travis CI.</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.2.0" id="amr-120">AMR 1.2.0<small>2020-05-28</small><a class="anchor" aria-label="anchor" href="#amr-120"></a></h2>
-<div class="section level4">
-<h4 id="breaking-1-2-0">Breaking<a class="anchor" aria-label="anchor" href="#breaking-1-2-0"></a></h4>
-<ul><li>
-<p>Removed code dependency on all other R packages, making this package fully independent of the development process of others. This is a major code change, but will probably not be noticeable by most users.</p>
-<p>Making this package independent of especially the tidyverse (e.g. packages <code>dplyr</code> and <code>tidyr</code>) tremendously increases sustainability on the long term, since tidyverse functions change quite often. Good for users, but hard for package maintainers. Most of our functions are replaced with versions that only rely on base R, which keeps this package fully functional for many years to come, without requiring a lot of maintenance to keep up with other packages anymore. Another upside it that this package can now be used with all versions of R since R-3.0.0 (April 2013). Our package is being used in settings where the resources are very limited. Fewer dependencies on newer software is helpful for such settings.</p>
-<p>Negative effects of this change are:</p>
-<ul><li>Function <code>freq()</code> that was borrowed from the <code>cleaner</code> package was removed. Use <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">cleaner::freq()</a></code>, or run <code><a href="https://github.com/msberends/cleaner" class="external-link">library("cleaner")</a></code> before you use <code>freq()</code>.</li>
-<li><del>Printing values of class <code>mo</code> or <code>rsi</code> in a tibble will no longer be in colour and printing <code>rsi</code> in a tibble will show the class <code><ord></code>, not <code><rsi></code> anymore. This is purely a visual effect.</del></li>
-<li><del>All functions from the <code>mo_*</code> family (like <code><a href="../reference/mo_property.html">mo_name()</a></code> and <code><a href="../reference/mo_property.html">mo_gramstain()</a></code>) are noticeably slower when running on hundreds of thousands of rows.</del></li>
-<li>For developers: classes <code>mo</code> and <code>ab</code> now both also inherit class <code>character</code>, to support any data transformation. This change invalidates code that checks for class length == 1.</li>
-</ul></li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-1-2-0">Changed<a class="anchor" aria-label="anchor" href="#changed-1-2-0"></a></h4>
-<ul><li>Taxonomy:
-<ul><li>Updated the taxonomy of microorganisms to May 2020, using the Catalogue of Life (CoL), the Global Biodiversity Information Facility (GBIF) and the List of Prokaryotic names with Standing in Nomenclature (LPSN, hosted by DSMZ since February 2020). <strong>Note:</strong> a taxonomic update may always impact determination of first isolates (using <code><a href="../reference/first_isolate.html">first_isolate()</a></code>), since some bacterial names might be renamed to other genera or other (sub)species. This is expected behaviour.</li>
-<li>Removed the Catalogue of Life IDs (like 776351), since they now work with a species ID (hexadecimal string)</li>
-</ul></li>
-<li>EUCAST rules:
-<ul><li>The <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function no longer applies “other” rules at default that are made available by this package (like setting ampicillin = R when ampicillin + enzyme inhibitor = R). The default input value for <code>rules</code> is now <code>c("breakpoints", "expert")</code> instead of <code>"all"</code>, but this can be changed by the user. To return to the old behaviour, set <code>options(AMR.eucast_rules = "all")</code>.</li>
-<li>Fixed a bug where checking antimicrobial results in the original data were not regarded as valid R/SI values</li>
-<li>All “other” rules now apply for all drug combinations in the <code>antibiotics</code> data set these two rules:
-<ol style="list-style-type: decimal"><li>A drug <strong>with</strong> enzyme inhibitor will be set to S if the drug <strong>without</strong> enzyme inhibitor is S</li>
-<li>A drug <strong>without</strong> enzyme inhibitor will be set to R if the drug <strong>with</strong> enzyme inhibitor is R</li>
-</ol>
-This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/avibactam, trimethoprim/sulfamethoxazole, etc.</li>
-<li>Added official drug names to verbose output of <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
-</li>
-</ul></li>
-<li>Added function <code><a href="../reference/ab_property.html">ab_url()</a></code> to return the direct URL of an antimicrobial agent from the official WHO website</li>
-<li>Improvements for algorithm in <code><a href="../reference/as.ab.html">as.ab()</a></code>, so that e.g. <code>as.ab("ampi sul")</code> and <code>ab_name("ampi sul")</code> work</li>
-<li>Functions <code><a href="../reference/ab_property.html">ab_atc()</a></code> and <code><a href="../reference/ab_property.html">ab_group()</a></code> now return <code>NA</code> if no antimicrobial agent could be found</li>
-<li>Small fix for some text input that could not be coerced as valid MIC values</li>
-<li>Fix for interpretation of generic CLSI interpretation rules (thanks to Anthony Underwood)</li>
-<li>Fix for <code><a href="../reference/mo_source.html">set_mo_source()</a></code> to make sure that column <code>mo</code> will always be the second column</li>
-<li>Added abbreviation “cfsc” for Cefoxitin and “cfav” for Ceftazidime/avibactam</li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-2-0">Other<a class="anchor" aria-label="anchor" href="#other-1-2-0"></a></h4>
-<ul><li>Removed previously deprecated function <code>p.symbol()</code> - it was replaced with <code>p_symbol()</code>
-</li>
-<li>Removed function <code>read.4d()</code>, that was only useful for reading data from an old test database.</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.1.0" id="amr-110">AMR 1.1.0<small>2020-04-15</small><a class="anchor" aria-label="anchor" href="#amr-110"></a></h2>
-<div class="section level4">
-<h4 id="new-1-1-0">New<a class="anchor" aria-label="anchor" href="#new-1-1-0"></a></h4>
-<ul><li>Support for easy principal component analysis for AMR, using the new <code><a href="../reference/pca.html">pca()</a></code> function</li>
-<li>Plotting biplots for principal component analysis using the new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function</li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-1-1-0">Changed<a class="anchor" aria-label="anchor" href="#changed-1-1-0"></a></h4>
-<ul><li>Improvements for the algorithm used by <code><a href="../reference/as.mo.html">as.mo()</a></code> (and consequently all <code>mo_*</code> functions, that use <code><a href="../reference/as.mo.html">as.mo()</a></code> internally):
-<ul><li>Support for codes ending with <code>SPE</code> for species, like <code>"ESCSPE"</code> for <em>Escherichia coli</em>
-</li>
-<li>Support for any encoding, which means that any language-specific character with accents can be used for input</li>
-<li>Support for more arbitrary IDs used in laboratory information systems</li>
-<li>Small fix for preventing viruses being treated as bacteria</li>
-<li>Small fix for preventing contamination and lack of growth being treated as valid microorganisms</li>
-</ul></li>
-<li>Support for all abbreviations of antibiotics and antimycotics used by the Netherlands National Institute for Public Health and the Environment (Rijksinstituut voor Volksgezondheid en Milieu; RIVM)</li>
-<li>Added more abbreviations to the <code>antibiotics</code> data set</li>
-<li>Reloaded original EUCAST master tables from 2019 (2020 was already available). This seems more reliable than the data we used from WHONET.</li>
-<li>Added generic CLSI rules for R/SI interpretation using <code><a href="../reference/as.rsi.html">as.rsi()</a></code> for years 2010-2019 (thanks to Anthony Underwood)</li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-1-0">Other<a class="anchor" aria-label="anchor" href="#other-1-1-0"></a></h4>
-<ul><li>Support for the upcoming <code>dplyr</code> version 1.0.0</li>
-<li>More robust assigning for classes <code>rsi</code> and <code>mic</code>
-</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.0.1" id="amr-101">AMR 1.0.1<small>2020-02-23</small><a class="anchor" aria-label="anchor" href="#amr-101"></a></h2>
-<div class="section level4">
-<h4 id="changed-1-0-1">Changed<a class="anchor" aria-label="anchor" href="#changed-1-0-1"></a></h4>
-<ul><li><p>Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline</p></li>
-<li>
-<p>Interpretation from MIC values (and disk zones) to R/SI can now be used with <code><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at()</a></code> of the <code>dplyr</code> package:</p>
-<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">yourdata</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">antibiotic1</span><span class="op">:</span><span class="va">antibiotic25</span><span class="op">)</span>, <span class="va">as.rsi</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span><span class="op">)</span></span>
-<span></span>
-<span><span class="va">yourdata</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">antibiotic1</span><span class="op">:</span><span class="va">antibiotic25</span><span class="op">)</span>, <span class="va">as.rsi</span>, mo <span class="op">=</span> <span class="va">.</span><span class="op">$</span><span class="va">mybacteria</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li><p>Added antibiotic abbreviations for a laboratory manufacturer (GLIMS) for cefuroxime, cefotaxime, ceftazidime, cefepime, cefoxitin and trimethoprim/sulfamethoxazole</p></li>
-<li><p>Added <code>uti</code> (as abbreviation of urinary tract infections) as argument to <code><a href="../reference/as.rsi.html">as.rsi()</a></code>, so interpretation of MIC values and disk zones can be made dependent on isolates specifically from UTIs</p></li>
-<li><p>Info printing in functions <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>, <code><a href="../reference/first_isolate.html">first_isolate()</a></code>, <code><a href="../reference/mdro.html">mdro()</a></code> and <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code> will now at default only print when R is in an interactive mode (i.e. not in RMarkdown)</p></li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="1.0.0" id="amr-100">AMR 1.0.0<small>2020-02-17</small><a class="anchor" aria-label="anchor" href="#amr-100"></a></h2>
-<p>This software is now out of beta and considered stable. Nonetheless, this package will be developed continually.</p>
-<div class="section level4">
-<h4 id="new-1-0-0">New<a class="anchor" aria-label="anchor" href="#new-1-0-0"></a></h4>
-<ul><li>Support for the newest <a href="https://www.eucast.org/clinical_breakpoints/" class="external-link">EUCAST Clinical Breakpoint Tables v.10.0</a>, valid from 1 January 2020. This affects translation of MIC and disk zones using <code><a href="../reference/as.rsi.html">as.rsi()</a></code> and inferred resistance and susceptibility using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>.</li>
-<li>The repository of this package now contains a clean version of the EUCAST and CLSI guidelines from 2011-2020 to translate MIC and disk diffusion values to R/SI: <a href="https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt" class="external-link uri">https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt</a>. This <strong>allows for machine reading these guidelines</strong>, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. This file used to process the EUCAST Clinical Breakpoints Excel file <a href="https://github.com/msberends/AMR/blob/main/data-raw/read_EUCAST.R" class="external-link">can be found here</a>.</li>
-<li>Support for LOINC and SNOMED codes
-<ul><li>
-<p>Support for LOINC codes in the <code>antibiotics</code> data set. Use <code><a href="../reference/ab_property.html">ab_loinc()</a></code> to retrieve LOINC codes, or use a LOINC code for input in any <code>ab_*</code> function:</p>
-<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/ab_property.html">ab_loinc</a></span><span class="op">(</span><span class="st">"ampicillin"</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "21066-6" "3355-5" "33562-0" "33919-2" "43883-8" "43884-6" "87604-5"</span></span>
-<span><span class="fu"><a href="../reference/ab_property.html">ab_name</a></span><span class="op">(</span><span class="st">"21066-6"</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "Ampicillin"</span></span>
-<span><span class="fu"><a href="../reference/ab_property.html">ab_atc</a></span><span class="op">(</span><span class="st">"21066-6"</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "J01CA01"</span></span></code></pre></div>
-</li>
-<li>
-<p>Support for SNOMED CT codes in the <code>microorganisms</code> data set. Use <code><a href="../reference/mo_property.html">mo_snomed()</a></code> to retrieve SNOMED codes, or use a SNOMED code for input in any <code>mo_*</code> function:</p>
-<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_snomed</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span></span>
-<span><span class="co">#> [1] 115329001 3092008 113961008</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="fl">115329001</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "Staphylococcus aureus"</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="fl">115329001</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "Gram-positive"</span></span></code></pre></div>
-</li>
-</ul></li>
-</ul></div>
-<div class="section level4">
-<h4 id="changes-1-0-0">Changes<a class="anchor" aria-label="anchor" href="#changes-1-0-0"></a></h4>
-<ul><li>The <code><a href="../reference/as.mo.html">as.mo()</a></code> function previously wrote to the package folder to improve calculation speed for previously calculated results. This is no longer the case, to comply with CRAN policies. Consequently, the function <code>clear_mo_history()</code> was removed.</li>
-<li>Bugfix for some WHONET microorganism codes that were not interpreted correctly when using <code><a href="../reference/as.rsi.html">as.rsi()</a></code>
-</li>
-<li>Improvements for the algorithm used by <code><a href="../reference/as.mo.html">as.mo()</a></code> (and consequently all <code>mo_*</code> functions, that use <code><a href="../reference/as.mo.html">as.mo()</a></code> internally):
-<ul><li>Support for missing spaces, e.g. in <code>as.mo("Methicillin-resistant S.aureus")</code>
-</li>
-<li>Better support for determination of <em>Salmonella</em> biovars</li>
-<li>Speed improvements, especially for the <em>G. species</em> format (G for genus), like <em>E. coli</em> and <em>K pneumoniae</em>
-</li>
-<li>Support for more common codes used in laboratory information systems</li>
-</ul></li>
-<li>Input values for <code><a href="../reference/as.disk.html">as.disk()</a></code> limited to a maximum of 50 millimeters</li>
-<li>Added a lifecycle state to every function, following the lifecycle circle of the <code>tidyverse</code>
-</li>
-<li>For in <code><a href="../reference/as.ab.html">as.ab()</a></code>: support for drugs starting with “co-” like co-amoxiclav, co-trimoxazole, co-trimazine and co-trimazole (thanks to Peter Dutey)</li>
-<li>Changes to the <code>antibiotics</code> data set (thanks to Peter Dutey):
-<ul><li>Added more synonyms to colistin, imipenem and piperacillin/tazobactam</li>
-<li>Moved synonyms Rifinah and Rimactazid from rifampicin (<code>RIF</code>) to rifampicin/isoniazid (<code>RFI</code>). Please note that <a href="https://www.whocc.no/atc_ddd_index/?code=J04AM02&showdescription=no" class="external-link">the combination rifampicin/isoniazid has no DDDs defined</a>, so e.g. <code>ab_ddd("Rimactazid")</code> will now return <code>NA</code>.</li>
-<li>Moved synonyms Bactrimel and Cotrimazole from sulfamethoxazole (<code>SMX</code>) to trimethoprim/sulfamethoxazole (<code>SXT</code>)</li>
-</ul></li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-1-0-0">Other<a class="anchor" aria-label="anchor" href="#other-1-0-0"></a></h4>
-<ul><li>Add a <code>CITATION</code> file</li>
-<li>Full support for the upcoming R 4.0</li>
-<li>Removed unnecessary <code>AMR::</code> calls</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.9.0" id="amr-090">AMR 0.9.0<small>2019-11-29</small><a class="anchor" aria-label="anchor" href="#amr-090"></a></h2>
-<div class="section level4">
-<h4 id="breaking-0-9-0">Breaking<a class="anchor" aria-label="anchor" href="#breaking-0-9-0"></a></h4>
-<ul><li>Adopted Adeolu <em>et al.</em> (2016), <a href="https:/pubmed.ncbi.nlm.nih.gov/27620848/">PMID 27620848</a> for the <code>microorganisms</code> data set, which means that the new order Enterobacterales now consists of a part of the existing family Enterobacteriaceae, but that this family has been split into other families as well (like <em>Morganellaceae</em> and <em>Yersiniaceae</em>). Although published in 2016, this information is not yet in the Catalogue of Life version of 2019. All MDRO determinations with <code><a href="../reference/mdro.html">mdro()</a></code> will now use the Enterobacterales order for all guidelines before 2016 that were dependent on the Enterobacteriaceae family.
-<ul><li>
-<p>If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:</p>
-<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="va">somebugs</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Enterobacteriaceae"</span><span class="op">)</span> <span class="va">...</span></span></code></pre></div>
-<p>then please adjust this to:</p>
-<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">somebugs</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Enterobacterales"</span><span class="op">)</span> <span class="va">...</span></span></code></pre></div>
-</li>
-</ul></li>
-</ul></div>
-<div class="section level4">
-<h4 id="new-0-9-0">New<a class="anchor" aria-label="anchor" href="#new-0-9-0"></a></h4>
-<ul><li>
-<p>Functions <code><a href="../reference/proportion.html">susceptibility()</a></code> and <code><a href="../reference/proportion.html">resistance()</a></code> as aliases of <code><a href="../reference/proportion.html">proportion_SI()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code>, respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.</p>
-<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>bug <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>amoxicillin <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span>,</span>
-<span> amox_clav <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMC</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">amoxicillin</span><span class="op">)</span> <span class="op">|</span> <span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">amox_clav</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li>
-<p>Support for a new MDRO guideline: Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.” Clinical Microbiology and Infection (2012).</p>
-<ul><li>This is now the new default guideline for the <code><a href="../reference/mdro.html">mdro()</a></code> function</li>
-<li>The new Verbose mode (<code>mdro(...., verbose = TRUE)</code>) returns an informative data set where the reason for MDRO determination is given for every isolate, and an list of the resistant antimicrobial agents</li>
-</ul></li>
-<li><p>Data set <code>antivirals</code>, containing all entries from the ATC J05 group with their DDDs for oral and parenteral treatment</p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="changes-0-9-0">Changes<a class="anchor" aria-label="anchor" href="#changes-0-9-0"></a></h4>
-<ul><li>Improvements to algorithm in <code><a href="../reference/as.mo.html">as.mo()</a></code>:
-<ul><li><p>Now allows “ou” where “au” should have been used and vice versa</p></li>
-<li><p>More intelligent way of coping with some consonants like “l” and “r”</p></li>
-<li>
-<p>Added a score (a certainty percentage) to <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code>, that is calculated using the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance" class="external-link">Levenshtein distance</a>:</p>
-<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Stafylococcus aureus"</span>,</span>
-<span> <span class="st">"staphylokok aureuz"</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#> Warning: </span></span>
-<span><span class="co">#> Results of two values were guessed with uncertainty. Use mo_uncertainties() to review them.</span></span>
-<span><span class="co">#> Class 'mo'</span></span>
-<span><span class="co">#> [1] B_STPHY_AURS B_STPHY_AURS</span></span>
-<span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">mo_uncertainties</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#> "Stafylococcus aureus" -> Staphylococcus aureus (B_STPHY_AURS, score: 95.2%)</span></span>
-<span><span class="co">#> "staphylokok aureuz" -> Staphylococcus aureus (B_STPHY_AURS, score: 85.7%)</span></span></code></pre></div>
-</li>
-</ul></li>
-<li>Removed previously deprecated function <code>as.atc()</code> - this function was replaced by <code><a href="../reference/ab_property.html">ab_atc()</a></code>
-</li>
-<li>Renamed all <code>portion_*</code> functions to <code>proportion_*</code>. All <code>portion_*</code> functions are still available as deprecated functions, and will return a warning when used.</li>
-<li>When running <code><a href="../reference/as.rsi.html">as.rsi()</a></code> over a data set, it will now print the guideline that will be used if it is not specified by the user</li>
-<li>Improvements for <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:
-<ul><li>Fix where <em>Stenotrophomonas maltophilia</em> would always become ceftazidime R (following EUCAST v3.1)</li>
-<li>Fix where <em>Leuconostoc</em> and <em>Pediococcus</em> would not always become glycopeptides R</li>
-<li>non-EUCAST rules in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> are now applied first and not as last anymore. This is to improve the dependency on certain antibiotics for the official EUCAST rules. Please see <code><a href="../reference/eucast_rules.html">?eucast_rules</a></code>.</li>
-</ul></li>
-<li>Fix for interpreting MIC values with <code><a href="../reference/as.rsi.html">as.rsi()</a></code> where the input is <code>NA</code>
-</li>
-<li>Added “imi” and “imp” as allowed abbreviation for Imipenem (IPM)</li>
-<li>Fix for automatically determining columns with antibiotic results in <code><a href="../reference/mdro.html">mdro()</a></code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
-</li>
-<li>Added ATC codes for ceftaroline, ceftobiprole and faropenem and fixed two typos in the <code>antibiotics</code> data set</li>
-<li>More robust way of determining valid MIC values</li>
-<li>Small changed to the <code>example_isolates</code> data set to better reflect reality</li>
-<li>Added more microorganisms codes from laboratory systems (esp. species of <em>Pseudescherichia</em> and <em>Rodentibacter</em>)</li>
-<li>Added Gram-stain to <code><a href="../reference/mo_property.html">mo_info()</a></code>
-</li>
-</ul></div>
-<div class="section level4">
-<h4 id="other-0-9-0">Other<a class="anchor" aria-label="anchor" href="#other-0-9-0"></a></h4>
-<ul><li>Rewrote the complete documentation to markdown format, to be able to use the very latest version of the great <a href="https://roxygen2.r-lib.org/index.html" class="external-link">Roxygen2</a>, released in November 2019. This tremously improved the documentation quality, since the rewrite forced us to go over all texts again and make changes where needed.</li>
-<li>Change dependency on <code>clean</code> to <code>cleaner</code>, as this package was renamed accordingly upon CRAN request</li>
-<li>Added Dr. Sofia Ny as contributor</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.8.0" id="amr-080">AMR 0.8.0<small>2019-10-15</small><a class="anchor" aria-label="anchor" href="#amr-080"></a></h2>
-<div class="section level4">
-<h4 id="breaking-0-8-0">Breaking<a class="anchor" aria-label="anchor" href="#breaking-0-8-0"></a></h4>
-<ul><li>
-<p>Determination of first isolates now <strong>excludes</strong> all ‘unknown’ microorganisms at default, i.e. microbial code <code>"UNKNOWN"</code>. They can be included with the new argument <code>include_unknown</code>:</p>
-<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="va">...</span>, include_unknown <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
-<p>For WHONET users, this means that all records/isolates with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default, since <code>as.mo("con") = "UNKNOWN"</code>. The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.</p>
-</li>
-<li>
-<p>For code consistency, classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in <code>NA</code>:</p>
-<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># how it works in base R:</span></span>
-<span><span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a></span><span class="op">(</span><span class="st">"A"</span><span class="op">)</span></span>
-<span><span class="va">x</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span> <span class="op"><-</span> <span class="st">"B"</span></span>
-<span><span class="co">#> Warning message:</span></span>
-<span><span class="co">#> invalid factor level, NA generated</span></span>
-<span></span>
-<span><span class="co"># how it now works similarly for classes 'mo' and 'ab':</span></span>
-<span><span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span></span>
-<span><span class="va">x</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span> <span class="op"><-</span> <span class="st">"testvalue"</span></span>
-<span><span class="co">#> Warning message:</span></span>
-<span><span class="co">#> invalid microorganism code, NA generated</span></span></code></pre></div>
-<p>This is important, because a value like <code>"testvalue"</code> could never be understood by e.g. <code><a href="../reference/mo_property.html">mo_name()</a></code>, although the class would suggest a valid microbial code.</p>
-</li>
-<li><p>Function <code>freq()</code> has moved to a new package, <a href="https://github.com/msberends/clean" class="external-link"><code>clean</code></a> (<a href="https://cran.r-project.org/package=clean" class="external-link">CRAN link</a>), since creating frequency tables actually does not fit the scope of this package. The <code>freq()</code> function still works, since it is re-exported from the <code>clean</code> package (which will be installed automatically upon updating this <code>AMR</code> package).</p></li>
-<li><p>Renamed data set <code>septic_patients</code> to <code>example_isolates</code></p></li>
-</ul></div>
-<div class="section level4">
-<h4 id="new-0-8-0">New<a class="anchor" aria-label="anchor" href="#new-0-8-0"></a></h4>
-<ul><li>
-<p>Function <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with <code><a href="../reference/mo_property.html">mo_shortname()</a></code> at default:</p>
-<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span></span>
-<span><span class="co">#> NOTE: Using column `mo` as input for `col_mo`.</span></span>
-<span><span class="va">x</span><span class="op">[</span><span class="fl">1</span><span class="op">:</span><span class="fl">4</span>, <span class="op">]</span></span>
-<span><span class="co">#> mo ab S I R total</span></span>
-<span><span class="co">#> 1 A. baumannii AMC 0 0 3 3</span></span>
-<span><span class="co">#> 2 A. baumannii AMK 0 0 0 0</span></span>
-<span><span class="co">#> 3 A. baumannii AMP 0 0 3 3</span></span>
-<span><span class="co">#> 4 A. baumannii AMX 0 0 3 3</span></span>
-<span><span class="co">#> NOTE: Use 'format()' on this result to get a publicable/printable format.</span></span>
-<span></span>
-<span><span class="co"># change the transformation with the FUN argument to anything you like:</span></span>
-<span><span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span><span class="op">(</span><span class="va">example_isolates</span>, FUN <span class="op">=</span> <span class="va">mo_gramstain</span><span class="op">)</span></span>
-<span><span class="co">#> NOTE: Using column `mo` as input for `col_mo`.</span></span>
-<span><span class="va">x</span><span class="op">[</span><span class="fl">1</span><span class="op">:</span><span class="fl">4</span>, <span class="op">]</span></span>
-<span><span class="co">#> mo ab S I R total</span></span>
-<span><span class="co">#> 1 Gram-negative AMC 469 89 174 732</span></span>
-<span><span class="co">#> 2 Gram-negative AMK 251 0 2 253</span></span>
-<span><span class="co">#> 3 Gram-negative AMP 227 0 405 632</span></span>
-<span><span class="co">#> 4 Gram-negative AMX 227 0 405 632</span></span>
-<span><span class="co">#> NOTE: Use 'format()' on this result to get a publicable/printable format.</span></span></code></pre></div>
-<p>You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R <code><a href="https://rdrr.io/r/base/format.html" class="external-link">format()</a></code> function:</p>
-<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/format.html" class="external-link">format</a></span><span class="op">(</span><span class="va">x</span>, combine_IR <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li>
-<p>Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for <code>portion_*</code> functions or <code>count_*</code> functions. This can be used to determine the empiric susceptibility of a combination therapy. A new argument <code>only_all_tested</code> (<strong>which defaults to <code>FALSE</code></strong>) replaces the old <code>also_single_tested</code> and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the <code>portion</code> and <code>count</code> help pages), where the %SI is being determined:</p>
-<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># --------------------------------------------------------------------</span></span>
-<span><span class="co"># only_all_tested = FALSE only_all_tested = TRUE</span></span>
-<span><span class="co"># ----------------------- -----------------------</span></span>
-<span><span class="co"># Drug A Drug B include as include as include as include as</span></span>
-<span><span class="co"># numerator denominator numerator denominator</span></span>
-<span><span class="co"># -------- -------- ---------- ----------- ---------- -----------</span></span>
-<span><span class="co"># S or I S or I X X X X</span></span>
-<span><span class="co"># R S or I X X X X</span></span>
-<span><span class="co"># <NA> S or I X X - -</span></span>
-<span><span class="co"># S or I R X X X X</span></span>
-<span><span class="co"># R R - X - X</span></span>
-<span><span class="co"># <NA> R - - - -</span></span>
-<span><span class="co"># S or I <NA> X X - -</span></span>
-<span><span class="co"># R <NA> - - - -</span></span>
-<span><span class="co"># <NA> <NA> - - - -</span></span>
-<span><span class="co"># --------------------------------------------------------------------</span></span></code></pre></div>
-<p>Since this is a major change, usage of the old <code>also_single_tested</code> will throw an informative error that it has been replaced by <code>only_all_tested</code>.</p>
-</li>
-<li>
-<p><code>tibble</code> printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code> <code>mo</code>. When using <code>tibble</code>s containing antimicrobial columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
-<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># (run this on your own console, as this page does not support colour printing)</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">mo</span><span class="op">:</span><span class="va">AMC</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://tibble.tidyverse.org/reference/as_tibble.html" class="external-link">as_tibble</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-</li>
-</ul></div>
-<div class="section level4">
-<h4 id="changed-0-8-0">Changed<a class="anchor" aria-label="anchor" href="#changed-0-8-0"></a></h4>
-<ul><li>Many algorithm improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code> (of which some led to additions to the <code>microorganisms</code> data set). Many thanks to all contributors that helped improving the algorithms.
-<ul><li>Self-learning algorithm - the function now gains experience from previously determined microorganism IDs and learns from it (yielding 80-95% speed improvement for any guess after the first try)</li>
-<li>Big improvement for misspelled input</li>
-<li>These new trivial names known to the field are now understood: meningococcus, gonococcus, pneumococcus</li>
-<li>Updated to the latest taxonomic data (updated to August 2019, from the International Journal of Systematic and Evolutionary Microbiology</li>
-<li>Added support for Viridans Group Streptococci (VGS) and Milleri Group Streptococci (MGS)</li>
-<li>Added support for <em>Blastocystis</em>
-</li>
-<li>Added support for 5,000 new fungi</li>
-<li>Added support for unknown yeasts and fungi</li>
-<li>Changed most microorganism IDs to improve readability. For example, the old code <code>B_ENTRC_FAE</code> could have been both <em>E. faecalis</em> and <em>E. faecium</em>. Its new code is <code>B_ENTRC_FCLS</code> and <em>E. faecium</em> has become <code>B_ENTRC_FACM</code>. Also, the Latin character ae is now preserved at the start of each genus and species abbreviation. For example, the old code for <em>Aerococcus urinae</em> was <code>B_ARCCC_NAE</code>. This is now <code>B_AERCC_URIN</code>. <strong>IMPORTANT:</strong> Old microorganism IDs are still supported, but support will be dropped in a future version. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> on your old codes to transform them to the new format. Using functions from the <code>mo_*</code> family (like <code><a href="../reference/mo_property.html">mo_name()</a></code> and <code><a href="../reference/mo_property.html">mo_gramstain()</a></code>) on old codes, will throw a warning.</li>
-</ul></li>
-<li>More intelligent guessing for <code><a href="../reference/as.ab.html">as.ab()</a></code>, including bidirectional language support</li>
-<li>Added support for the German national guideline (3MRGN/4MRGN) in the <code><a href="../reference/mdro.html">mdro()</a></code> function, to determine multi-drug resistant organisms</li>
-<li>Function <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:
-<ul><li>Fixed a bug for <em>Yersinia pseudotuberculosis</em>
-</li>
-<li>Added more informative errors and warnings</li>
-<li>Printed info now distinguishes between added and changes values</li>
-<li>Using Verbose mode (i.e. <code>eucast_rules(..., verbose = TRUE)</code>) returns more informative and readable output</li>
-<li>Using factors as input now adds missing factors levels when the function changes antibiotic results</li>
-</ul></li>
-<li>Improved the internal auto-guessing function for determining antimicrobials in your data set (<code>AMR:::get_column_abx()</code>)</li>
-<li>Removed class <code>atc</code> - using <code>as.atc()</code> is now deprecated in favour of <code><a href="../reference/ab_property.html">ab_atc()</a></code> and this will return a character, not the <code>atc</code> class anymore</li>
-<li>Removed deprecated functions <code>abname()</code>, <code>ab_official()</code>, <code>atc_name()</code>, <code>atc_official()</code>, <code>atc_property()</code>, <code>atc_tradenames()</code>, <code>atc_trivial_nl()</code>
-</li>
-<li>Fix and speed improvement for <code><a href="../reference/mo_property.html">mo_shortname()</a></code>
-</li>
-<li>Fix for using <code>mo_*</code> functions where the coercion uncertainties and failures would not be available through <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code> and <code><a href="../reference/as.mo.html">mo_failures()</a></code> anymore</li>
-<li>Deprecated the <code>country</code> argument of <code><a href="../reference/mdro.html">mdro()</a></code> in favour of the already existing <code>guideline</code> argument to support multiple guidelines within one country</li>
-<li>The <code>name</code> of <code>RIF</code> is now Rifampicin instead of Rifampin</li>
-<li>The <code>antibiotics</code> data set is now sorted by name and all cephalosporins now have their generation between brackets</li>
-<li>Speed improvement for <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code> which is now 30 times faster for antibiotic abbreviations</li>
-<li>Improved <code>filter_ab_class()</code> to be more reliable and to support 5th generation cephalosporins</li>
-<li>Function <code><a href="../reference/availability.html">availability()</a></code> now uses <code>portion_R()</code> instead of <code>portion_IR()</code>, to comply with EUCAST insights</li>
-<li>Functions <code><a href="../reference/age.html">age()</a></code> and <code><a href="../reference/age_groups.html">age_groups()</a></code> now have a <code>na.rm</code> argument to remove empty values</li>
-<li>Renamed function <code>p.symbol()</code> to <code>p_symbol()</code> (the former is now deprecated and will be removed in a future version)</li>
-<li>Using negative values for <code>x</code> in <code><a href="../reference/age_groups.html">age_groups()</a></code> will now introduce <code>NA</code>s and not return an error anymore</li>
-<li>Fix for determining the system’s language</li>
-<li>Fix for <code>key_antibiotics()</code> on foreign systems</li>
-<li>Added 80 new LIS codes for microorganisms</li>
-<li>Relabeled the factor levels of <code><a href="../reference/mdro.html">mdr_tb()</a></code>
-</li>
-<li>Added more MIC factor levels (<code><a href="../reference/as.mic.html">as.mic()</a></code>)</li>
-</ul><div class="section level5">
-<h5 id="other-0-8-0">Other<a class="anchor" aria-label="anchor" href="#other-0-8-0"></a></h5>
-<ul><li>Added Prof. Dr. Casper Albers as doctoral advisor and added Dr. Judith Fonville, Eric Hazenberg, Dr. Bart Meijer, Dr. Dennis Souverein and Annick Lenglet as contributors</li>
-<li>Cleaned the coding style of every single syntax line in this package with the help of the <code>lintr</code> package</li>
-</ul></div>
-</div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.7.1" id="amr-071">AMR 0.7.1<small>2019-06-23</small><a class="anchor" aria-label="anchor" href="#amr-071"></a></h2>
-<div class="section level5">
-<h5 id="new-0-7-1">New<a class="anchor" aria-label="anchor" href="#new-0-7-1"></a></h5>
-<ul><li>
-<p>Function <code><a href="../reference/proportion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><a href="../reference/count.html">count_df()</a></code> and <code>portion_df()</code> to immediately show resistance percentages and number of available isolates:</p>
-<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="../reference/proportion.html">rsi_df</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co"># antibiotic interpretation value isolates</span></span>
-<span><span class="co"># 1 Amoxicillin SI 0.4442636 546</span></span>
-<span><span class="co"># 2 Amoxicillin R 0.5557364 683</span></span>
-<span><span class="co"># 3 Ciprofloxacin SI 0.8381831 1181</span></span>
-<span><span class="co"># 4 Ciprofloxacin R 0.1618169 228</span></span></code></pre></div>
-</li>
-<li>
-<p>Support for all scientifically published pathotypes of <em>E. coli</em> to date (that we could find). Supported are:</p>
-<ul><li>AIEC (Adherent-Invasive <em>E. coli</em>)</li>
-<li>ATEC (Atypical Entero-pathogenic <em>E. coli</em>)</li>
-<li>DAEC (Diffusely Adhering <em>E. coli</em>)</li>
-<li>EAEC (Entero-Aggresive <em>E. coli</em>)</li>
-<li>EHEC (Entero-Haemorrhagic <em>E. coli</em>)</li>
-<li>EIEC (Entero-Invasive <em>E. coli</em>)</li>
-<li>EPEC (Entero-Pathogenic <em>E. coli</em>)</li>
-<li>ETEC (Entero-Toxigenic <em>E. coli</em>)</li>
-<li>NMEC (Neonatal Meningitis-causing <em>E. coli</em>)</li>
-<li>STEC (Shiga-toxin producing <em>E. coli</em>)</li>
-<li>UPEC (Uropathogenic <em>E. coli</em>)</li>
-</ul><p>All these lead to the microbial ID of <em>E. coli</em>:</p>
-<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"UPEC"</span><span class="op">)</span></span>
-<span><span class="co"># B_ESCHR_COL</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"UPEC"</span><span class="op">)</span></span>
-<span><span class="co"># "Escherichia coli"</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"EHEC"</span><span class="op">)</span></span>
-<span><span class="co"># "Gram-negative"</span></span></code></pre></div>
-</li>
-<li><p>Function <code><a href="../reference/mo_property.html">mo_info()</a></code> as an analogy to <code><a href="../reference/ab_property.html">ab_info()</a></code>. The <code><a href="../reference/mo_property.html">mo_info()</a></code> prints a list with the full taxonomy, authors, and the URL to the online database of a microorganism</p></li>
-<li><p>Function <code><a href="../reference/mo_property.html">mo_synonyms()</a></code> to get all previously accepted taxonomic names of a microorganism</p></li>
-</ul></div>
-<div class="section level5">
-<h5 id="changed-0-7-1">Changed<a class="anchor" aria-label="anchor" href="#changed-0-7-1"></a></h5>
-<ul><li>Column names of output <code><a href="../reference/count.html">count_df()</a></code> and <code>portion_df()</code> are now lowercase</li>
-<li>Fixed bug in translation of microorganism names</li>
-<li>Fixed bug in determining taxonomic kingdoms</li>
-<li>Algorithm improvements for <code><a href="../reference/as.ab.html">as.ab()</a></code> and <code><a href="../reference/as.mo.html">as.mo()</a></code> to understand even more severely misspelled input</li>
-<li>Function <code><a href="../reference/as.ab.html">as.ab()</a></code> now allows spaces for coercing antibiotics names</li>
-<li>Added <code>ggplot2</code> methods for automatically determining the scale type of classes <code>mo</code> and <code>ab</code>
-</li>
-<li>Added names of object in the header in frequency tables, even when using pipes</li>
-<li>Prevented <code>"bacteria"</code> from getting coerced by <code><a href="../reference/as.ab.html">as.ab()</a></code> because Bacterial is a brand name of trimethoprim (TMP)</li>
-<li>Fixed a bug where setting an antibiotic would not work for <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> and <code><a href="../reference/mdro.html">mdro()</a></code>
-</li>
-<li>Fixed a EUCAST rule for Staphylococci, where amikacin resistance would not be inferred from tobramycin</li>
-<li>Removed <code>latest_annual_release</code> from the <code><a href="../reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code> function</li>
-<li>Removed antibiotic code <code>PVM1</code> from the <code>antibiotics</code> data set as this was a duplicate of <code>PME</code>
-</li>
-<li>Fixed bug where not all old taxonomic names would be printed, when using a vector as input for <code><a href="../reference/as.mo.html">as.mo()</a></code>
-</li>
-<li>Manually added <em>Trichomonas vaginalis</em> from the kingdom of Protozoa, which is missing from the Catalogue of Life</li>
-<li>Small improvements to <code><a href="../reference/plot.html">plot()</a></code> and <code><a href="https://rdrr.io/r/graphics/barplot.html" class="external-link">barplot()</a></code> for MIC and RSI classes</li>
-<li>Allow Catalogue of Life IDs to be coerced by <code><a href="../reference/as.mo.html">as.mo()</a></code>
-</li>
-</ul></div>
-<div class="section level5">
-<h5 id="other-0-7-1">Other<a class="anchor" aria-label="anchor" href="#other-0-7-1"></a></h5>
-<ul><li>Fixed a note thrown by CRAN tests</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.7.0" id="amr-070">AMR 0.7.0<small>2019-06-03</small><a class="anchor" aria-label="anchor" href="#amr-070"></a></h2>
-<div class="section level5">
-<h5 id="new-0-7-0">New<a class="anchor" aria-label="anchor" href="#new-0-7-0"></a></h5>
-<ul><li>Support for translation of disk diffusion and MIC values to RSI values (i.e. antimicrobial interpretations). Supported guidelines are EUCAST (2011 to 2019) and CLSI (2011 to 2019). Use <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on an MIC value (created with <code><a href="../reference/as.mic.html">as.mic()</a></code>), a disk diffusion value (created with the new <code><a href="../reference/as.disk.html">as.disk()</a></code>) or on a complete date set containing columns with MIC or disk diffusion values.</li>
-<li>Function <code><a href="../reference/mo_property.html">mo_name()</a></code> as alias of <code><a href="../reference/mo_property.html">mo_fullname()</a></code>
-</li>
-<li>Added guidelines of the WHO to determine multi-drug resistance (MDR) for TB (<code><a href="../reference/mdro.html">mdr_tb()</a></code>) and added a new vignette about MDR. Read this tutorial <a href="https://msberends.gitlab.io/AMR/articles/MDR.html" class="external-link">here on our website</a>.</li>
-</ul></div>
-<div class="section level5">
-<h5 id="changed-0-7-0">Changed<a class="anchor" aria-label="anchor" href="#changed-0-7-0"></a></h5>
-<ul><li>Fixed a critical bug in <code><a href="../reference/first_isolate.html">first_isolate()</a></code> where missing species would lead to incorrect FALSEs. This bug was not present in AMR v0.5.0, but was in v0.6.0 and v0.6.1.</li>
-<li>Fixed a bug in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> where antibiotics from WHONET software would not be recognised</li>
-<li>Completely reworked the <code>antibiotics</code> data set:
-<ul><li>All entries now have 3 different identifiers:
-<ul><li>Column <code>ab</code> contains a human readable EARS-Net code, used by ECDC and WHO/WHONET - this is the primary identifier used in this package</li>
-<li>Column <code>atc</code> contains the ATC code, used by WHO/WHOCC</li>
-<li>Column <code>cid</code> contains the CID code (Compound ID), used by PubChem</li>
-</ul></li>
-<li>Based on the Compound ID, almost 5,000 official brand names have been added from many different countries</li>
-<li>All references to antibiotics in our package now use EARS-Net codes, like <code>AMX</code> for amoxicillin</li>
-<li>Functions <code>atc_certe</code>, <code>ab_umcg</code> and <code>atc_trivial_nl</code> have been removed</li>
-<li>All <code>atc_*</code> functions are superseded by <code>ab_*</code> functions</li>
-<li>All output will be translated by using an included translation file which <a href="https://github.com/msberends/AMR/blob/main/data-raw/translations.tsv" class="external-link">can be viewed here</a>
-</li>
-</ul></li>
-<li>Improvements to plotting AMR results with <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code>:
-<ul><li>New argument <code>colours</code> to set the bar colours</li>
-<li>New arguments <code>title</code>, <code>subtitle</code>, <code>caption</code>, <code>x.title</code> and <code>y.title</code> to set titles and axis descriptions</li>
-</ul></li>
-<li>Improved intelligence of looking up antibiotic columns in a data set using <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code>
-</li>
-<li>Added ~5,000 more old taxonomic names to the <code>microorganisms.old</code> data set, which leads to better results finding when using the <code><a href="../reference/as.mo.html">as.mo()</a></code> function</li>
-<li>This package now honours the new EUCAST insight (2019) that S and I are but classified as susceptible, where I is defined as ‘increased exposure’ and not ‘intermediate’ anymore. For functions like <code>portion_df()</code> and <code><a href="../reference/count.html">count_df()</a></code> this means that their new argument <code>combine_SI</code> is TRUE at default. Our plotting function <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> also reflects this change since it uses <code><a href="../reference/count.html">count_df()</a></code> internally.</li>
-<li>The <code><a href="../reference/age.html">age()</a></code> function gained a new argument <code>exact</code> to determine ages with decimals</li>
-<li>Removed deprecated functions <code>guess_mo()</code>, <code>guess_atc()</code>, <code>EUCAST_rules()</code>, <code>interpretive_reading()</code>, <code><a href="../reference/as.rsi.html">rsi()</a></code>
-</li>
-<li>Frequency tables (<code>freq()</code>):
-<ul><li><p>speed improvement for microbial IDs</p></li>
-<li><p>fixed factor level names for R Markdown</p></li>
-<li><p>when all values are unique it now shows a message instead of a warning</p></li>
-<li>
-<p>support for boxplots:</p>
-<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://rdrr.io/r/graphics/boxplot.html" class="external-link">boxplot</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co"># grouped boxplots:</span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://rdrr.io/r/graphics/boxplot.html" class="external-link">boxplot</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-</li>
-</ul></li>
-<li>Removed all hardcoded EUCAST rules and replaced them with a new reference file which <a href="https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv" class="external-link">can be viewed here</a>
-</li>
-<li>Added ceftazidim intrinsic resistance to <em>Streptococci</em>
-</li>
-<li>Changed default settings for <code><a href="../reference/age_groups.html">age_groups()</a></code>, to let groups of fives and tens end with 100+ instead of 120+</li>
-<li>Fix for <code>freq()</code> for when all values are <code>NA</code>
-</li>
-<li>Fix for <code><a href="../reference/first_isolate.html">first_isolate()</a></code> for when dates are missing</li>
-<li>Improved speed of <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code>
-</li>
-<li>Function <code><a href="../reference/as.mo.html">as.mo()</a></code> now gently interprets any number of whitespace characters (like tabs) as one space</li>
-<li>Function <code><a href="../reference/as.mo.html">as.mo()</a></code> now returns <code>UNKNOWN</code> for <code>"con"</code> (WHONET ID of ‘contamination’) and returns <code>NA</code> for <code>"xxx"</code>(WHONET ID of ‘no growth’)</li>
-<li>Small algorithm fix for <code><a href="../reference/as.mo.html">as.mo()</a></code>
-</li>
-<li>Removed viruses from data set <code>microorganisms.codes</code> and cleaned it up</li>
-<li>Fix for <code><a href="../reference/mo_property.html">mo_shortname()</a></code> where species would not be determined correctly</li>
-</ul></div>
-<div class="section level5">
-<h5 id="other-0-7-0">Other<a class="anchor" aria-label="anchor" href="#other-0-7-0"></a></h5>
-<ul><li>Support for R 3.6.0 and later by providing support for <a href="https://developer.r-project.org/Blog/public/2019/02/14/staged-install/index.html" class="external-link">staged install</a>
-</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.6.1" id="amr-061">AMR 0.6.1<small>2019-03-29</small><a class="anchor" aria-label="anchor" href="#amr-061"></a></h2>
-<div class="section level5">
-<h5 id="changed-0-6-1">Changed<a class="anchor" aria-label="anchor" href="#changed-0-6-1"></a></h5>
-<ul><li>Fixed a critical bug when using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> with <code>verbose = TRUE</code>
-</li>
-<li>Coercion of microbial IDs are now written to the package namespace instead of the user’s home folder, to comply with the CRAN policy</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.6.0" id="amr-060">AMR 0.6.0<small>2019-03-27</small><a class="anchor" aria-label="anchor" href="#amr-060"></a></h2>
-<p><strong>New website!</strong></p>
-<p>We’ve got a new website: <a href="https://msberends.gitlab.io/AMR/" class="external-link">https://msberends.gitlab.io/AMR</a> (built with the great <a href="https://pkgdown.r-lib.org/" class="external-link"><code>pkgdown</code></a>)</p>
-<ul><li>Contains the complete manual of this package and all of its functions with an explanation of their arguments</li>
-<li>Contains a comprehensive tutorial about how to conduct AMR data analysis, import data from WHONET or SPSS and many more.</li>
-</ul><div class="section level5">
-<h5 id="new-0-6-0">New<a class="anchor" aria-label="anchor" href="#new-0-6-0"></a></h5>
-<ul><li><p><strong>BREAKING</strong>: removed deprecated functions, arguments and references to ‘bactid’. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> to identify an MO code.</p></li>
-<li>
-<p>Catalogue of Life as a new taxonomic source for data about microorganisms, which also contains all ITIS data we used previously. The <code>microorganisms</code> data set now contains:</p>
-<ul><li><p>All ~55,000 (sub)species from the kingdoms of Archaea, Bacteria and Protozoa</p></li>
-<li><p>All ~3,000 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Onygenales, Pneumocystales, Saccharomycetales and Schizosaccharomycetales (covering at least like all species of <em>Aspergillus</em>, <em>Candida</em>, <em>Pneumocystis</em>, <em>Saccharomyces</em> and <em>Trichophyton</em>)</p></li>
-<li><p>All ~2,000 (sub)species from ~100 other relevant genera, from the kingdoms of Animalia and Plantae (like <em>Strongyloides</em> and <em>Taenia</em>)</p></li>
-<li><p>All ~15,000 previously accepted names of included (sub)species that have been taxonomically renamed</p></li>
-<li>
-<p>The responsible author(s) and year of scientific publication</p>
-<p>This data is updated annually - check the included version with the new function <code><a href="../reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code>.</p>
-</li>
-<li><p>Due to this change, some <code>mo</code> codes changed (e.g. <em>Streptococcus</em> changed from <code>B_STRPTC</code> to <code>B_STRPT</code>). A translation table is used internally to support older microorganism IDs, so users will not notice this difference.</p></li>
-<li><p>New function <code><a href="../reference/mo_property.html">mo_rank()</a></code> for the taxonomic rank (genus, species, infraspecies, etc.)</p></li>
-<li><p>New function <code><a href="../reference/mo_property.html">mo_url()</a></code> to get the direct URL of a species from the Catalogue of Life</p></li>
-</ul></li>
-<li>
-<p>Support for data from <a href="https://whonet.org/" class="external-link">WHONET</a> and <a href="https://www.ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net" class="external-link">EARS-Net</a> (European Antimicrobial Resistance Surveillance Network):</p>
-<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 arguments 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>The function <code><a href="../reference/as.mo.html">as.mo()</a></code> now knows all WHONET species abbreviations too, because almost 2,000 microbial abbreviations were added to the <code>microorganisms.codes</code> data set.</li>
-</ul></li>
-<li>
-<p>New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:</p>
-<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu">filter_aminoglycosides</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_carbapenems</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_cephalosporins</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_1st_cephalosporins</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_2nd_cephalosporins</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_3rd_cephalosporins</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_4th_cephalosporins</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_fluoroquinolones</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_glycopeptides</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_macrolides</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="fu">filter_tetracyclines</span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p>The <code>antibiotics</code> data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set. For example:</p>
-<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">filter_glycopeptides</span><span class="op">(</span>result <span class="op">=</span> <span class="st">"R"</span><span class="op">)</span></span>
-<span><span class="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">filter_glycopeptides</span><span class="op">(</span>result <span class="op">=</span> <span class="st">"R"</span>, scope <span class="op">=</span> <span class="st">"all"</span><span class="op">)</span></span>
-<span><span class="co"># Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is R</span></span></code></pre></div>
-</li>
-<li>
-<p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
-<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">ab_property</span> <span class="op">-></span> <span class="fu">atc_property</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="va">ab_name</span> <span class="op">-></span> <span class="fu">atc_name</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="va">ab_official</span> <span class="op">-></span> <span class="fu">atc_official</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="va">ab_trivial_nl</span> <span class="op">-></span> <span class="fu">atc_trivial_nl</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="va">ab_certe</span> <span class="op">-></span> <span class="fu">atc_certe</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="va">ab_umcg</span> <span class="op">-></span> <span class="fu">atc_umcg</span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="va">ab_tradenames</span> <span class="op">-></span> <span class="fu">atc_tradenames</span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p>These functions use <code>as.atc()</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>.</p>
-</li>
-<li><p>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</p></li>
-<li><p>Support for the upcoming <a href="https://dplyr.tidyverse.org" class="external-link"><code>dplyr</code></a> version 0.8.0</p></li>
-<li><p>New function <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code> to find an antibiotic column in a table</p></li>
-<li><p>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>.</p></li>
-<li><p>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.</p></li>
-<li><p>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</p></li>
-<li><p>New function <code><a href="../reference/age.html">age()</a></code> to calculate the (patients) age in years</p></li>
-<li><p>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 AMR data analysis per age group.</p></li>
-<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="../reference/plot.html">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="cb37"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span><span class="va">septic_patients</span>, col_ab <span class="op">=</span> <span class="st">"amox"</span><span class="op">)</span></span>
-<span><span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span><span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li>
-<p>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code>filter_first_weighted_isolate()</code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
-<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="va">...</span><span class="op">)</span></span>
-<span><span class="co"># or</span></span>
-<span><span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-<p>is equal to:</p>
-<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>only_firsts <span class="op">=</span> <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="va">...</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">only_firsts</span> <span class="op">==</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="op">-</span><span class="va">only_firsts</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li><p>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></p></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="external-link uri">https://msberends.gitlab.io/AMR</a>.</p></li>
-</ul></div>
-<div class="section level5">
-<h5 id="changed-0-6-0">Changed<a class="anchor" aria-label="anchor" href="#changed-0-6-0"></a></h5>
-<ul><li>Function <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:
-<ul><li>Updated EUCAST Clinical breakpoints to <a href="https://www.eucast.org/clinical_breakpoints/" class="external-link">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" class="external-link">J01CE01</a>)</li>
-<li>New info is returned when running this function, stating exactly what has been changed or added. Use <code>eucast_rules(..., verbose = TRUE)</code> to get a data set with all changed per bug and drug combination.</li>
-</ul></li>
-<li>Removed data sets <code>microorganisms.oldDT</code>, <code>microorganisms.prevDT</code>, <code>microorganisms.unprevDT</code> and <code>microorganismsDT</code> since they were no longer needed and only contained info already available in the <code>microorganisms</code> data set</li>
-<li>Added 65 antibiotics to the <code>antibiotics</code> data set, from the <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">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>Functions <code>atc_ddd()</code> and <code>atc_groups()</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>guess_mo()</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>guess_atc()</code> is now deprecated in favour of <code>as.atc()</code> and will be removed in future versions</li>
-<li>Improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code>:
-<ul><li>
-<p>Now handles incorrect spelling, like <code>i</code> instead of <code>y</code> and <code>f</code> instead of <code>ph</code>:</p>
-<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># mo_fullname() uses as.mo() internally</span></span>
-<span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="st">"Sthafilokockus aaureuz"</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "Staphylococcus aureus"</span></span>
-<span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="st">"S. klossi"</span><span class="op">)</span></span>
-<span><span class="co">#> [1] "Staphylococcus kloosii"</span></span></code></pre></div>
-</li>
-<li>
-<p>Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default <code>allow_uncertain = TRUE</code> is equal to uncertainty level 2. Run <code><a href="../reference/as.mo.html">?as.mo</a></code> for more info about these levels.</p>
-<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># equal:</span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">...</span>, allow_uncertain <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">...</span>, allow_uncertain <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># also equal:</span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">...</span>, allow_uncertain <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">...</span>, allow_uncertain <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span></code></pre></div>
-<p>Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable results.</p>
-</li>
-<li><p>Implemented the latest publication of Becker <em>et al.</em> (2019), for categorising coagulase-negative <em>Staphylococci</em></p></li>
-<li><p>All microbial IDs that found are now saved to a local file <code>~/.Rhistory_mo</code>. Use the new function <code>clean_mo_history()</code> to delete this file, which resets the algorithms.</p></li>
-<li><p>Incoercible results will now be considered ‘unknown’, MO code <code>UNKNOWN</code>. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese.</p></li>
-<li><p>Fix for vector containing only empty values</p></li>
-<li><p>Finds better results when input is in other languages</p></li>
-<li><p>Better handling for subspecies</p></li>
-<li><p>Better handling for <em>Salmonellae</em>, especially the ‘city like’ serovars like <em>Salmonella London</em></p></li>
-<li><p>Understanding of highly virulent <em>E. coli</em> strains like EIEC, EPEC and STEC</p></li>
-<li><p>There will be looked for uncertain results at default - these results will be returned with an informative warning</p></li>
-<li><p>Manual (help page) now contains more info about the algorithms</p></li>
-<li><p>Progress bar will be shown when it takes more than 3 seconds to get results</p></li>
-<li><p>Support for formatted console text</p></li>
-<li><p>Console will return the percentage of uncoercable input</p></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>Will now use a column named like “patid” for the patient ID (argument <code>col_patientid</code>), when this argument was left blank</li>
-<li>Will now use a column named like “key(…)ab” or “key(…)antibiotics” for the key antibiotics (argument <code>col_keyantibiotics()</code>), when this argument was left blank</li>
-<li>Removed argument <code>output_logical</code>, the function will now always return a logical value</li>
-<li>Renamed argument <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> argument)</li>
-<li>Merged data sets <code>microorganisms.certe</code> and <code>microorganisms.umcg</code> into <code>microorganisms.codes</code>
-</li>
-<li>Function <code><a href="../reference/mo_property.html">mo_taxonomy()</a></code> now contains the kingdom too</li>
-<li>Reduce false positives for <code><a href="../reference/as.rsi.html">is.rsi.eligible()</a></code> using the new <code>threshold</code> argument</li>
-<li>New colours for <code><a href="../reference/ggplot_rsi.html">scale_rsi_colours()</a></code>
-</li>
-<li>Summaries of class <code>mo</code> will now return the top 3 and the unique count, e.g. using <code>summary(mo)</code>
-</li>
-<li>Small text updates to summaries of class <code>rsi</code> and <code>mic</code>
-</li>
-<li>Function <code><a href="../reference/as.rsi.html">as.rsi()</a></code>:
-<ul><li>Now gives a warning when inputting MIC values</li>
-<li>Now accepts high and low resistance: <code>"HIGH S"</code> will return <code>S</code>
-</li>
-</ul></li>
-<li>Frequency tables (<code>freq()</code> function):
-<ul><li>
-<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
-<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span></span>
-<span><span class="co"># OLD WAY</span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>genus <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu">freq</span><span class="op">(</span><span class="va">genus</span><span class="op">)</span></span>
-<span><span class="co"># NEW WAY</span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu">freq</span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># Even supports grouping variables:</span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">gender</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu">freq</span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li><p>Header info is now available as a list, with the <code>header</code> function</p></li>
-<li><p>The argument <code>header</code> is now set to <code>TRUE</code> at default, even for markdown</p></li>
-<li><p>Added header info for class <code>mo</code> to show unique count of families, genera and species</p></li>
-<li><p>Now honours the <code>decimal.mark</code> setting, which just like <code>format</code> defaults to <code>getOption("OutDec")</code></p></li>
-<li><p>The new <code>big.mark</code> argument will at default be <code>","</code> when <code>decimal.mark = "."</code> and <code>"."</code> otherwise</p></li>
-<li><p>Fix for header text where all observations are <code>NA</code></p></li>
-<li><p>New argument <code>droplevels</code> to exclude empty factor levels when input is a factor</p></li>
-<li><p>Factor levels will be in header when present in input data (maximum of 5)</p></li>
-<li><p>Fix for using <code><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select()</a></code> on frequency tables</p></li>
-</ul></li>
-<li>Function <code><a href="../reference/ggplot_rsi.html">scale_y_percent()</a></code> now contains the <code>limits</code> argument</li>
-<li>Automatic argument filling for <code><a href="../reference/mdro.html">mdro()</a></code>, <code>key_antibiotics()</code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
-</li>
-<li>Updated examples for resistance prediction (<code><a href="../reference/resistance_predict.html">resistance_predict()</a></code> function)</li>
-<li>Fix for <code><a href="../reference/as.mic.html">as.mic()</a></code> to support more values ending in (several) zeroes</li>
-<li>if using different lengths of pattern and x in <code>%like%</code>, it will now return the call</li>
-</ul></div>
-<div class="section level5">
-<h5 id="other-0-6-0">Other<a class="anchor" aria-label="anchor" href="#other-0-6-0"></a></h5>
-<ul><li>Updated licence text to emphasise GPL 2.0 and that this is an R package.</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.5.0" id="amr-050">AMR 0.5.0<small>2018-11-30</small><a class="anchor" aria-label="anchor" href="#amr-050"></a></h2>
-<div class="section level5">
-<h5 id="new-0-5-0">New<a class="anchor" aria-label="anchor" href="#new-0-5-0"></a></h5>
-<ul><li>Repository moved to GitLab</li>
-<li>Function <code>count_all</code> to get all available isolates (that like all <code>portion_*</code> and <code>count_*</code> functions also supports <code>summarise</code> and <code>group_by</code>), the old <code>n_rsi</code> is now an alias of <code>count_all</code>
-</li>
-<li>Function <code>get_locale</code> to determine language for language-dependent output for some <code>mo_*</code> functions. This is now the default value for their <code>language</code> argument, by which the system language will be used at default.</li>
-<li>Data sets <code>microorganismsDT</code>, <code>microorganisms.prevDT</code>, <code>microorganisms.unprevDT</code> and <code>microorganisms.oldDT</code> to improve the speed of <code>as.mo</code>. They are for reference only, since they are primarily for internal use of <code>as.mo</code>.</li>
-<li>Function <code>read.4D</code> to read from the 4D database of the MMB department of the UMCG</li>
-<li>Functions <code>mo_authors</code> and <code>mo_year</code> to get specific values about the scientific reference of a taxonomic entry</li>
-</ul></div>
-<div class="section level5">
-<h5 id="changed-0-5-0">Changed<a class="anchor" aria-label="anchor" href="#changed-0-5-0"></a></h5>
-<ul><li><p>Functions <code>MDRO</code>, <code>BRMO</code>, <code>MRGN</code> and <code>EUCAST_exceptional_phenotypes</code> were renamed to <code>mdro</code>, <code>brmo</code>, <code>mrgn</code> and <code>eucast_exceptional_phenotypes</code></p></li>
-<li><p><code>EUCAST_rules</code> was renamed to <code>eucast_rules</code>, the old function still exists as a deprecated function</p></li>
-<li>
-<p>Big changes to the <code>eucast_rules</code> function:</p>
-<ul><li>Now also applies rules from the EUCAST ‘Breakpoint tables for bacteria’, version 8.1, 2018, <a href="https://www.eucast.org/clinical_breakpoints/" class="external-link uri">https://www.eucast.org/clinical_breakpoints/</a> (see Source of the function)</li>
-<li>New argument <code>rules</code> to specify which rules should be applied (expert rules, breakpoints, others or all)</li>
-<li>New argument <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>Better error handling when rules cannot be applied (i.e. new values could not be inserted)</li>
-<li>The number of affected values will now only be measured once per row/column combination</li>
-<li>Data set <code>septic_patients</code> now reflects these changes</li>
-<li>Added argument <code>pipe</code> for piperacillin (J01CA12), also to the <code>mdro</code> function</li>
-<li>Small fixes to EUCAST clinical breakpoint rules</li>
-</ul></li>
-<li><p>Added column <code>kingdom</code> to the microorganisms data set, and function <code>mo_kingdom</code> to look up values</p></li>
-<li><p>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></p></li>
-<li><p>Fewer than 3 characters as input for <code>as.mo</code> will return NA</p></li>
-<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="cb43"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. species"</span><span class="op">)</span> <span class="co"># B_ESCHR</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="st">"E. spp."</span><span class="op">)</span> <span class="co"># "Escherichia species"</span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"S. spp"</span><span class="op">)</span> <span class="co"># B_STPHY</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="st">"S. species"</span><span class="op">)</span> <span class="co"># "Staphylococcus species"</span></span></code></pre></div>
-</li>
-<li><p>Added argument <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)</p></li>
-<li><p>Fix for <code>portion_*(..., as_percent = TRUE)</code> when minimal number of isolates would not be met</p></li>
-<li><p>Added argument <code>also_single_tested</code> for <code>portion_*</code> and <code>count_*</code> functions to also include cases where not all antibiotics were tested but at least one of the tested antibiotics includes the target antimicribial interpretation, see <code><a href="../reference/proportion.html">?portion</a></code></p></li>
-<li><p>Using <code>portion_*</code> functions now throws a warning when total available isolate is below argument <code>minimum</code></p></li>
-<li><p>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</p></li>
-<li>
-<p>Frequency tables - <code>freq()</code>:</p>
-<ul><li>
-<p>Support for grouping variables, test with:</p>
-<div class="sourceCode" id="cb44"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu">freq</span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li>
-<p>Support for (un)selecting columns:</p>
-<div class="sourceCode" id="cb45"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu">freq</span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="op">-</span><span class="va">count</span>, <span class="op">-</span><span class="va">cum_count</span><span class="op">)</span> <span class="co"># only get item, percent, cum_percent</span></span></code></pre></div>
-</li>
-<li><p>Check for <code><a href="https://hms.tidyverse.org/reference/Deprecated.html" class="external-link">hms::is.hms</a></code></p></li>
-<li><p>Now prints in markdown at default in non-interactive sessions</p></li>
-<li><p>No longer adds the factor level column and sorts factors on count again</p></li>
-<li><p>Support for class <code>difftime</code></p></li>
-<li><p>New argument <code>na</code>, to choose which character to print for empty values</p></li>
-<li><p>New argument <code>header</code> to turn the header info off (default when <code>markdown = TRUE</code>)</p></li>
-<li><p>New argument <code>title</code> to manually setbthe title of the frequency table</p></li>
-</ul></li>
-<li><p><code>first_isolate</code> now tries to find columns to use as input when arguments are left blank</p></li>
-<li><p>Improvements for MDRO algorithm (function <code>mdro</code>)</p></li>
-<li><p>Data set <code>septic_patients</code> is now a <code>data.frame</code>, not a tibble anymore</p></li>
-<li><p>Removed diacritics from all authors (columns <code>microorganisms$ref</code> and <code>microorganisms.old$ref</code>) to comply with CRAN policy to only allow ASCII characters</p></li>
-<li><p>Fix for <code>mo_property</code> not working properly</p></li>
-<li><p>Fix for <code>eucast_rules</code> where some Streptococci would become ceftazidime R in EUCAST rule 4.5</p></li>
-<li><p>Support for named vectors of class <code>mo</code>, useful for <code>top_freq()</code></p></li>
-<li><p><code>ggplot_rsi</code> and <code>scale_y_percent</code> have <code>breaks</code> argument</p></li>
-<li>
-<p>AI improvements for <code>as.mo</code>:</p>
-<ul><li>
-<code>"CRS"</code> -> <em>Stenotrophomonas maltophilia</em>
-</li>
-<li>
-<code>"CRSM"</code> -> <em>Stenotrophomonas maltophilia</em>
-</li>
-<li>
-<code>"MSSA"</code> -> <em>Staphylococcus aureus</em>
-</li>
-<li>
-<code>"MSSE"</code> -> <em>Staphylococcus epidermidis</em>
-</li>
-</ul></li>
-<li><p>Fix for <code>join</code> functions</p></li>
-<li><p>Speed improvement for <code>is.rsi.eligible</code>, now 15-20 times faster</p></li>
-<li><p>In <code>g.test</code>, when <code>sum(x)</code> is below 1000 or any of the expected values is below 5, Fisher’s Exact Test will be suggested</p></li>
-<li><p><code>ab_name</code> will try to fall back on <code>as.atc</code> when no results are found</p></li>
-<li><p>Removed the addin to view data sets</p></li>
-<li><p>Percentages will now will rounded more logically (e.g. in <code>freq</code> function)</p></li>
-</ul></div>
-<div class="section level5">
-<h5 id="other-0-5-0">Other<a class="anchor" aria-label="anchor" href="#other-0-5-0"></a></h5>
-<ul><li>New dependency on package <code>crayon</code>, to support formatted text in the console</li>
-<li>Dependency <code>tidyr</code> is now mandatory (went to <code>Import</code> field) since <code>portion_df</code> and <code>count_df</code> rely on it</li>
-<li>Updated vignettes to comply with README</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.4.0" id="amr-040">AMR 0.4.0<small>2018-10-01</small><a class="anchor" aria-label="anchor" href="#amr-040"></a></h2>
-<div class="section level5">
-<h5 id="new-0-4-0">New<a class="anchor" aria-label="anchor" href="#new-0-4-0"></a></h5>
-<ul><li><p>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="external-link 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.</p></li>
-<li>
-<p>New functions based on the existing function <code>mo_property</code>:</p>
-<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>
-<li>Semantic names: <code>mo_fullname</code>, <code>mo_shortname</code>
-</li>
-<li>Microbial properties: <code>mo_type</code>, <code>mo_gramstain</code>
-</li>
-<li>Author and year: <code>mo_ref</code>
-</li>
-</ul><p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
-<div class="sourceCode" id="cb46"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span></span>
-<span><span class="co"># [1] "Gram negative"</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span>, language <span class="op">=</span> <span class="st">"de"</span><span class="op">)</span> <span class="co"># German</span></span>
-<span><span class="co"># [1] "Gramnegativ"</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span> <span class="co"># Spanish</span></span>
-<span><span class="co"># [1] "Gram negativo"</span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="st">"S. group A"</span>, language <span class="op">=</span> <span class="st">"pt"</span><span class="op">)</span> <span class="co"># Portuguese</span></span>
-<span><span class="co"># [1] "Streptococcus grupo A"</span></span></code></pre></div>
-<p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
-<div class="sourceCode" id="cb47"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"Esc blattae"</span><span class="op">)</span></span>
-<span><span class="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span></span>
-<span><span class="co"># [1] "Gram negative"</span></span></code></pre></div>
-</li>
-<li>
-<p>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</p>
-<ul><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><p>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 %>% mutate_if(is.rsi.eligible, as.rsi)</code></p></li>
-<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 intelligent rules:</p>
-<div class="sourceCode" id="cb48"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span></span>
-<span><span class="co"># [1] B_ESCHR_COL</span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"MRSA"</span><span class="op">)</span></span>
-<span><span class="co"># [1] B_STPHY_AUR</span></span>
-<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"S group A"</span><span class="op">)</span></span>
-<span><span class="co"># [1] B_STRPTC_GRA</span></span></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="cb49"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">thousands_of_E_colis</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"E. coli"</span>, <span class="fl">25000</span><span class="op">)</span></span>
-<span><span class="fu">microbenchmark</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">thousands_of_E_colis</span><span class="op">)</span>, unit <span class="op">=</span> <span class="st">"s"</span><span class="op">)</span></span>
-<span><span class="co"># Unit: seconds</span></span>
-<span><span class="co"># min median max neval</span></span>
-<span><span class="co"># 0.01817717 0.01843957 0.03878077 100</span></span></code></pre></div>
-</li>
-<li><p>Added argument <code>reference_df</code> for <code>as.mo</code>, so users can supply their own microbial IDs, name or codes as a reference table</p></li>
-<li>
-<p>Renamed all previous references to <code>bactid</code> to <code>mo</code>, like:</p>
-<ul><li>Column names inputs of <code>EUCAST_rules</code>, <code>first_isolate</code> and <code>key_antibiotics</code>
-</li>
-<li>Column names of datasets <code>microorganisms</code> and <code>septic_patients</code>
-</li>
-<li>All old syntaxes will still work with this version, but will throw warnings</li>
-</ul></li>
-<li><p>Function <code>labels_rsi_count</code> to print datalabels on a RSI <code>ggplot2</code> model</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><p>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></p></li>
-<li><p>Introduction to AMR as a vignette</p></li>
-<li><p>Removed clipboard functions as it violated the CRAN policy</p></li>
-<li><p>Renamed <code>septic_patients$sex</code> to <code>septic_patients$gender</code></p></li>
-</ul></div>
-<div class="section level5">
-<h5 id="changed-0-4-0">Changed<a class="anchor" aria-label="anchor" href="#changed-0-4-0"></a></h5>
-<ul><li><p>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</p></li>
-<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="cb50"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu">ab_official</span><span class="op">(</span><span class="st">"Bactroban"</span><span class="op">)</span></span>
-<span><span class="co"># [1] "Mupirocin"</span></span>
-<span><span class="fu"><a href="../reference/ab_property.html">ab_name</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co"># [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin"</span></span>
-<span><span class="fu"><a href="../reference/ab_property.html">ab_atc</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co"># [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"</span></span></code></pre></div>
-</li>
-<li><p>For <code>first_isolate</code>, rows will be ignored when there’s no species available</p></li>
-<li><p>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</p></li>
-<li><p>Fix for <code>as.mic</code> for values ending in zeroes after a real number</p></li>
-<li><p>Small fix where <em>B. fragilis</em> would not be found in the <code>microorganisms.umcg</code> data set</p></li>
-<li><p>Added <code>prevalence</code> column to the <code>microorganisms</code> data set</p></li>
-<li><p>Added arguments <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code></p></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="cb51"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">amox</span>, <span class="va">cipr</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="../reference/count.html">count_IR</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co"># which is the same as:</span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="../reference/count.html">count_IR</a></span><span class="op">(</span><span class="va">amox</span>, <span class="va">cipr</span><span class="op">)</span></span>
-<span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">portion_S</span><span class="op">(</span><span class="va">amcl</span><span class="op">)</span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">portion_S</span><span class="op">(</span><span class="va">amcl</span>, <span class="va">gent</span><span class="op">)</span></span>
-<span><span class="va">septic_patients</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">portion_S</span><span class="op">(</span><span class="va">amcl</span>, <span class="va">gent</span>, <span class="va">pita</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li><p>Edited <code>ggplot_rsi</code> and <code>geom_rsi</code> so they can cope with <code>count_df</code>. The new <code>fun</code> argument has value <code>portion_df</code> at default, but can be set to <code>count_df</code>.</p></li>
-<li><p>Fix for <code>ggplot_rsi</code> when the <code>ggplot2</code> package was not loaded</p></li>
-<li><p>Added datalabels function <code>labels_rsi_count</code> to <code>ggplot_rsi</code></p></li>
-<li><p>Added possibility to set any argument to <code>geom_rsi</code> (and <code>ggplot_rsi</code>) so you can set your own preferences</p></li>
-<li><p>Fix for joins, where predefined suffices would not be honoured</p></li>
-<li><p>Added argument <code>quote</code> to the <code>freq</code> function</p></li>
-<li><p>Added generic function <code>diff</code> for frequency tables</p></li>
-<li><p>Added longest en shortest character length in the frequency table (<code>freq</code>) header of class <code>character</code></p></li>
-<li>
-<p>Support for types (classes) list and matrix for <code>freq</code></p>
-<div class="sourceCode" id="cb52"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">my_matrix</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/with.html" class="external-link">with</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">age</span>, <span class="va">gender</span><span class="op">)</span>, ncol <span class="op">=</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="fu">freq</span><span class="op">(</span><span class="va">my_matrix</span><span class="op">)</span></span></code></pre></div>
-<p>For lists, subsetting is possible:</p>
-<div class="sourceCode" id="cb53"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">my_list</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>age <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">age</span>, gender <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">gender</span><span class="op">)</span></span>
-<span><span class="va">my_list</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span></span>
-<span><span class="va">my_list</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">freq</span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></span></code></pre></div>
-</li>
-</ul></div>
-<div class="section level5">
-<h5 id="other-0-4-0">Other<a class="anchor" aria-label="anchor" href="#other-0-4-0"></a></h5>
-<ul><li>More unit tests to ensure better integrity of functions</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.3.0" id="amr-030">AMR 0.3.0<small>2018-08-14</small><a class="anchor" aria-label="anchor" href="#amr-030"></a></h2>
-<div class="section level5">
-<h5 id="new-0-3-0">New<a class="anchor" aria-label="anchor" href="#new-0-3-0"></a></h5>
-<ul><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>
-</ul></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:
-<ul><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-negative: gentamicin, tobramycin, colistin, cefotaxime, ceftazidime, meropenem</li>
-</ul></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>
-<li>New wrapper function <code>ggplot_rsi</code> to apply all above functions on a data set:
-<ul><li>
-<code>septic_patients %>% select(tobr, gent) %>% ggplot_rsi</code> will show portions of S, I and R immediately in a pretty plot</li>
-<li>Support for grouped variables, see <code><a href="../reference/ggplot_rsi.html">?ggplot_rsi</a></code>
-</li>
-</ul></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>The existing function <code>guess_bactid</code> is now an alias of <code>as.bactid</code>
-</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>
-</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>Function <code>g.test</code> to perform the X<sup>2</sup> distributed <a href="https://en.wikipedia.org/wiki/G-test" class="external-link"><em>G</em>-test</a>, which use is the same as <code>chisq.test</code>
-</li>
-<li>
-<del>Function <code>ratio</code> to transform a vector of values to a preset ratio</del>
-<ul><li><del>For example: <code>ratio(c(10, 500, 10), ratio = "1:2:1")</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>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>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>):
-<ul><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>table</code> to use as input: <code>freq(table(x, y))</code>
-</li>
-<li>Support for existing functions <code>hist</code> and <code>plot</code> to use a frequency table as input: <code>hist(freq(df$age))</code>
-</li>
-<li>Support for <code>as.vector</code>, <code>as.data.frame</code>, <code>as_tibble</code> and <code>format</code>
-</li>
-<li>Support for quasiquotation: <code>freq(mydata, mycolumn)</code> is the same as <code>mydata %>% freq(mycolumn)</code>
-</li>
-<li>Function <code>top_freq</code> function to return the top/below <em>n</em> items as vector</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>options(max.print.freq = n)</code> where <em>n</em> is your preset value</li>
-</ul></li>
-</ul></div>
-<div class="section level5">
-<h5 id="changed-0-3-0">Changed<a class="anchor" aria-label="anchor" href="#changed-0-3-0"></a></h5>
-<ul><li>Improvements for forecasting with <code>resistance_predict</code> and added more examples</li>
-<li>More antibiotics added as arguments for EUCAST rules</li>
-<li>Updated version of the <code>septic_patients</code> data set to better reflect the reality</li>
-<li>Pretty printing for tibbles removed as it is not really the scope of this package</li>
-<li>Printing of <code>mic</code> and <code>rsi</code> classes now returns all values - use <code>freq</code> to check distributions</li>
-<li>Improved speed of key antibiotics comparison for determining first isolates</li>
-<li>Column names for the <code>key_antibiotics</code> function are now generic: 6 for broadspectrum ABs, 6 for Gram-positive specific and 6 for Gram-negative specific ABs</li>
-<li>Speed improvement for the <code>abname</code> function</li>
-<li>
-<code>%like%</code> now supports multiple patterns</li>
-<li>Frequency tables are now actual <code>data.frame</code>s with altered console printing to make it look like a frequency table. Because of this, the argument <code>toConsole</code> is not longer needed.</li>
-<li>Fix for <code>freq</code> where the class of an item would be lost</li>
-<li>Small translational improvements to the <code>septic_patients</code> dataset and the column <code>bactid</code> now has the new class <code>"bactid"</code>
-</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>
-<li>Combined MIC/RSI values will now be coerced by the <code>rsi</code> and <code>mic</code> functions:
-<ul><li>
-<code>as.rsi("<=0.002; S")</code> will return <code>S</code>
-</li>
-<li>
-<code>as.mic("<=0.002; S")</code> will return <code><=0.002</code>
-</li>
-</ul></li>
-<li>Now possible to coerce MIC values with a space between operator and value, i.e. <code>as.mic("<= 0.002")</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>Added <code>"groups"</code> option for <code>atc_property(..., property)</code>. It will return a vector of the ATC hierarchy as defined by the <a href="https://www.whocc.no/atc/structure_and_principles/" class="external-link">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>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" class="external-link"><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>)
-<ul><li>So <code>yourdata %>% select(genus, species) %>% as.bactid()</code> now also works</li>
-</ul></li>
-<li>Other small fixes</li>
-</ul></div>
-<div class="section level5">
-<h5 id="other-0-3-0">Other<a class="anchor" aria-label="anchor" href="#other-0-3-0"></a></h5>
-<ul><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="external-link uri">https://travis-ci.org/msberends/AMR</a>
-</li>
-<li>Windows: <a href="https://ci.appveyor.com/project/msberends/amr" class="external-link uri">https://ci.appveyor.com/project/msberends/amr</a>
-</li>
-</ul></li>
-<li>Added thesis advisors to DESCRIPTION file</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.2.0" id="amr-020">AMR 0.2.0<small>2018-05-03</small><a class="anchor" aria-label="anchor" href="#amr-020"></a></h2>
-<div class="section level5">
-<h5 id="new-0-2-0">New<a class="anchor" aria-label="anchor" href="#new-0-2-0"></a></h5>
-<ul><li>Full support for Windows, Linux and macOS</li>
-<li>Full support for old R versions, only R-3.0.0 (April 2013) or later is needed (needed packages may have other dependencies)</li>
-<li>Function <code>n_rsi</code> to count cases where antibiotic test results were available, to be used in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">dplyr::summarise</a></code>, see ?rsi</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>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.
-<ul><li>Exceptional resistances defined by EUCAST 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>
-</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>
-<li>New print format for <code>tibble</code>s and <code>data.table</code>s</li>
-</ul></div>
-<div class="section level5">
-<h5 id="changed-0-2-0">Changed<a class="anchor" aria-label="anchor" href="#changed-0-2-0"></a></h5>
-<ul><li>Fixed <code>rsi</code> class for vectors that contain only invalid antimicrobial interpretations</li>
-<li>Renamed dataset <code>ablist</code> to <code>antibiotics</code>
-</li>
-<li>Renamed dataset <code>bactlist</code> to <code>microorganisms</code>
-</li>
-<li>Added common abbreviations and trade names to the <code>antibiotics</code> dataset</li>
-<li>Added more microorganisms to the <code>microorganisms</code> dataset</li>
-<li>Added analysis examples on help page of dataset <code>septic_patients</code>
-</li>
-<li>Added support for character vector in <code>join</code> functions</li>
-<li>Added warnings when a join results in more rows after than before the join</li>
-<li>Altered <code>%like%</code> to make it case insensitive</li>
-<li>For arguments of functions <code>first_isolate</code> and <code>EUCAST_rules</code> column names are now case-insensitive</li>
-<li>Functions <code>as.rsi</code> and <code>as.mic</code> now add the package name and version as attributes</li>
-</ul></div>
-<div class="section level5">
-<h5 id="other-0-2-0">Other<a class="anchor" aria-label="anchor" href="#other-0-2-0"></a></h5>
-<ul><li>Expanded <code>README.md</code> with more examples</li>
-<li>Added <a href="https://orcid.org" class="external-link">ORCID</a> of authors to DESCRIPTION file</li>
-<li>Added unit testing with the <code>testthat</code> package</li>
-<li>Added build tests for Linux and macOS using Travis CI (<a href="https://travis-ci.org/msberends/AMR" class="external-link uri">https://travis-ci.org/msberends/AMR</a>)</li>
-<li>Added line coverage checking using CodeCov (<a href="https://codecov.io/gh/msberends/AMR/tree/main/R" class="external-link uri">https://codecov.io/gh/msberends/AMR/tree/main/R</a>)</li>
-</ul></div>
-</div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.1.1" id="amr-011">AMR 0.1.1<small>2018-03-14</small><a class="anchor" aria-label="anchor" href="#amr-011"></a></h2>
-<ul><li>
-<code>EUCAST_rules</code> applies for amoxicillin even if ampicillin is missing</li>
-<li>Edited column names to comply with GLIMS, the laboratory information system</li>
-<li>Added more valid MIC values</li>
-<li>Renamed ‘Daily Defined Dose’ to ‘Defined Daily Dose’</li>
-<li>Added barplots for <code>rsi</code> and <code>mic</code> classes</li>
-</ul></div>
- <div class="section level2">
-<h2 class="page-header" data-toc-text="0.1.0" id="amr-010">AMR 0.1.0<small>2018-02-22</small><a class="anchor" aria-label="anchor" href="#amr-010"></a></h2>
-<ul><li>First submission to CRAN.</li>
-</ul></div>
- </div>
-
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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- <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p>
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- * .Site -> body > .container
- * .Site-content -> body > .container .row
- * .footer -> footer
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- * have height set to 100%
- *
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- height: 100%;
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diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
deleted file mode 100644
index cd1d3da74..000000000
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- PCA: PCA.html
- SPSS: SPSS.html
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- benchmarks: benchmarks.html
- datasets: datasets.html
- resistance_predict: resistance_predict.html
- welcome_to_AMR: welcome_to_AMR.html
-last_built: 2022-03-27T07:33Z
-urls:
- reference: https://msberends.github.io/AMR/reference
- article: https://msberends.github.io/AMR/articles
-
diff --git a/docs/reference/AMR-deprecated.html b/docs/reference/AMR-deprecated.html
deleted file mode 100644
index fd452243d..000000000
--- a/docs/reference/AMR-deprecated.html
+++ /dev/null
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- <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1.9007</span>
- </span>
- </div>
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- Conduct AMR analysis
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- Predict antimicrobial resistance
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- <h1>Deprecated Functions</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/deprecated.R" class="external-link"><code>R/deprecated.R</code></a></small>
- <div class="hidden name"><code>AMR-deprecated.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>These functions are so-called '<a href="https://rdrr.io/r/base/Deprecated.html" class="external-link">Deprecated</a>'. <strong>They will be removed in a future release.</strong> Using the functions will give a warning with the name of the function it has been replaced by (if there is one).</p>
- </div>
-
-
- <div id="retired-lifecycle">
- <h2>Retired Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_retired.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>retired</strong>. A retired function is no longer under active development, and (if appropiate) a better alternative is available. No new arguments will be added, and only the most critical bugs will be fixed. In a future version, this function will be removed.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
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diff --git a/docs/reference/AMR.html b/docs/reference/AMR.html
deleted file mode 100644
index 8fc900b54..000000000
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- <h1>The <code>AMR</code> Package</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/amr.R" class="external-link"><code>R/amr.R</code></a></small>
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- <p>Welcome to the <code>AMR</code> package.</p>
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- <h2>Details</h2>
- <p><code>AMR</code> is a free, open-source and independent <span style="R">R</span> package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
-<p>After installing this package, <span style="R">R</span> knows ~71,000 distinct microbial species and all ~570 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
-<p>This package is fully independent of any other <span style="R">R</span> package and works on Windows, macOS and Linux with all versions of <span style="R">R</span> since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This <span style="R">R</span> 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.</p>
-<p>This package can be used for:</p><ul><li><p>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life and List of Prokaryotic names with Standing in Nomenclature</p></li>
-<li><p>Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines</p></li>
-<li><p>Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records</p></li>
-<li><p>Determining first isolates to be used for AMR data analysis</p></li>
-<li><p>Calculating antimicrobial resistance</p></li>
-<li><p>Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)</p></li>
-<li><p>Calculating (empirical) susceptibility of both mono therapy and combination therapies</p></li>
-<li><p>Predicting future antimicrobial resistance using regression models</p></li>
-<li><p>Getting properties for any microorganism (such as Gram stain, species, genus or family)</p></li>
-<li><p>Getting properties for any antibiotic (such as name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)</p></li>
-<li><p>Plotting antimicrobial resistance</p></li>
-<li><p>Applying EUCAST expert rules</p></li>
-<li><p>Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code</p></li>
-<li><p>Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code</p></li>
-<li><p>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI</p></li>
-<li><p>Principal component analysis for AMR</p></li>
-</ul></div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
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- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
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-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
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- <h2>Contact Us</h2>
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-<p>For suggestions, comments or questions, please contact us at:</p>
-<p>Matthijs S. Berends <br>
-m.s.berends [at] umcg [dot] nl <br>
-University of Groningen
-Department of Medical Microbiology and Infection Prevention <br>
-University Medical Center Groningen <br>
-Post Office Box 30001 <br>
-9700 RB Groningen <br>
-The Netherlands
-<a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a></p>
-<p>If you have found a bug, please file a new issue at: <br><a href="https://github.com/msberends/AMR/issues" class="external-link">https://github.com/msberends/AMR/issues</a></p>
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diff --git a/docs/reference/WHOCC.html b/docs/reference/WHOCC.html
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-
-<p><img src="figures/logo_who.png" height="60" style='margin-bottom:"5"'><br>
-This package contains <strong>all ~550 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://www.whocc.no" class="external-link">https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a>).</p>
-<p>These have become the gold standard for international drug utilisation monitoring and research.</p>
-<p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
-<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.</strong> See <a href="https://www.whocc.no/copyright_disclaimer/." class="external-link">https://www.whocc.no/copyright_disclaimer/.</a></p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
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-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu"><a href="as.ab.html">as.ab</a></span><span class="op">(</span><span class="st">"meropenem"</span><span class="op">)</span>
-<span class="fu"><a href="ab_property.html">ab_name</a></span><span class="op">(</span><span class="st">"J01DH02"</span><span class="op">)</span>
-
-<span class="fu"><a href="ab_property.html">ab_tradenames</a></span><span class="op">(</span><span class="st">"flucloxacillin"</span><span class="op">)</span>
-</code></pre></div>
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diff --git a/docs/reference/WHONET.html b/docs/reference/WHONET.html
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- <h1>Data Set with 500 Isolates - WHONET Example</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>WHONET.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our <a href="example_isolates.html">example_isolates</a> data set. All patient names are created using online surname generators and are only in place for practice purposes.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">WHONET</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 500 observations and 53 variables:</p><ul><li><p><code>Identification number</code><br> ID of the sample</p></li>
-<li><p><code>Specimen number</code><br> ID of the specimen</p></li>
-<li><p><code>Organism</code><br> Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using <code><a href="as.mo.html">as.mo()</a></code>.</p></li>
-<li><p><code>Country</code><br> Country of origin</p></li>
-<li><p><code>Laboratory</code><br> Name of laboratory</p></li>
-<li><p><code>Last name</code><br> Fictitious last name of patient</p></li>
-<li><p><code>First name</code><br> Fictitious initial of patient</p></li>
-<li><p><code>Sex</code><br> Fictitious gender of patient</p></li>
-<li><p><code>Age</code><br> Fictitious age of patient</p></li>
-<li><p><code>Age category</code><br> Age group, can also be looked up using <code><a href="age_groups.html">age_groups()</a></code></p></li>
-<li><p><code>Date of admission</code><br><a href="https://rdrr.io/r/base/Dates.html" class="external-link">Date</a> of hospital admission</p></li>
-<li><p><code>Specimen date</code><br><a href="https://rdrr.io/r/base/Dates.html" class="external-link">Date</a> when specimen was received at laboratory</p></li>
-<li><p><code>Specimen type</code><br> Specimen type or group</p></li>
-<li><p><code>Specimen type (Numeric)</code><br> Translation of <code>"Specimen type"</code></p></li>
-<li><p><code>Reason</code><br> Reason of request with Differential Diagnosis</p></li>
-<li><p><code>Isolate number</code><br> ID of isolate</p></li>
-<li><p><code>Organism type</code><br> Type of microorganism, can also be looked up using <code><a href="mo_property.html">mo_type()</a></code></p></li>
-<li><p><code>Serotype</code><br> Serotype of microorganism</p></li>
-<li><p><code>Beta-lactamase</code><br> Microorganism produces beta-lactamase?</p></li>
-<li><p><code>ESBL</code><br> Microorganism produces extended spectrum beta-lactamase?</p></li>
-<li><p><code>Carbapenemase</code><br> Microorganism produces carbapenemase?</p></li>
-<li><p><code>MRSA screening test</code><br> Microorganism is possible MRSA?</p></li>
-<li><p><code>Inducible clindamycin resistance</code><br> Clindamycin can be induced?</p></li>
-<li><p><code>Comment</code><br> Other comments</p></li>
-<li><p><code>Date of data entry</code><br><a href="https://rdrr.io/r/base/Dates.html" class="external-link">Date</a> this data was entered in WHONET</p></li>
-<li><p><code>AMP_ND10:CIP_EE</code><br> 28 different antibiotics. You can lookup the abbreviations in the <a href="antibiotics.html">antibiotics</a> data set, or use e.g. <code><a href="ab_property.html">ab_name("AMP")</a></code> to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using <code><a href="as.rsi.html">as.rsi()</a></code>.</p></li>
-</ul></div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
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diff --git a/docs/reference/ab_from_text.html b/docs/reference/ab_from_text.html
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- Conduct principal component analysis for AMR
- </a>
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- <a href="../articles/MDR.html">
- <span class="fa fa-skull-crossbones"></span>
-
- Determine multi-drug resistance (MDR)
- </a>
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- <li>
- <a href="../articles/WHONET.html">
- <span class="fa fa-globe-americas"></span>
-
- Work with WHONET data
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- Import data from SPSS/SAS/Stata
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- Apply EUCAST rules
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- Get properties of a microorganism
- </a>
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- <li>
- <a href="../reference/ab_property.html">
- <span class="fa fa-capsules"></span>
-
- Get properties of an antibiotic
- </a>
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- <h1>Retrieve Antimicrobial Drug Names and Doses from Clinical Text</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ab_from_text.R" class="external-link"><code>R/ab_from_text.R</code></a></small>
- <div class="hidden name"><code>ab_from_text.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Use this function on e.g. clinical texts from health care records. It returns a <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a> with all antimicrobial drugs, doses and forms of administration found in the texts.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">ab_from_text</span><span class="op">(</span>
- <span class="va">text</span>,
- type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"drug"</span>, <span class="st">"dose"</span>, <span class="st">"administration"</span><span class="op">)</span>,
- collapse <span class="op">=</span> <span class="cn">NULL</span>,
- translate_ab <span class="op">=</span> <span class="cn">FALSE</span>,
- thorough_search <span class="op">=</span> <span class="cn">NULL</span>,
- info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>,
- <span class="va">...</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>text</dt>
-<dd><p>text to analyse</p></dd>
-<dt>type</dt>
-<dd><p>type of property to search for, either <code>"drug"</code>, <code>"dose"</code> or <code>"administration"</code>, see <em>Examples</em></p></dd>
-<dt>collapse</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> to pass on to <code>paste(, collapse = ...)</code> to only return one <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> per element of <code>text</code>, see <em>Examples</em></p></dd>
-<dt>translate_ab</dt>
-<dd><p>if <code>type = "drug"</code>: a column name of the <a href="antibiotics.html">antibiotics</a> data set to translate the antibiotic abbreviations to, using <code><a href="ab_property.html">ab_property()</a></code>. Defaults to <code>FALSE</code>. Using <code>TRUE</code> is equal to using "name".</p></dd>
-<dt>thorough_search</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to <code>TRUE</code> will take considerably more time than when using <code>FALSE</code>. At default, it will turn <code>TRUE</code> when all input elements contain a maximum of three words.</p></dd>
-<dt>info</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a progress bar should be printed, defaults to <code>TRUE</code> only in interactive mode</p></dd>
-<dt>...</dt>
-<dd><p>arguments passed on to <code><a href="as.ab.html">as.ab()</a></code></p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>A <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a>, or a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> if <code>collapse</code> is not <code>NULL</code></p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>This function is also internally used by <code><a href="as.ab.html">as.ab()</a></code>, although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the <code><a href="as.ab.html">as.ab()</a></code> function may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.</p><div class="section">
-<h3 id="argument-type">Argument <code>type</code><a class="anchor" aria-label="anchor" href="#argument-type"></a></h3>
-
-
-<p>At default, the function will search for antimicrobial drug names. All text elements will be searched for official names, ATC codes and brand names. As it uses <code><a href="as.ab.html">as.ab()</a></code> internally, it will correct for misspelling.</p>
-<p>With <code>type = "dose"</code> (or similar, like "dosing", "doses"), all text elements will be searched for <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> values that are higher than 100 and do not resemble years. The output will be <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a>. It supports any unit (g, mg, IE, etc.) and multiple values in one clinical text, see <em>Examples</em>.</p>
-<p>With <code>type = "administration"</code> (or abbreviations, like "admin", "adm"), all text elements will be searched for a form of drug administration. It supports the following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal and vaginal. Abbreviations for oral (such as 'po', 'per os') will become "oral", all values for intravenous (such as 'iv', 'intraven') will become "iv". It supports multiple values in one clinical text, see <em>Examples</em>.</p>
-</div>
-
-<div class="section">
-<h3 id="argument-collapse">Argument <code>collapse</code><a class="anchor" aria-label="anchor" href="#argument-collapse"></a></h3>
-
-
-<p>Without using <code>collapse</code>, this function will return a <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a>. This can be convenient to use e.g. inside a <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code>):<br><code>df %>% mutate(abx = ab_from_text(clinical_text))</code></p>
-<p>The returned AB codes can be transformed to official names, groups, etc. with all <code><a href="ab_property.html">ab_*</a></code> functions such as <code><a href="ab_property.html">ab_name()</a></code> and <code><a href="ab_property.html">ab_group()</a></code>, or by using the <code>translate_ab</code> argument.</p>
-<p>With using <code>collapse</code>, this function will return a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>:<br><code>df %>% mutate(abx = ab_from_text(clinical_text, collapse = "|"))</code></p>
-</div>
-
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># mind the bad spelling of amoxicillin in this line, </span>
-<span class="co"># straight from a true health care record:</span>
-<span class="fu">ab_from_text</span><span class="op">(</span><span class="st">"28/03/2020 regular amoxicilliin 500mg po tds"</span><span class="op">)</span>
-
-<span class="fu">ab_from_text</span><span class="op">(</span><span class="st">"500 mg amoxi po and 400mg cipro iv"</span><span class="op">)</span>
-<span class="fu">ab_from_text</span><span class="op">(</span><span class="st">"500 mg amoxi po and 400mg cipro iv"</span>, type <span class="op">=</span> <span class="st">"dose"</span><span class="op">)</span>
-<span class="fu">ab_from_text</span><span class="op">(</span><span class="st">"500 mg amoxi po and 400mg cipro iv"</span>, type <span class="op">=</span> <span class="st">"admin"</span><span class="op">)</span>
-
-<span class="fu">ab_from_text</span><span class="op">(</span><span class="st">"500 mg amoxi po and 400mg cipro iv"</span>, collapse <span class="op">=</span> <span class="st">", "</span><span class="op">)</span>
-<span class="co"># \donttest{</span>
-<span class="co"># if you want to know which antibiotic groups were administered, do e.g.:</span>
-<span class="va">abx</span> <span class="op"><-</span> <span class="fu">ab_from_text</span><span class="op">(</span><span class="st">"500 mg amoxi po and 400mg cipro iv"</span><span class="op">)</span>
-<span class="fu"><a href="ab_property.html">ab_group</a></span><span class="op">(</span><span class="va">abx</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">)</span>
-
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="fu"><a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a></span><span class="op">(</span>clinical_text <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"given 400mg cipro and 500 mg amox"</span>,
- <span class="st">"started on doxy iv today"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>abx_codes <span class="op">=</span> <span class="fu">ab_from_text</span><span class="op">(</span><span class="va">clinical_text</span><span class="op">)</span>,
- abx_doses <span class="op">=</span> <span class="fu">ab_from_text</span><span class="op">(</span><span class="va">clinical_text</span>, type <span class="op">=</span> <span class="st">"doses"</span><span class="op">)</span>,
- abx_admin <span class="op">=</span> <span class="fu">ab_from_text</span><span class="op">(</span><span class="va">clinical_text</span>, type <span class="op">=</span> <span class="st">"admin"</span><span class="op">)</span>,
- abx_coll <span class="op">=</span> <span class="fu">ab_from_text</span><span class="op">(</span><span class="va">clinical_text</span>, collapse <span class="op">=</span> <span class="st">"|"</span><span class="op">)</span>,
- abx_coll_names <span class="op">=</span> <span class="fu">ab_from_text</span><span class="op">(</span><span class="va">clinical_text</span>,
- collapse <span class="op">=</span> <span class="st">"|"</span>,
- translate_ab <span class="op">=</span> <span class="st">"name"</span><span class="op">)</span>,
- abx_coll_doses <span class="op">=</span> <span class="fu">ab_from_text</span><span class="op">(</span><span class="va">clinical_text</span>,
- type <span class="op">=</span> <span class="st">"doses"</span>,
- collapse <span class="op">=</span> <span class="st">"|"</span><span class="op">)</span>,
- abx_coll_admin <span class="op">=</span> <span class="fu">ab_from_text</span><span class="op">(</span><span class="va">clinical_text</span>,
- type <span class="op">=</span> <span class="st">"admin"</span>,
- collapse <span class="op">=</span> <span class="st">"|"</span><span class="op">)</span><span class="op">)</span>
-
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
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- </ul><ul class="nav navbar-nav navbar-right"><li>
- <a href="https://github.com/msberends/AMR" class="external-link">
- <span class="fab fa-github"></span>
-
- Source Code
- </a>
-</li>
- </ul></div><!--/.nav-collapse -->
- </div><!--/.container -->
-</div><!--/.navbar -->
-
-
-
- </header><div class="row">
- <div class="col-md-9 contents">
- <div class="page-header">
- <h1>Get Properties of an Antibiotic</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ab_property.R" class="external-link"><code>R/ab_property.R</code></a></small>
- <div class="hidden name"><code>ab_property.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Use these functions to return a specific property of an antibiotic from the <a href="antibiotics.html">antibiotics</a> data set. All input values will be evaluated internally with <code><a href="as.ab.html">as.ab()</a></code>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">ab_name</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, tolower <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_cid</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_synonyms</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_tradenames</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_group</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_atc</span><span class="op">(</span><span class="va">x</span>, only_first <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_atc_group1</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_atc_group2</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_loinc</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_ddd</span><span class="op">(</span><span class="va">x</span>, administration <span class="op">=</span> <span class="st">"oral"</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_ddd_units</span><span class="op">(</span><span class="va">x</span>, administration <span class="op">=</span> <span class="st">"oral"</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_info</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_url</span><span class="op">(</span><span class="va">x</span>, open <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_property</span><span class="op">(</span><span class="va">x</span>, property <span class="op">=</span> <span class="st">"name"</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">set_ab_names</span><span class="op">(</span>
- <span class="va">data</span>,
- <span class="va">...</span>,
- property <span class="op">=</span> <span class="st">"name"</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- snake_case <span class="op">=</span> <span class="cn">NULL</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>any (vector of) text that can be coerced to a valid antibiotic code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
-<dt>language</dt>
-<dd><p>language of the returned text, defaults to system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with <code>getOption("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
-<dt>tolower</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the first <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> of every output should be transformed to a lower case <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>. This will lead to e.g. "polymyxin B" and not "polymyxin b".</p></dd>
-<dt>...</dt>
-<dd><p>in case of <code>set_ab_names()</code> and <code>data</code> is a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>: variables to select (supports tidy selection such as <code>column1:column4</code>), otherwise other arguments passed on to <code><a href="as.ab.html">as.ab()</a></code></p></dd>
-<dt>only_first</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only the first ATC code must be returned, with giving preference to J0-codes (i.e., the antimicrobial drug group)</p></dd>
-<dt>administration</dt>
-<dd><p>way of administration, either <code>"oral"</code> or <code>"iv"</code></p></dd>
-<dt>open</dt>
-<dd><p>browse the URL using <code><a href="https://rdrr.io/r/utils/browseURL.html" class="external-link">utils::browseURL()</a></code></p></dd>
-<dt>property</dt>
-<dd><p>one of the column names of one of the <a href="antibiotics.html">antibiotics</a> data set: <code>vector_or(colnames(antibiotics), sort = FALSE)</code>.</p></dd>
-<dt>data</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> of which the columns need to be renamed, or a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector of column names</p></dd>
-<dt>snake_case</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the names should be in so-called <a href="https://en.wikipedia.org/wiki/Snake_case" class="external-link">snake case</a>: in lower case and all spaces/slashes replaced with an underscore (<code>_</code>)</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <ul><li><p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> in case of <code>ab_cid()</code></p></li>
-<li><p>A named <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a> in case of <code>ab_info()</code> and multiple <code>ab_atc()</code>/<code>ab_synonyms()</code>/<code>ab_tradenames()</code></p></li>
-<li><p>A <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> in case of <code>ab_ddd()</code></p></li>
-<li><p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> in case of <code>set_ab_names()</code></p></li>
-<li><p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> in all other cases</p></li>
-</ul></div>
- <div id="details">
- <h2>Details</h2>
- <p>All output <a href="translate.html">will be translated</a> where possible.</p>
-<p>The function <code>ab_url()</code> will return the direct URL to the official WHO website. A warning will be returned if the required ATC code is not available.</p>
-<p>The function <code>set_ab_names()</code> is a special column renaming function for <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>s. It renames columns names that resemble antimicrobial drugs. It always makes sure that the new column names are unique. If <code>property = "atc"</code> is set, preference is given to ATC codes from the J-group.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="source">
- <h2>Source</h2>
-
-
-<p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: <a href="https://www.whocc.no/atc_ddd_index/" class="external-link">https://www.whocc.no/atc_ddd_index/</a></p>
-<p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a></p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><a href="antibiotics.html">antibiotics</a></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># all properties:</span>
-<span class="fu">ab_name</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># "Amoxicillin"</span>
-<span class="fu">ab_atc</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># "J01CA04" (ATC code from the WHO)</span>
-<span class="fu">ab_cid</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># 33613 (Compound ID from PubChem)</span>
-<span class="fu">ab_synonyms</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># a list with brand names of amoxicillin</span>
-<span class="fu">ab_tradenames</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># same</span>
-<span class="fu">ab_group</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># "Beta-lactams/penicillins"</span>
-<span class="fu">ab_atc_group1</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># "Beta-lactam antibacterials, penicillins"</span>
-<span class="fu">ab_atc_group2</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># "Penicillins with extended spectrum"</span>
-<span class="fu">ab_url</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># link to the official WHO page</span>
-
-<span class="co"># smart lowercase tranformation</span>
-<span class="fu">ab_name</span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="st">"PLB"</span><span class="op">)</span><span class="op">)</span> <span class="co"># "Amoxicillin/clavulanic acid" "Polymyxin B"</span>
-<span class="fu">ab_name</span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="st">"PLB"</span><span class="op">)</span>,
- tolower <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="co"># "amoxicillin/clavulanic acid" "polymyxin B"</span>
-
-<span class="co"># defined daily doses (DDD)</span>
-<span class="fu">ab_ddd</span><span class="op">(</span><span class="st">"AMX"</span>, <span class="st">"oral"</span><span class="op">)</span> <span class="co"># 1.5</span>
-<span class="fu">ab_ddd_units</span><span class="op">(</span><span class="st">"AMX"</span>, <span class="st">"oral"</span><span class="op">)</span> <span class="co"># "g"</span>
-<span class="fu">ab_ddd</span><span class="op">(</span><span class="st">"AMX"</span>, <span class="st">"iv"</span><span class="op">)</span> <span class="co"># 3</span>
-<span class="fu">ab_ddd_units</span><span class="op">(</span><span class="st">"AMX"</span>, <span class="st">"iv"</span><span class="op">)</span> <span class="co"># "g"</span>
-
-<span class="fu">ab_info</span><span class="op">(</span><span class="st">"AMX"</span><span class="op">)</span> <span class="co"># all properties as a list</span>
-
-<span class="co"># all ab_* functions use as.ab() internally, so you can go from 'any' to 'any':</span>
-<span class="fu">ab_atc</span><span class="op">(</span><span class="st">"AMP"</span><span class="op">)</span> <span class="co"># ATC code of AMP (ampicillin)</span>
-<span class="fu">ab_group</span><span class="op">(</span><span class="st">"J01CA01"</span><span class="op">)</span> <span class="co"># Drug group of ampicillins ATC code</span>
-<span class="fu">ab_loinc</span><span class="op">(</span><span class="st">"ampicillin"</span><span class="op">)</span> <span class="co"># LOINC codes of ampicillin</span>
-<span class="fu">ab_name</span><span class="op">(</span><span class="st">"21066-6"</span><span class="op">)</span> <span class="co"># "Ampicillin" (using LOINC)</span>
-<span class="fu">ab_name</span><span class="op">(</span><span class="fl">6249</span><span class="op">)</span> <span class="co"># "Ampicillin" (using CID)</span>
-<span class="fu">ab_name</span><span class="op">(</span><span class="st">"J01CA01"</span><span class="op">)</span> <span class="co"># "Ampicillin" (using ATC)</span>
-
-<span class="co"># spelling from different languages and dyslexia are no problem</span>
-<span class="fu">ab_atc</span><span class="op">(</span><span class="st">"ceftriaxon"</span><span class="op">)</span>
-<span class="fu">ab_atc</span><span class="op">(</span><span class="st">"cephtriaxone"</span><span class="op">)</span>
-<span class="fu">ab_atc</span><span class="op">(</span><span class="st">"cephthriaxone"</span><span class="op">)</span>
-<span class="fu">ab_atc</span><span class="op">(</span><span class="st">"seephthriaaksone"</span><span class="op">)</span>
-
-<span class="co"># use set_ab_names() for renaming columns</span>
-<span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="fu">set_ab_names</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="fu">set_ab_names</span><span class="op">(</span><span class="va">example_isolates</span>, <span class="va">NIT</span><span class="op">:</span><span class="va">VAN</span><span class="op">)</span><span class="op">)</span>
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">set_ab_names</span><span class="op">(</span><span class="op">)</span>
-
- <span class="co"># this does the same:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/rename.html" class="external-link">rename_with</a></span><span class="op">(</span><span class="va">set_ab_names</span><span class="op">)</span>
-
- <span class="co"># set_ab_names() works with any AB property:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">set_ab_names</span><span class="op">(</span>property <span class="op">=</span> <span class="st">"atc"</span><span class="op">)</span>
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">set_ab_names</span><span class="op">(</span><span class="fu">where</span><span class="op">(</span><span class="va">is.rsi</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span>
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">set_ab_names</span><span class="op">(</span><span class="va">NIT</span><span class="op">:</span><span class="va">VAN</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
- <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2>
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-</div>
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- <footer><div class="copyright">
- <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p>
-</div>
-
-<div class="pkgdown">
- <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.3.</p>
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diff --git a/docs/reference/age.html b/docs/reference/age.html
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--- a/docs/reference/age.html
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-<!DOCTYPE html>
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- <h1>Age in Years of Individuals</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/age.R" class="external-link"><code>R/age.R</code></a></small>
- <div class="hidden name"><code>age.Rd</code></div>
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- <p>Calculates age in years based on a reference date, which is the sytem date at default.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">age</span><span class="op">(</span><span class="va">x</span>, reference <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Sys.time.html" class="external-link">Sys.Date</a></span><span class="op">(</span><span class="op">)</span>, exact <span class="op">=</span> <span class="cn">FALSE</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>date(s), <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vectors) will be coerced with <code><a href="https://rdrr.io/r/base/as.POSIXlt.html" class="external-link">as.POSIXlt()</a></code></p></dd>
-<dt>reference</dt>
-<dd><p>reference date(s) (defaults to today), <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vectors) will be coerced with <code><a href="https://rdrr.io/r/base/as.POSIXlt.html" class="external-link">as.POSIXlt()</a></code></p></dd>
-<dt>exact</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether age calculation should be exact, i.e. with decimals. It divides the number of days of <a href="https://en.wikipedia.org/wiki/Year-to-date" class="external-link">year-to-date</a> (YTD) of <code>x</code> by the number of days in the year of <code>reference</code> (either 365 or 366).</p></dd>
-<dt>na.rm</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether missing values should be removed</p></dd>
-<dt>...</dt>
-<dd><p>arguments passed on to <code><a href="https://rdrr.io/r/base/as.POSIXlt.html" class="external-link">as.POSIXlt()</a></code>, such as <code>origin</code></p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> (no decimals) if <code>exact = FALSE</code>, a <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> (with decimals) otherwise</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>Ages below 0 will be returned as <code>NA</code> with a warning. Ages above 120 will only give a warning.</p>
-<p>This function vectorises over both <code>x</code> and <code>reference</code>, meaning that either can have a length of 1 while the other argument has a larger length.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p>To split ages into groups, use the <code><a href="age_groups.html">age_groups()</a></code> function.</p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># 10 random birth dates</span>
-<span class="va">df</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>birth_date <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Sys.time.html" class="external-link">Sys.Date</a></span><span class="op">(</span><span class="op">)</span> <span class="op">-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Uniform.html" class="external-link">runif</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span> <span class="op">*</span> <span class="fl">25000</span><span class="op">)</span>
-<span class="co"># add ages</span>
-<span class="va">df</span><span class="op">$</span><span class="va">age</span> <span class="op"><-</span> <span class="fu">age</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">birth_date</span><span class="op">)</span>
-<span class="co"># add exact ages</span>
-<span class="va">df</span><span class="op">$</span><span class="va">age_exact</span> <span class="op"><-</span> <span class="fu">age</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">birth_date</span>, exact <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>
-
-<span class="va">df</span>
-</code></pre></div>
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-
-
- </header><div class="row">
- <div class="col-md-9 contents">
- <div class="page-header">
- <h1>Split Ages into Age Groups</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/age.R" class="external-link"><code>R/age.R</code></a></small>
- <div class="hidden name"><code>age_groups.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Split ages into age groups defined by the <code>split</code> argument. This allows for easier demographic (antimicrobial resistance) analysis.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">age_groups</span><span class="op">(</span><span class="va">x</span>, split_at <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">12</span>, <span class="fl">25</span>, <span class="fl">55</span>, <span class="fl">75</span><span class="op">)</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>age, e.g. calculated with <code><a href="age.html">age()</a></code></p></dd>
-<dt>split_at</dt>
-<dd><p>values to split <code>x</code> at, defaults to age groups 0-11, 12-24, 25-54, 55-74 and 75+. See <em>Details</em>.</p></dd>
-<dt>na.rm</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether missing values should be removed</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a></p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>To split ages, the input for the <code>split_at</code> argument can be:</p><ul><li><p>A <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> vector. A value of e.g. <code>c(10, 20)</code> will split <code>x</code> on 0-9, 10-19 and 20+. A value of only <code>50</code> will split <code>x</code> on 0-49 and 50+.
-The default is to split on young children (0-11), youth (12-24), young adults (25-54), middle-aged adults (55-74) and elderly (75+).</p></li>
-<li><p>A character:</p><ul><li><p><code>"children"</code> or <code>"kids"</code>, equivalent of: <code>c(0, 1, 2, 4, 6, 13, 18)</code>. This will split on 0, 1, 2-3, 4-5, 6-12, 13-17 and 18+.</p></li>
-<li><p><code>"elderly"</code> or <code>"seniors"</code>, equivalent of: <code>c(65, 75, 85)</code>. This will split on 0-64, 65-74, 75-84, 85+.</p></li>
-<li><p><code>"fives"</code>, equivalent of: <code>1:20 * 5</code>. This will split on 0-4, 5-9, ..., 95-99, 100+.</p></li>
-<li><p><code>"tens"</code>, equivalent of: <code>1:10 * 10</code>. This will split on 0-9, 10-19, ..., 90-99, 100+.</p></li>
-</ul></li>
-</ul></div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p>To determine ages, based on one or more reference dates, use the <code><a href="age.html">age()</a></code> function.</p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">ages</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fl">8</span>, <span class="fl">16</span>, <span class="fl">54</span>, <span class="fl">31</span>, <span class="fl">76</span>, <span class="fl">101</span>, <span class="fl">43</span>, <span class="fl">21</span><span class="op">)</span>
-
-<span class="co"># split into 0-49 and 50+</span>
-<span class="fu">age_groups</span><span class="op">(</span><span class="va">ages</span>, <span class="fl">50</span><span class="op">)</span>
-
-<span class="co"># split into 0-19, 20-49 and 50+</span>
-<span class="fu">age_groups</span><span class="op">(</span><span class="va">ages</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">20</span>, <span class="fl">50</span><span class="op">)</span><span class="op">)</span>
-
-<span class="co"># split into groups of ten years</span>
-<span class="fu">age_groups</span><span class="op">(</span><span class="va">ages</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">10</span> <span class="op">*</span> <span class="fl">10</span><span class="op">)</span>
-<span class="fu">age_groups</span><span class="op">(</span><span class="va">ages</span>, split_at <span class="op">=</span> <span class="st">"tens"</span><span class="op">)</span>
-
-<span class="co"># split into groups of five years</span>
-<span class="fu">age_groups</span><span class="op">(</span><span class="va">ages</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">20</span> <span class="op">*</span> <span class="fl">5</span><span class="op">)</span>
-<span class="fu">age_groups</span><span class="op">(</span><span class="va">ages</span>, split_at <span class="op">=</span> <span class="st">"fives"</span><span class="op">)</span>
-
-<span class="co"># split specifically for children</span>
-<span class="fu">age_groups</span><span class="op">(</span><span class="va">ages</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">4</span>, <span class="fl">6</span>, <span class="fl">13</span>, <span class="fl">17</span><span class="op">)</span><span class="op">)</span>
-<span class="fu">age_groups</span><span class="op">(</span><span class="va">ages</span>, <span class="st">"children"</span><span class="op">)</span>
-
-<span class="co"># \donttest{</span>
-<span class="co"># resistance of ciprofloxacin per age group</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">mo</span> <span class="op">==</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>age_group <span class="op">=</span> <span class="fu">age_groups</span><span class="op">(</span><span class="va">age</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">age_group</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="ggplot_rsi.html">ggplot_rsi</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"age_group"</span>, minimum <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
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- <h1>Antibiotic Selectors</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ab_selectors.R" class="external-link"><code>R/ab_selectors.R</code></a></small>
- <div class="hidden name"><code>antibiotic_class_selectors.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group, without the need to define the columns or antibiotic abbreviations. In short, if you have a column name that resembles an antimicrobial agent, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "CZO" and "J01DB04" will all be picked up by <code>cephalosporins()</code>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">ab_class</span><span class="op">(</span><span class="va">ab_class</span>, only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, only_treatable <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ab_selector</span><span class="op">(</span><span class="va">filter</span>, only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, only_treatable <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">aminoglycosides</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, only_treatable <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">aminopenicillins</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">antifungals</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">antimycobacterials</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">betalactams</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, only_treatable <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">carbapenems</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, only_treatable <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">cephalosporins</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">cephalosporins_1st</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">cephalosporins_2nd</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">cephalosporins_3rd</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">cephalosporins_4th</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">cephalosporins_5th</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">fluoroquinolones</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">glycopeptides</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">lincosamides</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">lipoglycopeptides</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">macrolides</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">oxazolidinones</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">penicillins</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">polymyxins</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, only_treatable <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">streptogramins</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">quinolones</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">tetracyclines</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">trimethoprims</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ureidopenicillins</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">administrable_per_os</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">administrable_iv</span><span class="op">(</span>only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">not_intrinsic_resistant</span><span class="op">(</span>
- only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>,
- col_mo <span class="op">=</span> <span class="cn">NULL</span>,
- version_expertrules <span class="op">=</span> <span class="fl">3.3</span>,
- <span class="va">...</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>ab_class</dt>
-<dd><p>an antimicrobial class or a part of it, such as <code>"carba"</code> and <code>"carbapenems"</code>. The columns <code>group</code>, <code>atc_group1</code> and <code>atc_group2</code> of the <a href="antibiotics.html">antibiotics</a> data set will be searched (case-insensitive) for this value.</p></dd>
-<dt>only_rsi_columns</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only columns of class <code><rsi></code> must be selected (defaults to <code>FALSE</code>), see <code><a href="as.rsi.html">as.rsi()</a></code></p></dd>
-<dt>only_treatable</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether agents that are only for laboratory tests should be excluded (defaults to <code>TRUE</code>), such as gentamicin-high (<code>GEH</code>) and imipenem/EDTA (<code>IPE</code>)</p></dd>
-<dt>...</dt>
-<dd><p>ignored, only in place to allow future extensions</p></dd>
-<dt>filter</dt>
-<dd><p>an <a href="https://rdrr.io/r/base/expression.html" class="external-link">expression</a> to be evaluated in the <a href="antibiotics.html">antibiotics</a> data set, such as <code>name %like% "trim"</code></p></dd>
-<dt>col_mo</dt>
-<dd><p>column name of the IDs of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>), defaults to the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
-<dt>version_expertrules</dt>
-<dd><p>the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be either "3.3", "3.2" or "3.1".</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>(internally) a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector of column names, with additional class <code>"ab_selector"</code></p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the <a href="https://tidyselect.r-lib.org/reference/language.html" class="external-link">Tidyverse selection helpers</a> such as <code><a href="https://tidyselect.r-lib.org/reference/everything.html" class="external-link">everything()</a></code>, but also work in base <span style="R">R</span> and not only in <code>dplyr</code> verbs. Nonetheless, they are very convenient to use with <code>dplyr</code> functions such as <code><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>, see <em>Examples</em>.</p>
-<p>All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) according to the <a href="antibiotics.html">antibiotics</a> data set. This means that a selector such as <code>aminoglycosides()</code> will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.</p>
-<p>The <code>ab_class()</code> function can be used to filter/select on a manually defined antibiotic class. It searches for results in the <a href="antibiotics.html">antibiotics</a> data set within the columns <code>group</code>, <code>atc_group1</code> and <code>atc_group2</code>.</p>
-<p>The <code>ab_selector()</code> function can be used to internally filter the <a href="antibiotics.html">antibiotics</a> data set on any results, see <em>Examples</em>. It allows for filtering on a (part of) a certain name, and/or a group name or even a minimum of DDDs for oral treatment. This function yields the highest flexibility, but is also the least user-friendly, since it requires a hard-coded filter to set.</p>
-<p>The <code>administrable_per_os()</code> and <code>administrable_iv()</code> functions also rely on the <a href="antibiotics.html">antibiotics</a> data set - antibiotic columns will be matched where a DDD (defined daily dose) for resp. oral and IV treatment is available in the <a href="antibiotics.html">antibiotics</a> data set.</p>
-<p>The <code>not_intrinsic_resistant()</code> function can be used to only select antibiotic columns that pose no intrinsic resistance for the microorganisms in the data set. For example, if a data set contains only microorganism codes or names of <em>E. coli</em> and <em>K. pneumoniae</em> and contains a column "vancomycin", this column will be removed (or rather, unselected) using this function. It currently applies <a href="https://www.eucast.org/expert_rules_and_expected_phenotypes/" class="external-link">'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3</a> (2021) to determine intrinsic resistance, using the <code><a href="eucast_rules.html">eucast_rules()</a></code> function internally. Because of this determination, this function is quite slow in terms of performance.</p>
- </div>
- <div id="full-list-of-supported-antibiotic-classes">
- <h2>Full list of supported (antibiotic) classes</h2>
-
-
-<ul><li><p><code>aminoglycosides()</code> can select: <br> amikacin (AMK), amikacin/fosfomycin (AKF), amphotericin B-high (AMH), apramycin (APR), arbekacin (ARB), astromicin (AST), bekanamycin (BEK), dibekacin (DKB), framycetin (FRM), gentamicin (GEN), gentamicin-high (GEH), habekacin (HAB), hygromycin (HYG), isepamicin (ISE), kanamycin (KAN), kanamycin-high (KAH), kanamycin/cephalexin (KAC), micronomicin (MCR), neomycin (NEO), netilmicin (NET), pentisomicin (PIM), plazomicin (PLZ), propikacin (PKA), ribostamycin (RST), sisomicin (SIS), streptoduocin (STR), streptomycin (STR1), streptomycin-high (STH), tobramycin (TOB) and tobramycin-high (TOH)</p></li>
-<li><p><code>aminopenicillins()</code> can select: <br> amoxicillin (AMX) and ampicillin (AMP)</p></li>
-<li><p><code>antifungals()</code> can select: <br> 5-fluorocytosine (FCT), amphotericin B (AMB), anidulafungin (ANI), butoconazole (BUT), caspofungin (CAS), ciclopirox (CIX), clotrimazole (CTR), econazole (ECO), fluconazole (FLU), fosfluconazole (FFL), griseofulvin (GRI), hachimycin (HCH), ibrexafungerp (IBX), isavuconazole (ISV), isoconazole (ISO), itraconazole (ITR), ketoconazole (KET), manogepix (MGX), micafungin (MIF), miconazole (MCZ), nystatin (NYS), pimaricin (PMR), posaconazole (POS), rezafungin (RZF), ribociclib (RBC), sulconazole (SUC), terbinafine (TRB), terconazole (TRC) and voriconazole (VOR)</p></li>
-<li><p><code>antimycobacterials()</code> can select: <br> 4-aminosalicylic acid (AMA), calcium aminosalicylate (CLA), capreomycin (CAP), clofazimine (CLF), delamanid (DLM), enviomycin (ENV), ethambutol (ETH), ethambutol/isoniazid (ETI), ethionamide (ETI1), isoniazid (INH), morinamide (MRN), p-aminosalicylic acid (PAS), pretomanid (PMD), prothionamide (PTH), pyrazinamide (PZA), rifabutin (RIB), rifampicin (RIF), rifampicin/isoniazid (RFI), rifampicin/pyrazinamide/ethambutol/isoniazid (RPEI), rifampicin/pyrazinamide/isoniazid (RPI), rifamycin (RFM), rifapentine (RFP), simvastatin/fenofibrate (SMF), sodium aminosalicylate (SDA), streptomycin/isoniazid (STI), terizidone (TRZ), thioacetazone/isoniazid (THI1), tiocarlide (TCR) and viomycin (VIO)</p></li>
-<li><p><code>betalactams()</code> can select: <br> amoxicillin (AMX), amoxicillin/clavulanic acid (AMC), amoxicillin/sulbactam (AXS), ampicillin (AMP), ampicillin/sulbactam (SAM), apalcillin (APL), aspoxicillin (APX), avibactam (AVB), azidocillin (AZD), azlocillin (AZL), aztreonam (ATM), aztreonam/avibactam (AZA), aztreonam/nacubactam (ANC), bacampicillin (BAM), benzathine benzylpenicillin (BNB), benzathine phenoxymethylpenicillin (BNP), benzylpenicillin (PEN), biapenem (BIA), carbenicillin (CRB), carindacillin (CRN), cefacetrile (CAC), cefaclor (CEC), cefadroxil (CFR), cefaloridine (RID), cefamandole (MAN), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefepime (FEP), cefepime/clavulanic acid (CPC), cefepime/nacubactam (FNC), cefepime/tazobactam (FPT), cefetamet (CAT), cefetamet pivoxil (CPI), cefetecol (CCL), cefetrizole (CZL), cefixime (CFM), cefmenoxime (CMX), cefmetazole (CMZ), cefodizime (DIZ), cefonicid (CID), cefoperazone (CFP), cefoperazone/sulbactam (CSL), ceforanide (CND), cefoselis (CSE), cefotaxime (CTX), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotetan (CTT), cefotiam (CTF), cefotiam hexetil (CHE), cefovecin (FOV), cefoxitin (FOX), cefoxitin screening (FOX1), cefozopran (ZOP), cefpimizole (CFZ), cefpiramide (CPM), cefpirome (CPO), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefprozil (CPR), cefquinome (CEQ), cefroxadine (CRD), cefsulodin (CFS), cefsumide (CSU), ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftezole (CTL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/enzyme inhibitor (CEI), ceftolozane/tazobactam (CZT), ceftriaxone (CRO), cefuroxime (CXM), cefuroxime axetil (CXA), cephalexin (LEX), cephalothin (CEP), cephapirin (HAP), cephradine (CED), ciclacillin (CIC), clometocillin (CLM), cloxacillin (CLO), dicloxacillin (DIC), doripenem (DOR), epicillin (EPC), ertapenem (ETP), flucloxacillin (FLC), hetacillin (HET), imipenem (IPM), imipenem/EDTA (IPE), imipenem/relebactam (IMR), latamoxef (LTM), lenampicillin (LEN), loracarbef (LOR), mecillinam (MEC), meropenem (MEM), meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), metampicillin (MTM), methicillin (MET), mezlocillin (MEZ), mezlocillin/sulbactam (MSU), nacubactam (NAC), nafcillin (NAF), oxacillin (OXA), panipenem (PAN), penamecillin (PNM), penicillin/novobiocin (PNO), penicillin/sulbactam (PSU), phenethicillin (PHE), phenoxymethylpenicillin (PHN), piperacillin (PIP), piperacillin/sulbactam (PIS), piperacillin/tazobactam (TZP), piridicillin (PRC), pivampicillin (PVM), pivmecillinam (PME), procaine benzylpenicillin (PRB), propicillin (PRP), razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), sarmoxicillin (SRX), sulbactam (SUL), sulbenicillin (SBC), sultamicillin (SLT6), talampicillin (TAL), tazobactam (TAZ), tebipenem (TBP), temocillin (TEM), ticarcillin (TIC) and ticarcillin/clavulanic acid (TCC)</p></li>
-<li><p><code>carbapenems()</code> can select: <br> biapenem (BIA), doripenem (DOR), ertapenem (ETP), imipenem (IPM), imipenem/EDTA (IPE), imipenem/relebactam (IMR), meropenem (MEM), meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), panipenem (PAN), razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA) and tebipenem (TBP)</p></li>
-<li><p><code>cephalosporins()</code> can select: <br> cefacetrile (CAC), cefaclor (CEC), cefadroxil (CFR), cefaloridine (RID), cefamandole (MAN), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefepime (FEP), cefepime/clavulanic acid (CPC), cefepime/tazobactam (FPT), cefetamet (CAT), cefetamet pivoxil (CPI), cefetecol (CCL), cefetrizole (CZL), cefixime (CFM), cefmenoxime (CMX), cefmetazole (CMZ), cefodizime (DIZ), cefonicid (CID), cefoperazone (CFP), cefoperazone/sulbactam (CSL), ceforanide (CND), cefoselis (CSE), cefotaxime (CTX), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotetan (CTT), cefotiam (CTF), cefotiam hexetil (CHE), cefovecin (FOV), cefoxitin (FOX), cefoxitin screening (FOX1), cefozopran (ZOP), cefpimizole (CFZ), cefpiramide (CPM), cefpirome (CPO), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefprozil (CPR), cefquinome (CEQ), cefroxadine (CRD), cefsulodin (CFS), cefsumide (CSU), ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftezole (CTL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/enzyme inhibitor (CEI), ceftolozane/tazobactam (CZT), ceftriaxone (CRO), cefuroxime (CXM), cefuroxime axetil (CXA), cephalexin (LEX), cephalothin (CEP), cephapirin (HAP), cephradine (CED), latamoxef (LTM) and loracarbef (LOR)</p></li>
-<li><p><code>cephalosporins_1st()</code> can select: <br> cefacetrile (CAC), cefadroxil (CFR), cefaloridine (RID), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefroxadine (CRD), ceftezole (CTL), cephalexin (LEX), cephalothin (CEP), cephapirin (HAP) and cephradine (CED)</p></li>
-<li><p><code>cephalosporins_2nd()</code> can select: <br> cefaclor (CEC), cefamandole (MAN), cefmetazole (CMZ), cefonicid (CID), ceforanide (CND), cefotetan (CTT), cefotiam (CTF), cefoxitin (FOX), cefoxitin screening (FOX1), cefprozil (CPR), cefuroxime (CXM), cefuroxime axetil (CXA) and loracarbef (LOR)</p></li>
-<li><p><code>cephalosporins_3rd()</code> can select: <br> cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefetamet (CAT), cefetamet pivoxil (CPI), cefixime (CFM), cefmenoxime (CMX), cefodizime (DIZ), cefoperazone (CFP), cefoperazone/sulbactam (CSL), cefotaxime (CTX), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotiam hexetil (CHE), cefovecin (FOV), cefpimizole (CFZ), cefpiramide (CPM), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefsulodin (CFS), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftriaxone (CRO) and latamoxef (LTM)</p></li>
-<li><p><code>cephalosporins_4th()</code> can select: <br> cefepime (FEP), cefepime/clavulanic acid (CPC), cefepime/tazobactam (FPT), cefetecol (CCL), cefoselis (CSE), cefozopran (ZOP), cefpirome (CPO) and cefquinome (CEQ)</p></li>
-<li><p><code>cephalosporins_5th()</code> can select: <br> ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/enzyme inhibitor (CEI) and ceftolozane/tazobactam (CZT)</p></li>
-<li><p><code>fluoroquinolones()</code> can select: <br> besifloxacin (BES), ciprofloxacin (CIP), clinafloxacin (CLX), danofloxacin (DAN), delafloxacin (DFX), difloxacin (DIF), enoxacin (ENX), enrofloxacin (ENR), finafloxacin (FIN), fleroxacin (FLE), garenoxacin (GRN), gatifloxacin (GAT), gemifloxacin (GEM), grepafloxacin (GRX), levofloxacin (LVX), levonadifloxacin (LND), lomefloxacin (LOM), marbofloxacin (MAR), metioxate (MXT), miloxacin (MIL), moxifloxacin (MFX), nadifloxacin (NAD), nifuroquine (NIF), norfloxacin (NOR), ofloxacin (OFX), orbifloxacin (ORB), pazufloxacin (PAZ), pefloxacin (PEF), pradofloxacin (PRA), premafloxacin (PRX), prulifloxacin (PRU), rufloxacin (RFL), sarafloxacin (SAR), sitafloxacin (SIT), sparfloxacin (SPX), temafloxacin (TMX), tilbroquinol (TBQ), tioxacin (TXC), tosufloxacin (TFX) and trovafloxacin (TVA)</p></li>
-<li><p><code>glycopeptides()</code> can select: <br> avoparcin (AVO), dalbavancin (DAL), norvancomycin (NVA), oritavancin (ORI), ramoplanin (RAM), teicoplanin (TEC), teicoplanin-macromethod (TCM), telavancin (TLV), vancomycin (VAN) and vancomycin-macromethod (VAM)</p></li>
-<li><p><code>lincosamides()</code> can select: <br> acetylmidecamycin (ACM), acetylspiramycin (ASP), clindamycin (CLI), gamithromycin (GAM), kitasamycin (KIT), lincomycin (LIN), meleumycin (MEL), nafithromycin (ZWK), pirlimycin (PRL), primycin (PRM), solithromycin (SOL), tildipirosin (TIP), tilmicosin (TIL), tulathromycin (TUL), tylosin (TYL) and tylvalosin (TYL1)</p></li>
-<li><p><code>lipoglycopeptides()</code> can select: <br> dalbavancin (DAL), oritavancin (ORI) and telavancin (TLV)</p></li>
-<li><p><code>macrolides()</code> can select: <br> acetylmidecamycin (ACM), acetylspiramycin (ASP), azithromycin (AZM), clarithromycin (CLR), dirithromycin (DIR), erythromycin (ERY), flurithromycin (FLR1), gamithromycin (GAM), josamycin (JOS), kitasamycin (KIT), meleumycin (MEL), midecamycin (MID), miocamycin (MCM), nafithromycin (ZWK), oleandomycin (OLE), pirlimycin (PRL), primycin (PRM), rokitamycin (ROK), roxithromycin (RXT), solithromycin (SOL), spiramycin (SPI), telithromycin (TLT), tildipirosin (TIP), tilmicosin (TIL), troleandomycin (TRL), tulathromycin (TUL), tylosin (TYL) and tylvalosin (TYL1)</p></li>
-<li><p><code>oxazolidinones()</code> can select: <br> cadazolid (CDZ), cycloserine (CYC), linezolid (LNZ), tedizolid (TZD) and thiacetazone (THA)</p></li>
-<li><p><code>penicillins()</code> can select: <br> amoxicillin (AMX), amoxicillin/clavulanic acid (AMC), amoxicillin/sulbactam (AXS), ampicillin (AMP), ampicillin/sulbactam (SAM), apalcillin (APL), aspoxicillin (APX), avibactam (AVB), azidocillin (AZD), azlocillin (AZL), aztreonam (ATM), aztreonam/avibactam (AZA), aztreonam/nacubactam (ANC), bacampicillin (BAM), benzathine benzylpenicillin (BNB), benzathine phenoxymethylpenicillin (BNP), benzylpenicillin (PEN), carbenicillin (CRB), carindacillin (CRN), cefepime/nacubactam (FNC), ciclacillin (CIC), clometocillin (CLM), cloxacillin (CLO), dicloxacillin (DIC), epicillin (EPC), flucloxacillin (FLC), hetacillin (HET), lenampicillin (LEN), mecillinam (MEC), metampicillin (MTM), methicillin (MET), mezlocillin (MEZ), mezlocillin/sulbactam (MSU), nacubactam (NAC), nafcillin (NAF), oxacillin (OXA), penamecillin (PNM), penicillin/novobiocin (PNO), penicillin/sulbactam (PSU), phenethicillin (PHE), phenoxymethylpenicillin (PHN), piperacillin (PIP), piperacillin/sulbactam (PIS), piperacillin/tazobactam (TZP), piridicillin (PRC), pivampicillin (PVM), pivmecillinam (PME), procaine benzylpenicillin (PRB), propicillin (PRP), sarmoxicillin (SRX), sulbactam (SUL), sulbenicillin (SBC), sultamicillin (SLT6), talampicillin (TAL), tazobactam (TAZ), temocillin (TEM), ticarcillin (TIC) and ticarcillin/clavulanic acid (TCC)</p></li>
-<li><p><code>polymyxins()</code> can select: <br> colistin (COL), polymyxin B (PLB) and polymyxin B/polysorbate 80 (POP)</p></li>
-<li><p><code>quinolones()</code> can select: <br> besifloxacin (BES), cinoxacin (CIN), ciprofloxacin (CIP), clinafloxacin (CLX), danofloxacin (DAN), delafloxacin (DFX), difloxacin (DIF), enoxacin (ENX), enrofloxacin (ENR), finafloxacin (FIN), fleroxacin (FLE), flumequine (FLM), garenoxacin (GRN), gatifloxacin (GAT), gemifloxacin (GEM), grepafloxacin (GRX), levofloxacin (LVX), levonadifloxacin (LND), lomefloxacin (LOM), marbofloxacin (MAR), metioxate (MXT), miloxacin (MIL), moxifloxacin (MFX), nadifloxacin (NAD), nalidixic acid (NAL), nifuroquine (NIF), nitroxoline (NTR), norfloxacin (NOR), ofloxacin (OFX), orbifloxacin (ORB), oxolinic acid (OXO), pazufloxacin (PAZ), pefloxacin (PEF), pipemidic acid (PPA), piromidic acid (PIR), pradofloxacin (PRA), premafloxacin (PRX), prulifloxacin (PRU), rosoxacin (ROS), rufloxacin (RFL), sarafloxacin (SAR), sitafloxacin (SIT), sparfloxacin (SPX), temafloxacin (TMX), tilbroquinol (TBQ), tioxacin (TXC), tosufloxacin (TFX) and trovafloxacin (TVA)</p></li>
-<li><p><code>streptogramins()</code> can select: <br> pristinamycin (PRI) and quinupristin/dalfopristin (QDA)</p></li>
-<li><p><code>tetracyclines()</code> can select: <br> cetocycline (CTO), chlortetracycline (CTE), clomocycline (CLM1), demeclocycline (DEM), doxycycline (DOX), eravacycline (ERV), lymecycline (LYM), metacycline (MTC), minocycline (MNO), omadacycline (OMC), oxytetracycline (OXY), penimepicycline (PNM1), rolitetracycline (RLT), tetracycline (TCY) and tigecycline (TGC)</p></li>
-<li><p><code>trimethoprims()</code> can select: <br> brodimoprim (BDP), sulfadiazine (SDI), sulfadiazine/tetroxoprim (SLT), sulfadiazine/trimethoprim (SLT1), sulfadimethoxine (SUD), sulfadimidine (SDM), sulfadimidine/trimethoprim (SLT2), sulfafurazole (SLF), sulfaisodimidine (SLF1), sulfalene (SLF2), sulfamazone (SZO), sulfamerazine (SLF3), sulfamerazine/trimethoprim (SLT3), sulfamethizole (SLF4), sulfamethoxazole (SMX), sulfamethoxypyridazine (SLF5), sulfametomidine (SLF6), sulfametoxydiazine (SLF7), sulfametrole/trimethoprim (SLT4), sulfamoxole (SLF8), sulfamoxole/trimethoprim (SLT5), sulfanilamide (SLF9), sulfaperin (SLF10), sulfaphenazole (SLF11), sulfapyridine (SLF12), sulfathiazole (SUT), sulfathiourea (SLF13), trimethoprim (TMP) and trimethoprim/sulfamethoxazole (SXT)</p></li>
-<li><p><code>ureidopenicillins()</code> can select: <br> azlocillin (AZL), mezlocillin (MEZ), piperacillin (PIP) and piperacillin/tazobactam (TZP)</p></li>
-</ul></div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># `example_isolates` is a data set available in the AMR package.</span>
-<span class="co"># See ?example_isolates.</span>
-
-<span class="co"># base R ------------------------------------------------------------------</span>
-
-<span class="co"># select columns 'IPM' (imipenem) and 'MEM' (meropenem)</span>
-<span class="va">example_isolates</span><span class="op">[</span>, <span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span><span class="op">]</span>
-
-<span class="co"># select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'</span>
-<span class="va">example_isolates</span><span class="op">[</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mo"</span>, <span class="fu">aminoglycosides</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">]</span>
-
-<span class="co"># select only antibiotic columns with DDDs for oral treatment</span>
-<span class="va">example_isolates</span><span class="op">[</span>, <span class="fu">administrable_per_os</span><span class="op">(</span><span class="op">)</span><span class="op">]</span>
-
-<span class="co"># filter using any() or all()</span>
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>, <span class="op">]</span>
-<span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">example_isolates</span>, <span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span>
-
-<span class="co"># filter on any or all results in the carbapenem columns (i.e., IPM, MEM):</span>
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>, <span class="op">]</span>
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>, <span class="op">]</span>
-
-<span class="co"># filter with multiple antibiotic selectors using c()</span>
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span>, <span class="fu">aminoglycosides</span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>, <span class="op">]</span>
-
-<span class="co"># filter + select in one go: get penicillins in carbapenems-resistant strains</span>
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>, <span class="fu">penicillins</span><span class="op">(</span><span class="op">)</span><span class="op">]</span>
-
-<span class="co"># You can combine selectors with '&' to be more specific. For example,</span>
-<span class="co"># penicillins() would select benzylpenicillin ('peni G') and</span>
-<span class="co"># administrable_per_os() would select erythromycin. Yet, when combined these</span>
-<span class="co"># drugs are both omitted since benzylpenicillin is not administrable per os</span>
-<span class="co"># and erythromycin is not a penicillin:</span>
-<span class="va">example_isolates</span><span class="op">[</span>, <span class="fu">penicillins</span><span class="op">(</span><span class="op">)</span> <span class="op">&</span> <span class="fu">administrable_per_os</span><span class="op">(</span><span class="op">)</span><span class="op">]</span>
-
-<span class="co"># ab_selector() applies a filter in the `antibiotics` data set and is thus very</span>
-<span class="co"># flexible. For instance, to select antibiotic columns with an oral DDD of at</span>
-<span class="co"># least 1 gram:</span>
-<span class="va">example_isolates</span><span class="op">[</span>, <span class="fu">ab_selector</span><span class="op">(</span><span class="va">oral_ddd</span> <span class="op">></span> <span class="fl">1</span> <span class="op">&</span> <span class="va">oral_units</span> <span class="op">==</span> <span class="st">"g"</span><span class="op">)</span><span class="op">]</span>
-
-<span class="co"># dplyr -------------------------------------------------------------------</span>
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
-
- <span class="co"># get AMR for all aminoglycosides e.g., per hospital:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu">aminoglycosides</span><span class="op">(</span><span class="op">)</span>, <span class="va">resistance</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># You can combine selectors with '&' to be more specific:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="fu">penicillins</span><span class="op">(</span><span class="op">)</span> <span class="op">&</span> <span class="fu">administrable_per_os</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># get AMR for only drugs that matter - no intrinsic resistance:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_genus</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Escherichia"</span>, <span class="st">"Klebsiella"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu">not_intrinsic_resistant</span><span class="op">(</span><span class="op">)</span>, <span class="va">resistance</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># get susceptibility for antibiotics whose name contains "trim":</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu">ab_selector</span><span class="op">(</span><span class="va">name</span> <span class="op"><a href="like.html">%like%</a></span> <span class="st">"trim"</span><span class="op">)</span>, <span class="va">susceptibility</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">mo</span>, <span class="fu">aminoglycosides</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># any() and all() work in dplyr's filter() too:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu">aminoglycosides</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>,
- <span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu">cephalosporins_2nd</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># also works with c():</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span>, <span class="fu">aminoglycosides</span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># not setting any/all will automatically apply all():</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu">aminoglycosides</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>
- <span class="co">#> i Assuming a filter on all 4 aminoglycosides.</span>
-
- <span class="co"># this will select columns 'mo' and all antimycobacterial drugs ('RIF'):</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">mo</span>, <span class="fu">ab_class</span><span class="op">(</span><span class="st">"mycobact"</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># get bug/drug combinations for only macrolides in Gram-positives:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_is_gram_positive</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">mo</span>, <span class="fu">macrolides</span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="bug_drug_combinations.html">bug_drug_combinations</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://rdrr.io/r/base/format.html" class="external-link">format</a></span><span class="op">(</span><span class="op">)</span>
-
- <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>some_column <span class="op">=</span> <span class="st">"some_value"</span>,
- J01CA01 <span class="op">=</span> <span class="st">"S"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># ATC code of ampicillin</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="fu">penicillins</span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co"># only the 'J01CA01' column will be selected</span>
-
-
- <span class="co"># with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal:</span>
- <span class="va">example_isolates</span><span class="op">[</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span>, <span class="op">]</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu">carbapenems</span><span class="op">(</span><span class="op">)</span>, <span class="op">~</span><span class="va">.x</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/antibiotics.html b/docs/reference/antibiotics.html
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- <h1>Data Sets with 566 Antimicrobial Drugs</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>antibiotics.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Two data sets containing all antibiotics/antimycotics and antivirals. Use <code><a href="as.ab.html">as.ab()</a></code> or one of the <code><a href="ab_property.html">ab_*</a></code> functions to retrieve values from the antibiotics data set. Three identifiers are included in this data set: an antibiotic ID (<code>ab</code>, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (<code>atc</code>) as defined by the WHO, and a Compound ID (<code>cid</code>) as found in PubChem. Other properties in this data set are derived from one or more of these codes. Note that some drugs have multiple ATC codes.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">antibiotics</span>
-
-<span class="va">antivirals</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
-
-<div class="section">
-<h3 id="for-the-antibiotics-data-set-a-data-frame-with-observations-and-variables-">For the antibiotics data set: a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 464 observations and 14 variables:<a class="anchor" aria-label="anchor" href="#for-the-antibiotics-data-set-a-data-frame-with-observations-and-variables-"></a></h3>
-
-<ul><li><p><code>ab</code><br> Antibiotic ID as used in this package (such as <code>AMC</code>), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available</p></li>
-<li><p><code>cid</code><br> Compound ID as found in PubChem</p></li>
-<li><p><code>name</code><br> Official name as used by WHONET/EARS-Net or the WHO</p></li>
-<li><p><code>group</code><br> A short and concise group name, based on WHONET and WHOCC definitions</p></li>
-<li><p><code>atc</code><br> ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC, like <code>J01CR02</code></p></li>
-<li><p><code>atc_group1</code><br> Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC, like <code>"Macrolides, lincosamides and streptogramins"</code></p></li>
-<li><p><code>atc_group2</code><br> Official chemical subgroup (4th level ATC code) as defined by the WHOCC, like <code>"Macrolides"</code></p></li>
-<li><p><code>abbr</code><br> List of abbreviations as used in many countries, also for antibiotic susceptibility testing (AST)</p></li>
-<li><p><code>synonyms</code><br> Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID</p></li>
-<li><p><code>oral_ddd</code><br> Defined Daily Dose (DDD), oral treatment, currently available for 170 drugs</p></li>
-<li><p><code>oral_units</code><br> Units of <code>oral_ddd</code></p></li>
-<li><p><code>iv_ddd</code><br> Defined Daily Dose (DDD), parenteral (intravenous) treatment, currently available for 145 drugs</p></li>
-<li><p><code>iv_units</code><br> Units of <code>iv_ddd</code></p></li>
-<li><p><code>loinc</code><br> All LOINC codes (Logical Observation Identifiers Names and Codes) associated with the name of the antimicrobial agent. Use <code><a href="ab_property.html">ab_loinc()</a></code> to retrieve them quickly, see <code><a href="ab_property.html">ab_property()</a></code>.</p></li>
-</ul></div>
-
-<div class="section">
-<h3 id="for-the-antivirals-data-set-a-data-frame-with-observations-and-variables-">For the antivirals data set: a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 102 observations and 9 variables:<a class="anchor" aria-label="anchor" href="#for-the-antivirals-data-set-a-data-frame-with-observations-and-variables-"></a></h3>
-
-<ul><li><p><code>atc</code><br> ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC</p></li>
-<li><p><code>cid</code><br> Compound ID as found in PubChem</p></li>
-<li><p><code>name</code><br> Official name as used by WHONET/EARS-Net or the WHO</p></li>
-<li><p><code>atc_group</code><br> Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC</p></li>
-<li><p><code>synonyms</code><br> Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID</p></li>
-<li><p><code>oral_ddd</code><br> Defined Daily Dose (DDD), oral treatment</p></li>
-<li><p><code>oral_units</code><br> Units of <code>oral_ddd</code></p></li>
-<li><p><code>iv_ddd</code><br> Defined Daily Dose (DDD), parenteral treatment</p></li>
-<li><p><code>iv_units</code><br> Units of <code>iv_ddd</code></p></li>
-</ul></div>
-
-<p>An object of class <code>data.frame</code> with 102 rows and 9 columns.</p>
- </div>
- <div id="source">
- <h2>Source</h2>
- <p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): <a href="https://www.whocc.no/atc_ddd_index/" class="external-link">https://www.whocc.no/atc_ddd_index/</a></p>
-<p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a></p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>Properties that are based on an ATC code are only available when an ATC is available. These properties are: <code>atc_group1</code>, <code>atc_group2</code>, <code>oral_ddd</code>, <code>oral_units</code>, <code>iv_ddd</code> and <code>iv_units</code>.</p>
-<p>Synonyms (i.e. trade names) were derived from the Compound ID (<code>cid</code>) and consequently only available where a CID is available.</p><div class="section">
-<h3 id="direct-download">Direct download<a class="anchor" aria-label="anchor" href="#direct-download"></a></h3>
-
-
-<p>These data sets are available as 'flat files' for use even without <span style="R">R</span> - you can find the files here:</p><ul><li><p><a href="https://github.com/msberends/AMR/raw/main/data-raw/antibiotics.txt" class="external-link">https://github.com/msberends/AMR/raw/main/data-raw/antibiotics.txt</a></p></li>
-<li><p><a href="https://github.com/msberends/AMR/raw/main/data-raw/antivirals.txt" class="external-link">https://github.com/msberends/AMR/raw/main/data-raw/antivirals.txt</a></p></li>
-</ul><p>Files in <span style="R">R</span> format (with preserved data structure) can be found here:</p><ul><li><p><a href="https://github.com/msberends/AMR/raw/main/data/antibiotics.rda" class="external-link">https://github.com/msberends/AMR/raw/main/data/antibiotics.rda</a></p></li>
-<li><p><a href="https://github.com/msberends/AMR/raw/main/data/antivirals.rda" class="external-link">https://github.com/msberends/AMR/raw/main/data/antivirals.rda</a></p></li>
-</ul></div>
-
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="whocc">
- <h2>WHOCC</h2>
-
-
-<p><img src="figures/logo_who.png" height="60" style='margin-bottom:"5"'><br>
-This package contains <strong>all ~550 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://www.whocc.no" class="external-link">https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a>).</p>
-<p>These have become the gold standard for international drug utilisation monitoring and research.</p>
-<p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
-<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.</strong> See <a href="https://www.whocc.no/copyright_disclaimer/." class="external-link">https://www.whocc.no/copyright_disclaimer/.</a></p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><a href="microorganisms.html">microorganisms</a>, <a href="intrinsic_resistant.html">intrinsic_resistant</a></p></div>
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- <h1>Transform Input to an Antibiotic ID</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ab.R" class="external-link"><code>R/ab.R</code></a></small>
- <div class="hidden name"><code>as.ab.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Use this function to determine the antibiotic code of one or more antibiotics. The data set <a href="antibiotics.html">antibiotics</a> will be searched for abbreviations, official names and synonyms (brand names).</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">as.ab</span><span class="op">(</span><span class="va">x</span>, flag_multiple_results <span class="op">=</span> <span class="cn">TRUE</span>, info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">is.ab</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector to determine to antibiotic ID</p></dd>
-<dt>flag_multiple_results</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a note should be printed to the console that probably more than one antibiotic code or name can be retrieved from a single input value.</p></dd>
-<dt>info</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a progress bar should be printed, defaults to <code>TRUE</code> only in interactive mode</p></dd>
-<dt>...</dt>
-<dd><p>arguments passed on to internal functions</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a><a href="https://rdrr.io/r/base/vector.html" class="external-link">vector</a> with additional class <code>ab</code></p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>All entries in the <a href="antibiotics.html">antibiotics</a> data set have three different identifiers: a human readable EARS-Net code (column <code>ab</code>, used by ECDC and WHONET), an ATC code (column <code>atc</code>, used by WHO), and a CID code (column <code>cid</code>, Compound ID, used by PubChem). The data set contains more than 5,000 official brand names from many different countries, as found in PubChem. Not that some drugs contain multiple ATC codes.</p>
-<p>All these properties will be searched for the user input. The <code>as.ab()</code> can correct for different forms of misspelling:</p><ul><li><p>Wrong spelling of drug names (such as "tobramicin" or "gentamycin"), which corrects for most audible similarities such as f/ph, x/ks, c/z/s, t/th, etc.</p></li>
-<li><p>Too few or too many vowels or consonants</p></li>
-<li><p>Switching two characters (such as "mreopenem", often the case in clinical data, when doctors typed too fast)</p></li>
-<li><p>Digitalised paper records, leaving artefacts like 0/o/O (zero and O's), B/8, n/r, etc.</p></li>
-</ul><p>Use the <code><a href="ab_property.html">ab_*</a></code> functions to get properties based on the returned antibiotic ID, see <em>Examples</em>.</p>
-<p>Note: the <code>as.ab()</code> and <code><a href="ab_property.html">ab_*</a></code> functions may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.</p>
- </div>
- <div id="source">
- <h2>Source</h2>
-
-
-<p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: <a href="https://www.whocc.no/atc_ddd_index/" class="external-link">https://www.whocc.no/atc_ddd_index/</a></p>
-<p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a></p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="whocc">
- <h2>WHOCC</h2>
-
-
-<p><img src="figures/logo_who.png" height="60" style='margin-bottom:"5"'><br>
-This package contains <strong>all ~550 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://www.whocc.no" class="external-link">https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a>).</p>
-<p>These have become the gold standard for international drug utilisation monitoring and research.</p>
-<p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
-<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.</strong> See <a href="https://www.whocc.no/copyright_disclaimer/." class="external-link">https://www.whocc.no/copyright_disclaimer/.</a></p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index">
-<ul><li><p><a href="antibiotics.html">antibiotics</a> for the <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> that is being used to determine ATCs</p></li>
-<li><p><code><a href="ab_from_text.html">ab_from_text()</a></code> for a function to retrieve antimicrobial drugs from clinical text (from health care records)</p></li>
-</ul></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># these examples all return "ERY", the ID of erythromycin:</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">"J01FA01"</span><span class="op">)</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">"J 01 FA 01"</span><span class="op">)</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">"Erythromycin"</span><span class="op">)</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">"eryt"</span><span class="op">)</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">" eryt 123"</span><span class="op">)</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">"ERYT"</span><span class="op">)</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">"ERY"</span><span class="op">)</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">"eritromicine"</span><span class="op">)</span> <span class="co"># spelled wrong, yet works</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">"Erythrocin"</span><span class="op">)</span> <span class="co"># trade name</span>
-<span class="fu">as.ab</span><span class="op">(</span><span class="st">"Romycin"</span><span class="op">)</span> <span class="co"># trade name</span>
-
-<span class="co"># spelling from different languages and dyslexia are no problem</span>
-<span class="fu"><a href="ab_property.html">ab_atc</a></span><span class="op">(</span><span class="st">"ceftriaxon"</span><span class="op">)</span>
-<span class="fu"><a href="ab_property.html">ab_atc</a></span><span class="op">(</span><span class="st">"cephtriaxone"</span><span class="op">)</span> <span class="co"># small spelling error</span>
-<span class="fu"><a href="ab_property.html">ab_atc</a></span><span class="op">(</span><span class="st">"cephthriaxone"</span><span class="op">)</span> <span class="co"># or a bit more severe</span>
-<span class="fu"><a href="ab_property.html">ab_atc</a></span><span class="op">(</span><span class="st">"seephthriaaksone"</span><span class="op">)</span> <span class="co"># and even this works</span>
-
-<span class="co"># use ab_* functions to get a specific properties (see ?ab_property);</span>
-<span class="co"># they use as.ab() internally:</span>
-<span class="fu"><a href="ab_property.html">ab_name</a></span><span class="op">(</span><span class="st">"J01FA01"</span><span class="op">)</span> <span class="co"># "Erythromycin"</span>
-<span class="fu"><a href="ab_property.html">ab_name</a></span><span class="op">(</span><span class="st">"eryt"</span><span class="op">)</span> <span class="co"># "Erythromycin"</span>
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
-
- <span class="co"># you can quickly rename <rsi> columns using dplyr >= 1.0.0:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/rename.html" class="external-link">rename_with</a></span><span class="op">(</span><span class="va">as.ab</span>, <span class="fu">where</span><span class="op">(</span><span class="va">is.rsi</span><span class="op">)</span><span class="op">)</span>
-
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
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- <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2>
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- <h1>Transform Input to Disk Diffusion Diameters</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/disk.R" class="external-link"><code>R/disk.R</code></a></small>
- <div class="hidden name"><code>as.disk.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>This transforms a vector to a new class <code>disk</code>, which is a disk diffusion growth zone size (around an antibiotic disk) in millimetres between 6 and 50.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">as.disk</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="va">NA_disk_</span>
-
-<span class="fu">is.disk</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>An object of class <code>disk</code> (inherits from <code>integer</code>) of length 1.</p>
- </div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>vector</p></dd>
-<dt>na.rm</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> indicating whether missing values should be removed</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> with additional class <code>disk</code></p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>Interpret disk values as RSI values with <code><a href="as.rsi.html">as.rsi()</a></code>. It supports guidelines from EUCAST and CLSI.</p>
-<p><code>NA_disk_</code> is a missing value of the new <code><disk></code> class.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
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- <h2>Read more on Our Website!</h2>
-
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-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="as.rsi.html">as.rsi()</a></code></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># \donttest{</span>
-<span class="co"># transform existing disk zones to the `disk` class</span>
-<span class="va">df</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>microorganism <span class="op">=</span> <span class="st">"E. coli"</span>,
- AMP <span class="op">=</span> <span class="fl">20</span>,
- CIP <span class="op">=</span> <span class="fl">14</span>,
- GEN <span class="op">=</span> <span class="fl">18</span>,
- TOB <span class="op">=</span> <span class="fl">16</span><span class="op">)</span>
-<span class="va">df</span><span class="op">[</span>, <span class="fl">2</span><span class="op">:</span><span class="fl">5</span><span class="op">]</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">df</span><span class="op">[</span>, <span class="fl">2</span><span class="op">:</span><span class="fl">5</span><span class="op">]</span>, <span class="va">as.disk</span><span class="op">)</span>
-<span class="co"># same with dplyr:</span>
-<span class="co"># df %>% mutate(across(AMP:TOB, as.disk))</span>
-
-<span class="co"># interpret disk values, see ?as.rsi</span>
-<span class="fu"><a href="as.rsi.html">as.rsi</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu">as.disk</span><span class="op">(</span><span class="fl">18</span><span class="op">)</span>,
- mo <span class="op">=</span> <span class="st">"Strep pneu"</span>, <span class="co"># `mo` will be coerced with as.mo()</span>
- ab <span class="op">=</span> <span class="st">"ampicillin"</span>, <span class="co"># and `ab` with as.ab()</span>
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span><span class="op">)</span>
-
-<span class="fu"><a href="as.rsi.html">as.rsi</a></span><span class="op">(</span><span class="va">df</span><span class="op">)</span>
-<span class="co"># }</span>
-</code></pre></div>
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diff --git a/docs/reference/as.mic.html b/docs/reference/as.mic.html
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- <div class="page-header">
- <h1>Transform Input to Minimum Inhibitory Concentrations (MIC)</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mic.R" class="external-link"><code>R/mic.R</code></a></small>
- <div class="hidden name"><code>as.mic.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>This transforms vectors to a new class <code>mic</code>, which treats the input as decimal numbers, while maintaining operators (such as ">=") and only allowing valid MIC values known to the field of (medical) microbiology.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">as.mic</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="va">NA_mic_</span>
-
-<span class="fu">is.mic</span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-
-<span class="co"># S3 method for mic</span>
-<span class="fu"><a href="https://rdrr.io/r/base/droplevels.html" class="external-link">droplevels</a></span><span class="op">(</span><span class="va">x</span>, as.mic <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> or <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> vector</p></dd>
-<dt>na.rm</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> indicating whether missing values should be removed</p></dd>
-<dt>as.mic</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the <code><mic></code> class should be kept, defaults to <code>FALSE</code></p></dd>
-<dt>...</dt>
-<dd><p>arguments passed on to methods</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with additional class <code>mic</code>, that in mathematical operations acts as decimal numbers. Bare in mind that the outcome of any mathematical operation on MICs will return a <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> value.</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>To interpret MIC values as RSI values, use <code><a href="as.rsi.html">as.rsi()</a></code> on MIC values. It supports guidelines from EUCAST (2011-2022) and CLSI (2011-2022).</p>
-<p>This class for MIC values is a quite a special data type: formally it is an ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with valid MIC values as <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> levels (to make sure only valid MIC values are retained), but for any mathematical operation it acts as decimal numbers:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>This makes it possible to maintain operators that often come with MIC values, such ">=" and "<=", even when filtering using <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> values in data analysis, e.g.:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>The following <a href="https://rdrr.io/r/base/groupGeneric.html" class="external-link">generic functions</a> are implemented for the MIC class: <code>!</code>, <code>!=</code>, <code>%%</code>, <code>%/%</code>, <code>&</code>, <code>*</code>, <code>+</code>, <code>-</code>, <code>/</code>, <code><</code>, <code><=</code>, <code>==</code>, <code>></code>, <code>>=</code>, <code>^</code>, <code>|</code>, <code><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">abs()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">acos()</a></code>, <code><a href="https://rdrr.io/r/base/Hyperbolic.html" class="external-link">acosh()</a></code>, <code><a href="https://rdrr.io/r/base/all.html" class="external-link">all()</a></code>, <code><a href="https://rdrr.io/r/base/any.html" class="external-link">any()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">asin()</a></code>, <code><a href="https://rdrr.io/r/base/Hyperbolic.html" class="external-link">asinh()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">atan()</a></code>, <code><a href="https://rdrr.io/r/base/Hyperbolic.html" class="external-link">atanh()</a></code>, <code><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">cos()</a></code>, <code><a href="https://rdrr.io/r/base/Hyperbolic.html" class="external-link">cosh()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">cospi()</a></code>, <code><a href="https://rdrr.io/r/base/cumsum.html" class="external-link">cummax()</a></code>, <code><a href="https://rdrr.io/r/base/cumsum.html" class="external-link">cummin()</a></code>, <code><a href="https://rdrr.io/r/base/cumsum.html" class="external-link">cumprod()</a></code>, <code><a href="https://rdrr.io/r/base/cumsum.html" class="external-link">cumsum()</a></code>, <code><a href="https://rdrr.io/r/base/Special.html" class="external-link">digamma()</a></code>, <code><a href="https://rdrr.io/r/base/Log.html" class="external-link">exp()</a></code>, <code><a href="https://rdrr.io/r/base/Log.html" class="external-link">expm1()</a></code>, <code><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor()</a></code>, <code><a href="https://rdrr.io/r/base/Special.html" class="external-link">gamma()</a></code>, <code><a href="https://rdrr.io/r/base/Special.html" class="external-link">lgamma()</a></code>, <code><a href="https://rdrr.io/r/base/Log.html" class="external-link">log()</a></code>, <code><a href="https://rdrr.io/r/base/Log.html" class="external-link">log1p()</a></code>, <code><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2()</a></code>, <code><a href="https://rdrr.io/r/base/Log.html" class="external-link">log10()</a></code>, <code><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max()</a></code>, <code><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean()</a></code>, <code><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">min()</a></code>, <code><a href="https://rdrr.io/r/base/prod.html" class="external-link">prod()</a></code>, <code><a href="https://rdrr.io/r/base/range.html" class="external-link">range()</a></code>, <code><a href="https://rdrr.io/r/base/Round.html" class="external-link">round()</a></code>, <code><a href="https://rdrr.io/r/base/sign.html" class="external-link">sign()</a></code>, <code><a href="https://rdrr.io/r/base/Round.html" class="external-link">signif()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">sin()</a></code>, <code><a href="https://rdrr.io/r/base/Hyperbolic.html" class="external-link">sinh()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">sinpi()</a></code>, <code><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">sqrt()</a></code>, <code><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">tan()</a></code>, <code><a href="https://rdrr.io/r/base/Hyperbolic.html" class="external-link">tanh()</a></code>, <code><a href="https://rdrr.io/r/base/Trig.html" class="external-link">tanpi()</a></code>, <code><a href="https://rdrr.io/r/base/Special.html" class="external-link">trigamma()</a></code> and <code><a href="https://rdrr.io/r/base/Round.html" class="external-link">trunc()</a></code>. Some functions of the <code>stats</code> package are also implemented: <code><a href="https://rdrr.io/r/stats/median.html" class="external-link">median()</a></code>, <code><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile()</a></code>, <code><a href="https://rdrr.io/r/stats/mad.html" class="external-link">mad()</a></code>, <code><a href="https://rdrr.io/r/stats/IQR.html" class="external-link">IQR()</a></code>, <code><a href="https://rdrr.io/r/stats/fivenum.html" class="external-link">fivenum()</a></code>. Also, <code><a href="https://rdrr.io/r/grDevices/boxplot.stats.html" class="external-link">boxplot.stats()</a></code> is supported. Since <code><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd()</a></code> and <code><a href="https://rdrr.io/r/stats/cor.html" class="external-link">var()</a></code> are non-generic functions, these could not be extended. Use <code><a href="https://rdrr.io/r/stats/mad.html" class="external-link">mad()</a></code> as an alternative, or use e.g. <code>sd(as.numeric(x))</code> where <code>x</code> is your vector of MIC values.</p>
-<p>Using <code><a href="https://rdrr.io/r/base/double.html" class="external-link">as.double()</a></code> or <code><a href="https://rdrr.io/r/base/numeric.html" class="external-link">as.numeric()</a></code> on MIC values will remove the operators and return a numeric vector. Do <strong>not</strong> use <code><a href="https://rdrr.io/r/base/integer.html" class="external-link">as.integer()</a></code> on MIC values as by the <span style="R">R</span> convention on <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a>s, it will return the index of the factor levels (which is often useless for regular users).</p>
-<p>Use <code><a href="https://rdrr.io/r/base/droplevels.html" class="external-link">droplevels()</a></code> to drop unused levels. At default, it will return a plain factor. Use <code>droplevels(..., as.mic = TRUE)</code> to maintain the <code><mic></code> class.</p>
-<p><code>NA_mic_</code> is a missing value of the new <code><mic></code> class, analogous to e.g. base <span style="R">R</span>'s <code><a href="https://rdrr.io/r/base/NA.html" class="external-link">NA_character_</a></code>.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="as.rsi.html">as.rsi()</a></code></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">mic_data</span> <span class="op"><-</span> <span class="fu">as.mic</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">">=32"</span>, <span class="st">"1.0"</span>, <span class="st">"1"</span>, <span class="st">"1.00"</span>, <span class="fl">8</span>, <span class="st">"<=0.128"</span>, <span class="st">"8"</span>, <span class="st">"16"</span>, <span class="st">"16"</span><span class="op">)</span><span class="op">)</span>
-<span class="fu">is.mic</span><span class="op">(</span><span class="va">mic_data</span><span class="op">)</span>
-
-<span class="co"># this can also coerce combined MIC/RSI values:</span>
-<span class="fu">as.mic</span><span class="op">(</span><span class="st">"<=0.002; S"</span><span class="op">)</span> <span class="co"># will return <=0.002</span>
-
-<span class="co"># mathematical processing treats MICs as [numeric] values</span>
-<span class="fu"><a href="https://rdrr.io/r/stats/fivenum.html" class="external-link">fivenum</a></span><span class="op">(</span><span class="va">mic_data</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile</a></span><span class="op">(</span><span class="va">mic_data</span><span class="op">)</span>
-<span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="va">mic_data</span> <span class="op"><</span> <span class="fl">512</span><span class="op">)</span>
-
-<span class="co"># interpret MIC values</span>
-<span class="fu"><a href="as.rsi.html">as.rsi</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu">as.mic</span><span class="op">(</span><span class="fl">2</span><span class="op">)</span>,
- mo <span class="op">=</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"S. pneumoniae"</span><span class="op">)</span>,
- ab <span class="op">=</span> <span class="st">"AMX"</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span><span class="op">)</span>
-<span class="fu"><a href="as.rsi.html">as.rsi</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu">as.mic</span><span class="op">(</span><span class="fl">4</span><span class="op">)</span>,
- mo <span class="op">=</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"S. pneumoniae"</span><span class="op">)</span>,
- ab <span class="op">=</span> <span class="st">"AMX"</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span><span class="op">)</span>
-
-<span class="co"># plot MIC values, see ?plot</span>
-<span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">mic_data</span><span class="op">)</span>
-<span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">mic_data</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span>
-</code></pre></div>
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diff --git a/docs/reference/as.mo.html b/docs/reference/as.mo.html
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- </header><div class="row">
- <div class="col-md-9 contents">
- <div class="page-header">
- <h1>Transform Input to a Microorganism Code</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mo.R" class="external-link"><code>R/mo.R</code></a></small>
- <div class="hidden name"><code>as.mo.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Use this function to determine a valid microorganism code (<code>mo</code>). Determination is done using intelligent rules and the complete taxonomic kingdoms Bacteria, Chromista, Protozoa, Archaea and most microbial species from the kingdom Fungi (see <em>Source</em>). The input can be almost anything: a full name (like <code>"Staphylococcus aureus"</code>), an abbreviated name (such as <code>"S. aureus"</code>), an abbreviation known in the field (such as <code>"MRSA"</code>), or just a genus. See <em>Examples</em>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">as.mo</span><span class="op">(</span></span>
-<span> <span class="va">x</span>,</span>
-<span> Becker <span class="op">=</span> <span class="cn">FALSE</span>,</span>
-<span> Lancefield <span class="op">=</span> <span class="cn">FALSE</span>,</span>
-<span> allow_uncertain <span class="op">=</span> <span class="cn">TRUE</span>,</span>
-<span> reference_df <span class="op">=</span> <span class="fu"><a href="mo_source.html">get_mo_source</a></span><span class="op">(</span><span class="op">)</span>,</span>
-<span> ignore_pattern <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"AMR_ignore_pattern"</span><span class="op">)</span>,</span>
-<span> language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,</span>
-<span> info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>,</span>
-<span> <span class="va">...</span></span>
-<span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">is.mo</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_failures</span><span class="op">(</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_uncertainties</span><span class="op">(</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_renamed</span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector or a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with one or two columns</p></dd>
-
-
-<dt>Becker</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether staphylococci should be categorised into coagulase-negative staphylococci ("CoNS") and coagulase-positive staphylococci ("CoPS") instead of their own species, according to Karsten Becker <em>et al.</em> (1,2,3).</p>
-<p>This excludes <em>Staphylococcus aureus</em> at default, use <code>Becker = "all"</code> to also categorise <em>S. aureus</em> as "CoPS".</p></dd>
-
-
-<dt>Lancefield</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a beta-haemolytic <em>Streptococcus</em> should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield (4). These streptococci will be categorised in their first group, e.g. <em>Streptococcus dysgalactiae</em> will be group C, although officially it was also categorised into groups G and L.</p>
-<p>This excludes enterococci at default (who are in group D), use <code>Lancefield = "all"</code> to also categorise all enterococci as group D.</p></dd>
-
-
-<dt>allow_uncertain</dt>
-<dd><p>a number between <code>0</code> (or <code>"none"</code>) and <code>3</code> (or <code>"all"</code>), or <code>TRUE</code> (= <code>2</code>) or <code>FALSE</code> (= <code>0</code>) to indicate whether the input should be checked for less probable results, see <em>Details</em></p></dd>
-
-
-<dt>reference_df</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> to be used for extra reference when translating <code>x</code> to a valid <code>mo</code>. See <code><a href="mo_source.html">set_mo_source()</a></code> and <code><a href="mo_source.html">get_mo_source()</a></code> to automate the usage of your own codes (e.g. used in your analysis or organisation).</p></dd>
-
-
-<dt>ignore_pattern</dt>
-<dd><p>a regular expression (case-insensitive) of which all matches in <code>x</code> must return <code>NA</code>. This can be convenient to exclude known non-relevant input and can also be set with the option <code>AMR_ignore_pattern</code>, e.g. <code>options(AMR_ignore_pattern = "(not reported|contaminated flora)")</code>.</p></dd>
-
-
-<dt>language</dt>
-<dd><p>language to translate text like "no growth", which defaults to the system language (see <code><a href="translate.html">get_AMR_locale()</a></code>)</p></dd>
-
-
-<dt>info</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate if a progress bar should be printed if more than 25 items are to be coerced, defaults to <code>TRUE</code> only in interactive mode</p></dd>
-
-
-<dt>...</dt>
-<dd><p>other arguments passed on to functions</p></dd>
-
-</dl></div>
- <div id="value">
- <h2>Value</h2>
-
-
-<p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a></p>
-<p></p>
-<p><a href="https://rdrr.io/r/base/vector.html" class="external-link">vector</a> with additional class <code>mo</code></p>
-
-
- </div>
- <div id="details">
- <h2>Details</h2>
-
-<div class="section">
-<h3 id="general-info">General Info<a class="anchor" aria-label="anchor" href="#general-info"></a></h3>
-
-
-<p>A microorganism (MO) code from this package (class: <code>mo</code>) is human readable and typically looks like these examples:</p>
-<p></p><div class="sourceCode"><pre><code><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a> Code Full name</span>
-<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a> <span class="sc">---------------</span> <span class="sc">--------------------------------------</span></span>
-<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a> B_KLBSL Klebsiella</span>
-<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a> B_KLBSL_PNMN Klebsiella pneumoniae</span>
-<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a> B_KLBSL_PNMN_RHNS Klebsiella pneumoniae rhinoscleromatis</span>
-<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a> <span class="sc">|</span> <span class="er">|</span> <span class="er">|</span> <span class="er">|</span></span>
-<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a> <span class="er">|</span> <span class="er">|</span> <span class="er">|</span> <span class="er">|</span></span>
-<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a> <span class="er">|</span> <span class="er">|</span> <span class="er">|</span> \<span class="sc">--</span><span class="ot">-></span> subspecies, a <span class="dv">4-5</span> letter acronym</span>
-<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a> <span class="sc">|</span> <span class="er">|</span> \<span class="sc">---</span><span class="ot">-></span> species, a <span class="dv">4-5</span> letter acronym</span>
-<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a> <span class="sc">|</span> \<span class="sc">---</span><span class="ot">-></span> genus, a <span class="dv">5-7</span> letter acronym</span>
-<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a> \<span class="sc">---</span><span class="ot">-></span> taxonomic kingdom<span class="sc">:</span> <span class="fu">A</span> (Archaea), <span class="fu">AN</span> (Animalia), <span class="fu">B</span> (Bacteria),</span>
-<span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">C</span> (Chromista), <span class="fu">F</span> (Fungi), <span class="fu">P</span> (Protozoa)</span></code></pre><p></p></div>
-<p>Values that cannot be coerced will be considered 'unknown' and will get the MO code <code>UNKNOWN</code>.</p>
-<p>Use the <code><a href="mo_property.html">mo_*</a></code> functions to get properties based on the returned code, see <em>Examples</em>.</p>
-<p>The algorithm uses data from the Catalogue of Life (see below) and from one other source (see <a href="microorganisms.html">microorganisms</a>).</p>
-<p>The <code>as.mo()</code> function uses several coercion rules for fast and logical results. It assesses the input matching criteria in the following order:</p><ol><li><p>Human pathogenic prevalence: the function starts with more prevalent microorganisms, followed by less prevalent ones;</p></li>
-<li><p>Taxonomic kingdom: the function starts with determining Bacteria, then Fungi, then Protozoa, then others;</p></li>
-<li><p>Breakdown of input values to identify possible matches.</p></li>
-</ol><p>This will lead to the effect that e.g. <code>"E. coli"</code> (a microorganism highly prevalent in humans) will return the microbial ID of <em>Escherichia coli</em> and not <em>Entamoeba coli</em> (a microorganism less prevalent in humans), although the latter would alphabetically come first.</p>
-</div>
-
-<div class="section">
-<h3 id="coping-with-uncertain-results">Coping with Uncertain Results<a class="anchor" aria-label="anchor" href="#coping-with-uncertain-results"></a></h3>
-
-
-<p>In addition, the <code>as.mo()</code> function can differentiate four levels of uncertainty to guess valid results:</p><ul><li><p>Uncertainty level 0: no additional rules are applied;</p></li>
-<li><p>Uncertainty level 1: allow previously accepted (but now invalid) taxonomic names and minor spelling errors;</p></li>
-<li><p>Uncertainty level 2: allow all of level 1, strip values between brackets, inverse the words of the input, strip off text elements from the end keeping at least two elements;</p></li>
-<li><p>Uncertainty level 3: allow all of level 1 and 2, strip off text elements from the end, allow any part of a taxonomic name.</p></li>
-</ul><p>The level of uncertainty can be set using the argument <code>allow_uncertain</code>. The default is <code>allow_uncertain = TRUE</code>, which is equal to uncertainty level 2. Using <code>allow_uncertain = FALSE</code> is equal to uncertainty level 0 and will skip all rules. You can also use e.g. <code>as.mo(..., allow_uncertain = 1)</code> to only allow up to level 1 uncertainty.</p>
-<p>With the default setting (<code>allow_uncertain = TRUE</code>, level 2), below examples will lead to valid results:</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_STRPT_GRPB</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_AURS</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_GNRR</code>) needs review.</p></li>
-</ul><p>There are three helper functions that can be run after using the <code>as.mo()</code> function:</p><ul><li><p>Use <code>mo_uncertainties()</code> to get a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> that prints in a pretty format with all taxonomic names that were guessed. The output contains the matching score for all matches (see <em>Matching Score for Microorganisms</em> below).</p></li>
-<li><p>Use <code>mo_failures()</code> to get a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> <a href="https://rdrr.io/r/base/vector.html" class="external-link">vector</a> with all values that could not be coerced to a valid value.</p></li>
-<li><p>Use <code>mo_renamed()</code> to get a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with all values that could be coerced based on old, previously accepted taxonomic names.</p></li>
-</ul></div>
-
-<div class="section">
-<h3 id="microbial-prevalence-of-pathogens-in-humans">Microbial Prevalence of Pathogens in Humans<a class="anchor" aria-label="anchor" href="#microbial-prevalence-of-pathogens-in-humans"></a></h3>
-
-
-<p>The intelligent rules consider the prevalence of microorganisms in humans grouped into three groups, which is available as the <code>prevalence</code> columns in the <a href="microorganisms.html">microorganisms</a> and <a href="microorganisms.old.html">microorganisms.old</a> data sets. The grouping into human pathogenic prevalence is explained in the section <em>Matching Score for Microorganisms</em> below.</p>
-</div>
-
- </div>
- <div id="source">
- <h2>Source</h2>
-
-
-<ol><li><p>Becker K <em>et al.</em> <strong>Coagulase-Negative Staphylococci</strong>. 2014. Clin Microbiol Rev. 27(4): 870-926; <a href="https://doi.org/10.1128/CMR.00109-13" class="external-link">doi:10.1128/CMR.00109-13</a></p></li>
-<li><p>Becker K <em>et al.</em> <strong>Implications of identifying the recently defined members of the <em>S. aureus</em> complex, <em>S. argenteus</em> and <em>S. schweitzeri</em>: A position paper of members of the ESCMID Study Group for staphylococci and Staphylococcal Diseases (ESGS).</strong> 2019. Clin Microbiol Infect; <a href="https://doi.org/10.1016/j.cmi.2019.02.028" class="external-link">doi:10.1016/j.cmi.2019.02.028</a></p></li>
-<li><p>Becker K <em>et al.</em> <strong>Emergence of coagulase-negative staphylococci</strong> 2020. Expert Rev Anti Infect Ther. 18(4):349-366; <a href="https://doi.org/10.1080/14787210.2020.1730813" class="external-link">doi:10.1080/14787210.2020.1730813</a></p></li>
-<li><p>Lancefield RC <strong>A serological differentiation of human and other groups of hemolytic streptococci</strong>. 1933. J Exp Med. 57(4): 571-95; <a href="https://doi.org/10.1084/jem.57.4.571" class="external-link">doi:10.1084/jem.57.4.571</a></p></li>
-<li><p>Catalogue of Life: 2019 Annual Checklist, <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a></p></li>
-<li><p>List of Prokaryotic names with Standing in Nomenclature (5 October 2021), <a href="https://doi.org/10.1099/ijsem.0.004332" class="external-link">doi:10.1099/ijsem.0.004332</a></p></li>
-<li><p>US Edition of SNOMED CT from 1 September 2020, retrieved from the Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS), OID 2.16.840.1.114222.4.11.1009, version 12; url: <a href="https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009" class="external-link">https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009</a></p></li>
-</ol></div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="matching-score-for-microorganisms">
- <h2>Matching Score for Microorganisms</h2>
-
-
-<p>With ambiguous user input in <code>as.mo()</code> and all the <code><a href="mo_property.html">mo_*</a></code> functions, the returned results are chosen based on their matching score using <code><a href="mo_matching_score.html">mo_matching_score()</a></code>. This matching score \(m\), is calculated as:</p>
-<p><img src="figures/mo_matching_score.png" width="300" alt="mo matching score"></p>
-<p>where:</p><ul><li><p><i>x</i> is the user input;</p></li>
-<li><p><i>n</i> is a taxonomic name (genus, species, and subspecies);</p></li>
-<li><p><i>l<sub>n</sub></i> is the length of <i>n</i>;</p></li>
-<li><p><i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance" class="external-link">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;</p></li>
-<li><p><i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;</p></li>
-<li><p><i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
-</ul><p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>, <em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
-<p>All characters in \(x\) and \(n\) are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.</p>
-<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.079\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
-<p>Since <code>AMR</code> version 1.8.1, common microorganism abbreviations are ignored in determining the matching score. These abbreviations are currently: AIEC, ATEC, BORSA, CRSM, DAEC, EAEC, EHEC, EIEC, EPEC, ETEC, GISA, MRPA, MRSA, MRSE, MSSA, MSSE, NMEC, PISP, PRSP, STEC, UPEC, VISA, VISP, VRE, VRSA and VRSP.</p>
- </div>
- <div id="catalogue-of-life">
- <h2>Catalogue of Life</h2>
-
-
-<p><img src="figures/logo_col.png" height="40" style='margin-bottom:"5"'><br>
-This package contains the complete taxonomic tree of almost all microorganisms (~71,000 species) from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a>). The CoL is the most comprehensive and authoritative global index of species currently available. Nonetheless, we supplemented the CoL data with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de" class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/CatalogueOfLife/general" class="external-link">CoL+ project</a> is finished, which we await.</p>
-<p><a href="catalogue_of_life.html">Click here</a> for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with <code><a href="catalogue_of_life_version.html">catalogue_of_life_version()</a></code>.</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><a href="microorganisms.html">microorganisms</a> for the <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> that is being used to determine ID's.</p>
-<p>The <code><a href="mo_property.html">mo_*</a></code> functions (such as <code><a href="mo_property.html">mo_genus()</a></code>, <code><a href="mo_property.html">mo_gramstain()</a></code>) to get properties based on the returned code.</p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># \donttest{</span></span>
-<span><span class="co"># These examples all return "B_STPHY_AURS", the ID of S. aureus:</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"sau"</span><span class="op">)</span> <span class="co"># WHONET code</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"stau"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"STAU"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"staaur"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"S aureus"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"Staphylococcus aureus (MRSA)"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"Zthafilokkoockus oureuz"</span><span class="op">)</span> <span class="co"># handles incorrect spelling</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"MRSA"</span><span class="op">)</span> <span class="co"># Methicillin Resistant S. aureus</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"VISA"</span><span class="op">)</span> <span class="co"># Vancomycin Intermediate S. aureus</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"VRSA"</span><span class="op">)</span> <span class="co"># Vancomycin Resistant S. aureus</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="fl">115329001</span><span class="op">)</span> <span class="co"># SNOMED CT code</span></span>
-<span></span>
-<span><span class="co"># Dyslexia is no problem - these all work:</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"Ureaplasma urealyticum"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"Ureaplasma urealyticus"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"Ureaplasmium urealytica"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"Ureaplazma urealitycium"</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"Streptococcus group A"</span><span class="op">)</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"GAS"</span><span class="op">)</span> <span class="co"># Group A Streptococci</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"GBS"</span><span class="op">)</span> <span class="co"># Group B Streptococci</span></span>
-<span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"S. epidermidis"</span><span class="op">)</span> <span class="co"># will remain species: B_STPHY_EPDR</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"S. epidermidis"</span>, Becker <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="co"># will not remain species: B_STPHY_CONS</span></span>
-<span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"S. pyogenes"</span><span class="op">)</span> <span class="co"># will remain species: B_STRPT_PYGN</span></span>
-<span><span class="fu">as.mo</span><span class="op">(</span><span class="st">"S. pyogenes"</span>, Lancefield <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="co"># will not remain species: B_STRPT_GRPA</span></span>
-<span></span>
-<span><span class="co"># All mo_* functions use as.mo() internally too (see ?mo_property):</span></span>
-<span><span class="fu"><a href="mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># returns "Escherichia"</span></span>
-<span><span class="fu"><a href="mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># returns "Gram negative"</span></span>
-<span><span class="fu"><a href="mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="st">"E. coli"</span>, <span class="st">"vanco"</span><span class="op">)</span> <span class="co"># returns TRUE</span></span>
-<span><span class="co"># }</span></span></code></pre></div>
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- <h1>Interpret MIC and Disk Values, or Clean Raw R/SI Data</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/rsi.R" class="external-link"><code>R/rsi.R</code></a></small>
- <div class="hidden name"><code>as.rsi.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI, or clean up existing R/SI values. This transforms the input to a new class <code>rsi</code>, which is an ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with levels <code>S < I < R</code>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">as.rsi</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="va">NA_rsi_</span>
-
-<span class="fu">is.rsi</span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-
-<span class="fu">is.rsi.eligible</span><span class="op">(</span><span class="va">x</span>, threshold <span class="op">=</span> <span class="fl">0.05</span><span class="op">)</span>
-
-<span class="co"># S3 method for mic</span>
-<span class="fu">as.rsi</span><span class="op">(</span>
- <span class="va">x</span>,
- mo <span class="op">=</span> <span class="cn">NULL</span>,
- ab <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span>,
- uti <span class="op">=</span> <span class="cn">FALSE</span>,
- conserve_capped_values <span class="op">=</span> <span class="cn">FALSE</span>,
- add_intrinsic_resistance <span class="op">=</span> <span class="cn">FALSE</span>,
- reference_data <span class="op">=</span> <span class="fu">AMR</span><span class="fu">::</span><span class="va"><a href="rsi_translation.html">rsi_translation</a></span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for disk</span>
-<span class="fu">as.rsi</span><span class="op">(</span>
- <span class="va">x</span>,
- mo <span class="op">=</span> <span class="cn">NULL</span>,
- ab <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span>,
- uti <span class="op">=</span> <span class="cn">FALSE</span>,
- add_intrinsic_resistance <span class="op">=</span> <span class="cn">FALSE</span>,
- reference_data <span class="op">=</span> <span class="fu">AMR</span><span class="fu">::</span><span class="va"><a href="rsi_translation.html">rsi_translation</a></span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for data.frame</span>
-<span class="fu">as.rsi</span><span class="op">(</span>
- <span class="va">x</span>,
- <span class="va">...</span>,
- col_mo <span class="op">=</span> <span class="cn">NULL</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span>,
- uti <span class="op">=</span> <span class="cn">NULL</span>,
- conserve_capped_values <span class="op">=</span> <span class="cn">FALSE</span>,
- add_intrinsic_resistance <span class="op">=</span> <span class="cn">FALSE</span>,
- reference_data <span class="op">=</span> <span class="fu">AMR</span><span class="fu">::</span><span class="va"><a href="rsi_translation.html">rsi_translation</a></span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>An object of class <code>rsi</code> (inherits from <code>ordered</code>, <code>factor</code>) of length 1.</p>
- </div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>vector of values (for class <code><a href="as.mic.html">mic</a></code>: MIC values in mg/L, for class <code><a href="as.disk.html">disk</a></code>: a disk diffusion radius in millimetres)</p></dd>
-<dt>...</dt>
-<dd><p>for using on a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>: names of columns to apply <code>as.rsi()</code> on (supports tidy selection such as <code>column1:column4</code>). Otherwise: arguments passed on to methods.</p></dd>
-<dt>threshold</dt>
-<dd><p>maximum fraction of invalid antimicrobial interpretations of <code>x</code>, see <em>Examples</em></p></dd>
-<dt>mo</dt>
-<dd><p>any (vector of) text that can be coerced to valid microorganism codes with <code><a href="as.mo.html">as.mo()</a></code>, can be left empty to determine it automatically</p></dd>
-<dt>ab</dt>
-<dd><p>any (vector of) text that can be coerced to a valid antimicrobial code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
-<dt>guideline</dt>
-<dd><p>defaults to EUCAST 2022 (the latest implemented EUCAST guideline in the <a href="rsi_translation.html">rsi_translation</a> data set), supports EUCAST (2011-2022) and CLSI (2011-2022), see <em>Details</em></p></dd>
-<dt>uti</dt>
-<dd><p>(Urinary Tract Infection) A vector with <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a>s (<code>TRUE</code> or <code>FALSE</code>) to specify whether a UTI specific interpretation from the guideline should be chosen. For using <code>as.rsi()</code> on a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>, this can also be a column containing <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a>s or when left blank, the data set will be searched for a column 'specimen', and rows within this column containing 'urin' (such as 'urine', 'urina') will be regarded isolates from a UTI. See <em>Examples</em>.</p></dd>
-<dt>conserve_capped_values</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that MIC values starting with <code>">"</code> (but not <code>">="</code>) must always return "R" , and that MIC values starting with <code>"<"</code> (but not <code>"<="</code>) must always return "S"</p></dd>
-<dt>add_intrinsic_resistance</dt>
-<dd><p><em>(only useful when using a EUCAST guideline)</em> a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in <em>Klebsiella</em> species. Determination is based on the <a href="intrinsic_resistant.html">intrinsic_resistant</a> data set, that itself is based on <a href="https://www.eucast.org/expert_rules_and_expected_phenotypes/" class="external-link">'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3</a> (2021).</p></dd>
-<dt>reference_data</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> to be used for interpretation, which defaults to the <a href="rsi_translation.html">rsi_translation</a> data set. Changing this argument allows for using own interpretation guidelines. This argument must contain a data set that is equal in structure to the <a href="rsi_translation.html">rsi_translation</a> data set (same column names and column types). Please note that the <code>guideline</code> argument will be ignored when <code>reference_data</code> is manually set.</p></dd>
-<dt>col_mo</dt>
-<dd><p>column name of the IDs of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>), defaults to the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with new class <code><rsi></code></p>
- </div>
- <div id="details">
- <h2>Details</h2>
-
-<div class="section">
-<h3 id="how-it-works">How it Works<a class="anchor" aria-label="anchor" href="#how-it-works"></a></h3>
-
-
-<p>The <code>as.rsi()</code> function works in four ways:</p><ol><li><p>For <strong>cleaning raw / untransformed data</strong>. The data will be cleaned to only contain values S, I and R and will try its best to determine this with some intelligence. For example, mixed values with R/SI interpretations and MIC values such as <code>"<0.25; S"</code> will be coerced to <code>"S"</code>. Combined interpretations for multiple test methods (as seen in laboratory records) such as <code>"S; S"</code> will be coerced to <code>"S"</code>, but a value like <code>"S; I"</code> will return <code>NA</code> with a warning that the input is unclear.</p></li>
-<li><p>For <strong>interpreting minimum inhibitory concentration (MIC) values</strong> according to EUCAST or CLSI. You must clean your MIC values first using <code><a href="as.mic.html">as.mic()</a></code>, that also gives your columns the new data class <code><a href="as.mic.html">mic</a></code>. Also, be sure to have a column with microorganism names or codes. It will be found automatically, but can be set manually using the <code>mo</code> argument.</p><ul><li><p>Using <code>dplyr</code>, R/SI interpretation can be done very easily with either:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div></li>
-<li><p>Operators like "<=" will be stripped before interpretation. When using <code>conserve_capped_values = TRUE</code>, an MIC value of e.g. ">2" will always return "R", even if the breakpoint according to the chosen guideline is ">=4". This is to prevent that capped values from raw laboratory data would not be treated conservatively. The default behaviour (<code>conserve_capped_values = FALSE</code>) considers ">2" to be lower than ">=4" and might in this case return "S" or "I".</p></li>
-</ul></li>
-<li><p>For <strong>interpreting disk diffusion diameters</strong> according to EUCAST or CLSI. You must clean your disk zones first using <code><a href="as.disk.html">as.disk()</a></code>, that also gives your columns the new data class <code><a href="as.disk.html">disk</a></code>. Also, be sure to have a column with microorganism names or codes. It will be found automatically, but can be set manually using the <code>mo</code> argument.</p><ul><li><p>Using <code>dplyr</code>, R/SI interpretation can be done very easily with either:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div></li>
-</ul></li>
-<li><p>For <strong>interpreting a complete data set</strong>, with automatic determination of MIC values, disk diffusion diameters, microorganism names or codes, and antimicrobial test results. This is done very simply by running <code>as.rsi(your_data)</code>.</p></li>
-</ol></div>
-
-<div class="section">
-<h3 id="supported-guidelines">Supported Guidelines<a class="anchor" aria-label="anchor" href="#supported-guidelines"></a></h3>
-
-
-<p>For interpreting MIC values as well as disk diffusion diameters, currently implemented guidelines are EUCAST (2011-2022) and CLSI (2011-2022).</p>
-<p>Thus, the <code>guideline</code> argument must be set to e.g., <code>"EUCAST 2022"</code> or <code>"CLSI 2022"</code>. By simply using <code>"EUCAST"</code> (the default) or <code>"CLSI"</code> as input, the latest included version of that guideline will automatically be selected. You can set your own data set using the <code>reference_data</code> argument. The <code>guideline</code> argument will then be ignored.</p>
-</div>
-
-<div class="section">
-<h3 id="after-interpretation">After Interpretation<a class="anchor" aria-label="anchor" href="#after-interpretation"></a></h3>
-
-
-<p>After using <code>as.rsi()</code>, you can use the <code><a href="eucast_rules.html">eucast_rules()</a></code> defined by EUCAST to (1) apply inferred susceptibility and resistance based on results of other antimicrobials and (2) apply intrinsic resistance based on taxonomic properties of a microorganism.</p>
-</div>
-
-<div class="section">
-<h3 id="machine-readable-interpretation-guidelines">Machine-Readable Interpretation Guidelines<a class="anchor" aria-label="anchor" href="#machine-readable-interpretation-guidelines"></a></h3>
-
-
-<p>The repository of this package <a href="https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt" class="external-link">contains a machine-readable version</a> of all guidelines. This is a CSV file consisting of 20,369 rows and 11 columns. This file is machine-readable, since it contains one row for every unique combination of the test method (MIC or disk diffusion), the antimicrobial agent and the microorganism. <strong>This allows for easy implementation of these rules in laboratory information systems (LIS)</strong>. Note that it only contains interpretation guidelines for humans - interpretation guidelines from CLSI for animals were removed.</p>
-</div>
-
-<div class="section">
-<h3 id="other">Other<a class="anchor" aria-label="anchor" href="#other"></a></h3>
-
-
-<p>The function <code>is.rsi()</code> detects if the input contains class <code><rsi></code>. If the input is a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>, it iterates over all columns and returns a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector.</p>
-<p>The function <code>is.rsi.eligible()</code> returns <code>TRUE</code> when a columns contains at most 5% invalid antimicrobial interpretations (not S and/or I and/or R), and <code>FALSE</code> otherwise. The threshold of 5% can be set with the <code>threshold</code> argument. If the input is a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>, it iterates over all columns and returns a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector.</p>
-</div>
-
-<p><code>NA_rsi_</code> is a missing value of the new <code><rsi></code> class, analogous to e.g. base <span style="R">R</span>'s <code><a href="https://rdrr.io/r/base/NA.html" class="external-link">NA_character_</a></code>.</p>
- </div>
- <div id="interpretation-of-r-and-s-i">
- <h2>Interpretation of R and S/I</h2>
-
-
-<p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (<a href="https://www.eucast.org/newsiandr/" class="external-link">https://www.eucast.org/newsiandr/</a>).</p><ul><li><p><strong>R = Resistant</strong><br>
-A microorganism is categorised as <em>Resistant</em> when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p></li>
-<li><p><strong>S = Susceptible</strong><br>
-A microorganism is categorised as <em>Susceptible, standard dosing regimen</em>, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
-<li><p><strong>I = Susceptible, Increased exposure</strong><br>
-A microorganism is categorised as <em>Susceptible, Increased exposure</em> when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.</p></li>
-</ul><p>This AMR package honours this (new) insight. Use <code><a href="proportion.html">susceptibility()</a></code> (equal to <code><a href="proportion.html">proportion_SI()</a></code>) to determine antimicrobial susceptibility and <code><a href="count.html">count_susceptible()</a></code> (equal to <code><a href="count.html">count_SI()</a></code>) to count susceptible isolates.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="as.mic.html">as.mic()</a></code>, <code><a href="as.disk.html">as.disk()</a></code>, <code><a href="as.mo.html">as.mo()</a></code></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span> <span class="co"># see all R/SI results at a glance</span>
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://docs.ropensci.org/skimr/" class="external-link">"skimr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="co"># class <rsi> supported in skim() too:</span>
- <span class="fu"><a href="https://docs.ropensci.org/skimr/reference/skim.html" class="external-link">skim</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-<span class="co"># For INTERPRETING disk diffusion and MIC values -----------------------</span>
-
-<span class="co"># a whole data set, even with combined MIC values and disk zones</span>
-<span class="va">df</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>microorganism <span class="op">=</span> <span class="st">"Escherichia coli"</span>,
- AMP <span class="op">=</span> <span class="fu"><a href="as.mic.html">as.mic</a></span><span class="op">(</span><span class="fl">8</span><span class="op">)</span>,
- CIP <span class="op">=</span> <span class="fu"><a href="as.mic.html">as.mic</a></span><span class="op">(</span><span class="fl">0.256</span><span class="op">)</span>,
- GEN <span class="op">=</span> <span class="fu"><a href="as.disk.html">as.disk</a></span><span class="op">(</span><span class="fl">18</span><span class="op">)</span>,
- TOB <span class="op">=</span> <span class="fu"><a href="as.disk.html">as.disk</a></span><span class="op">(</span><span class="fl">16</span><span class="op">)</span>,
- NIT <span class="op">=</span> <span class="fu"><a href="as.mic.html">as.mic</a></span><span class="op">(</span><span class="fl">32</span><span class="op">)</span>,
- ERY <span class="op">=</span> <span class="st">"R"</span><span class="op">)</span>
-<span class="fu">as.rsi</span><span class="op">(</span><span class="va">df</span><span class="op">)</span>
-
-<span class="co"># for single values</span>
-<span class="fu">as.rsi</span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="as.mic.html">as.mic</a></span><span class="op">(</span><span class="fl">2</span><span class="op">)</span>,
- mo <span class="op">=</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"S. pneumoniae"</span><span class="op">)</span>,
- ab <span class="op">=</span> <span class="st">"AMP"</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span><span class="op">)</span>
-
-<span class="fu">as.rsi</span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="as.disk.html">as.disk</a></span><span class="op">(</span><span class="fl">18</span><span class="op">)</span>,
- mo <span class="op">=</span> <span class="st">"Strep pneu"</span>, <span class="co"># `mo` will be coerced with as.mo()</span>
- ab <span class="op">=</span> <span class="st">"ampicillin"</span>, <span class="co"># and `ab` with as.ab()</span>
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span><span class="op">)</span>
-
-<span class="co"># \donttest{</span>
-<span class="co"># the dplyr way</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="va">is.mic</span>, <span class="va">as.rsi</span><span class="op">)</span>
- <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="as.mic.html">is.mic</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="op">|</span> <span class="fu"><a href="as.disk.html">is.disk</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span>
- <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu">where</span><span class="op">(</span><span class="va">is.mic</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span><span class="op">)</span>
- <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMP</span><span class="op">:</span><span class="va">TOB</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span>
- <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="va">AMP</span><span class="op">:</span><span class="va">TOB</span>, <span class="va">as.rsi</span><span class="op">)</span><span class="op">)</span>
-
- <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMP</span><span class="op">:</span><span class="va">TOB</span><span class="op">)</span>, <span class="va">as.rsi</span>, mo <span class="op">=</span> <span class="va">.</span><span class="op">$</span><span class="va">microorganism</span><span class="op">)</span>
-
- <span class="co"># to include information about urinary tract infections (UTI)</span>
- <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="st">"E. coli"</span>,
- NIT <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"<= 2"</span>, <span class="fl">32</span><span class="op">)</span>,
- from_the_bladder <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="cn">TRUE</span>, <span class="cn">FALSE</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">as.rsi</span><span class="op">(</span>uti <span class="op">=</span> <span class="st">"from_the_bladder"</span><span class="op">)</span>
-
- <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="st">"E. coli"</span>,
- NIT <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"<= 2"</span>, <span class="fl">32</span><span class="op">)</span>,
- specimen <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"urine"</span>, <span class="st">"blood"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">as.rsi</span><span class="op">(</span><span class="op">)</span> <span class="co"># automatically determines urine isolates</span>
-
- <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMP</span><span class="op">:</span><span class="va">NIT</span><span class="op">)</span>, <span class="va">as.rsi</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span>, uti <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>
-<span class="op">}</span>
-
-<span class="co"># For CLEANING existing R/SI values ------------------------------------</span>
-
-<span class="fu">as.rsi</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"S"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>, <span class="st">"A"</span>, <span class="st">"B"</span>, <span class="st">"C"</span><span class="op">)</span><span class="op">)</span>
-<span class="fu">as.rsi</span><span class="op">(</span><span class="st">"<= 0.002; S"</span><span class="op">)</span> <span class="co"># will return "S"</span>
-<span class="va">rsi_data</span> <span class="op"><-</span> <span class="fu">as.rsi</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"S"</span>, <span class="fl">474</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"I"</span>, <span class="fl">36</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"R"</span>, <span class="fl">370</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>
-<span class="fu">is.rsi</span><span class="op">(</span><span class="va">rsi_data</span><span class="op">)</span>
-<span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">rsi_data</span><span class="op">)</span> <span class="co"># for percentages</span>
-<span class="fu"><a href="https://rdrr.io/r/graphics/barplot.html" class="external-link">barplot</a></span><span class="op">(</span><span class="va">rsi_data</span><span class="op">)</span> <span class="co"># for frequencies</span>
-
-<span class="co"># the dplyr way</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">PEN</span><span class="op">:</span><span class="va">RIF</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span>
- <span class="co"># same: </span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">as.rsi</span><span class="op">(</span><span class="va">PEN</span><span class="op">:</span><span class="va">RIF</span><span class="op">)</span>
-
- <span class="co"># fastest way to transform all columns with already valid AMR results to class `rsi`:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="va">is.rsi.eligible</span>, <span class="va">as.rsi</span><span class="op">)</span>
-
- <span class="co"># since dplyr 1.0.0, this can also be: </span>
- <span class="co"># example_isolates %>%</span>
- <span class="co"># mutate(across(where(is.rsi.eligible), as.rsi))</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
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- <h1>Get ATC Properties from WHOCC Website</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/atc_online.R" class="external-link"><code>R/atc_online.R</code></a></small>
- <div class="hidden name"><code>atc_online.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Gets data from the WHOCC website to determine properties of an Anatomical Therapeutic Chemical (ATC) (e.g. an antibiotic), such as the name, defined daily dose (DDD) or standard unit.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">atc_online_property</span><span class="op">(</span>
- <span class="va">atc_code</span>,
- <span class="va">property</span>,
- administration <span class="op">=</span> <span class="st">"O"</span>,
- url <span class="op">=</span> <span class="st">"https://www.whocc.no/atc_ddd_index/?code=%s&showdescription=no"</span>,
- url_vet <span class="op">=</span> <span class="st">"https://www.whocc.no/atcvet/atcvet_index/?code=%s&showdescription=no"</span>
-<span class="op">)</span>
-
-<span class="fu">atc_online_groups</span><span class="op">(</span><span class="va">atc_code</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">atc_online_ddd</span><span class="op">(</span><span class="va">atc_code</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">atc_online_ddd_units</span><span class="op">(</span><span class="va">atc_code</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="source">
- <h2>Source</h2>
- <p><a href="https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/" class="external-link">https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/</a></p>
- </div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>atc_code</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vector) with ATC code(s) of antibiotics, will be coerced with <code><a href="as.ab.html">as.ab()</a></code> and <code><a href="ab_property.html">ab_atc()</a></code> internally if not a valid ATC code</p></dd>
-<dt>property</dt>
-<dd><p>property of an ATC code. Valid values are <code>"ATC"</code>, <code>"Name"</code>, <code>"DDD"</code>, <code>"U"</code> (<code>"unit"</code>), <code>"Adm.R"</code>, <code>"Note"</code> and <code>groups</code>. For this last option, all hierarchical groups of an ATC code will be returned, see <em>Examples</em>.</p></dd>
-<dt>administration</dt>
-<dd><p>type of administration when using <code>property = "Adm.R"</code>, see <em>Details</em></p></dd>
-<dt>url</dt>
-<dd><p>url of website of the WHOCC. The sign <code>%s</code> can be used as a placeholder for ATC codes.</p></dd>
-<dt>url_vet</dt>
-<dd><p>url of website of the WHOCC for veterinary medicine. The sign <code>%s</code> can be used as a placeholder for ATC_vet codes (that all start with "Q").</p></dd>
-<dt>...</dt>
-<dd><p>arguments to pass on to <code>atc_property</code></p></dd>
-</dl></div>
- <div id="details">
- <h2>Details</h2>
- <p>Options for argument <code>administration</code>:</p><ul><li><p><code>"Implant"</code> = Implant</p></li>
-<li><p><code>"Inhal"</code> = Inhalation</p></li>
-<li><p><code>"Instill"</code> = Instillation</p></li>
-<li><p><code>"N"</code> = nasal</p></li>
-<li><p><code>"O"</code> = oral</p></li>
-<li><p><code>"P"</code> = parenteral</p></li>
-<li><p><code>"R"</code> = rectal</p></li>
-<li><p><code>"SL"</code> = sublingual/buccal</p></li>
-<li><p><code>"TD"</code> = transdermal</p></li>
-<li><p><code>"V"</code> = vaginal</p></li>
-</ul><p>Abbreviations of return values when using <code>property = "U"</code> (unit):</p><ul><li><p><code>"g"</code> = gram</p></li>
-<li><p><code>"mg"</code> = milligram</p></li>
-<li><p><code>"mcg"</code> = microgram</p></li>
-<li><p><code>"U"</code> = unit</p></li>
-<li><p><code>"TU"</code> = thousand units</p></li>
-<li><p><code>"MU"</code> = million units</p></li>
-<li><p><code>"mmol"</code> = millimole</p></li>
-<li><p><code>"ml"</code> = millilitre (e.g. eyedrops)</p></li>
-</ul><p><strong>N.B. This function requires an internet connection and only works if the following packages are installed: <code>curl</code>, <code>rvest</code>, <code>xml2</code>.</strong></p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/ns-load.html" class="external-link">requireNamespace</a></span><span class="op">(</span><span class="st">"curl"</span><span class="op">)</span> <span class="op">&&</span> <span class="fu"><a href="https://rdrr.io/r/base/ns-load.html" class="external-link">requireNamespace</a></span><span class="op">(</span><span class="st">"rvest"</span><span class="op">)</span> <span class="op">&&</span> <span class="fu"><a href="https://rdrr.io/r/base/ns-load.html" class="external-link">requireNamespace</a></span><span class="op">(</span><span class="st">"xml2"</span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="co"># oral DDD (Defined Daily Dose) of amoxicillin</span>
- <span class="fu">atc_online_property</span><span class="op">(</span><span class="st">"J01CA04"</span>, <span class="st">"DDD"</span>, <span class="st">"O"</span><span class="op">)</span>
- <span class="fu">atc_online_ddd</span><span class="op">(</span><span class="fu"><a href="ab_property.html">ab_atc</a></span><span class="op">(</span><span class="st">"amox"</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># parenteral DDD (Defined Daily Dose) of amoxicillin</span>
- <span class="fu">atc_online_property</span><span class="op">(</span><span class="st">"J01CA04"</span>, <span class="st">"DDD"</span>, <span class="st">"P"</span><span class="op">)</span>
-
- <span class="fu">atc_online_property</span><span class="op">(</span><span class="st">"J01CA04"</span>, property <span class="op">=</span> <span class="st">"groups"</span><span class="op">)</span> <span class="co"># search hierarchical groups of amoxicillin</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
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diff --git a/docs/reference/availability.html b/docs/reference/availability.html
deleted file mode 100644
index 22fdf3667..000000000
--- a/docs/reference/availability.html
+++ /dev/null
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- <h1>Check Availability of Columns</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/availability.R" class="external-link"><code>R/availability.R</code></a></small>
- <div class="hidden name"><code>availability.Rd</code></div>
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- <p>Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. <code><a href="proportion.html">susceptibility()</a></code> and <code><a href="proportion.html">resistance()</a></code>.</p>
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- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">availability</span><span class="op">(</span><span class="va">tbl</span>, width <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span></code></pre></div>
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-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>tbl</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> or <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></p></dd>
-<dt>width</dt>
-<dd><p>number of characters to present the visual availability, defaults to filling the width of the console</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with column names of <code>tbl</code> as row names</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>The function returns a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with columns <code>"resistant"</code> and <code>"visual_resistance"</code>. The values in that columns are calculated with <code><a href="proportion.html">resistance()</a></code>.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
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-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
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- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
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-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">availability</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">mo</span> <span class="op">==</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select_all.html" class="external-link">select_if</a></span><span class="op">(</span><span class="va">is.rsi</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">availability</span><span class="op">(</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
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diff --git a/docs/reference/bug_drug_combinations.html b/docs/reference/bug_drug_combinations.html
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- <h1>Determine Bug-Drug Combinations</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/bug_drug_combinations.R" class="external-link"><code>R/bug_drug_combinations.R</code></a></small>
- <div class="hidden name"><code>bug_drug_combinations.Rd</code></div>
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- <p>Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use <code><a href="https://rdrr.io/r/base/format.html" class="external-link">format()</a></code> on the result to prettify it to a publishable/printable format, see <em>Examples</em>.</p>
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-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">bug_drug_combinations</span><span class="op">(</span><span class="va">x</span>, col_mo <span class="op">=</span> <span class="cn">NULL</span>, FUN <span class="op">=</span> <span class="va">mo_shortname</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="co"># S3 method for bug_drug_combinations</span>
-<span class="fu"><a href="https://rdrr.io/r/base/format.html" class="external-link">format</a></span><span class="op">(</span>
- <span class="va">x</span>,
- translate_ab <span class="op">=</span> <span class="st">"name (ab, atc)"</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- minimum <span class="op">=</span> <span class="fl">30</span>,
- combine_SI <span class="op">=</span> <span class="cn">TRUE</span>,
- combine_IR <span class="op">=</span> <span class="cn">FALSE</span>,
- add_ab_group <span class="op">=</span> <span class="cn">TRUE</span>,
- remove_intrinsic_resistant <span class="op">=</span> <span class="cn">FALSE</span>,
- decimal.mark <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"OutDec"</span><span class="op">)</span>,
- big.mark <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">decimal.mark</span> <span class="op">==</span> <span class="st">","</span>, <span class="st">"."</span>, <span class="st">","</span><span class="op">)</span>,
- <span class="va">...</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="source">
- <h2>Source</h2>
- <p><strong>M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition</strong>, 2014, <em>Clinical and Laboratory Standards Institute (CLSI)</em>. <a href="https://clsi.org/standards/products/microbiology/documents/m39/" class="external-link">https://clsi.org/standards/products/microbiology/documents/m39/</a>.</p>
- </div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>data with antibiotic columns, such as <code>amox</code>, <code>AMX</code> and <code>AMC</code></p></dd>
-<dt>col_mo</dt>
-<dd><p>column name of the IDs of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>), defaults to the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
-<dt>FUN</dt>
-<dd><p>the function to call on the <code>mo</code> column to transform the microorganism codes, defaults to <code><a href="mo_property.html">mo_shortname()</a></code></p></dd>
-<dt>...</dt>
-<dd><p>arguments passed on to <code>FUN</code></p></dd>
-<dt>translate_ab</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> of length 1 containing column names of the <a href="antibiotics.html">antibiotics</a> data set</p></dd>
-<dt>language</dt>
-<dd><p>language of the returned text, defaults to system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with <code>getOption("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
-<dt>minimum</dt>
-<dd><p>the minimum allowed number of available (tested) isolates. Any isolate count lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see <em>Source</em>.</p></dd>
-<dt>combine_SI</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument <code>combine_IR</code>, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is <code>TRUE</code>.</p></dd>
-<dt>combine_IR</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether values R and I should be summed</p></dd>
-<dt>add_ab_group</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate where the group of the antimicrobials must be included as a first column</p></dd>
-<dt>remove_intrinsic_resistant</dt>
-<dd><p><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that rows and columns with 100% resistance for all tested antimicrobials must be removed from the table</p></dd>
-<dt>decimal.mark</dt>
-<dd><p>the character to be used to indicate the numeric
- decimal point.</p></dd>
-<dt>big.mark</dt>
-<dd><p>character; if not empty used as mark between every
- <code>big.interval</code> decimals <em>before</em> (hence <code>big</code>) the
- decimal point.</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>The function <code>bug_drug_combinations()</code> returns a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with columns "mo", "ab", "S", "I", "R" and "total".</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>The function <code><a href="https://rdrr.io/r/base/format.html" class="external-link">format()</a></code> calculates the resistance per bug-drug combination. Use <code>combine_IR = FALSE</code> (default) to test R vs. S+I and <code>combine_IR = TRUE</code> to test R+I vs. S.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># \donttest{</span>
-<span class="va">x</span> <span class="op"><-</span> <span class="fu">bug_drug_combinations</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
-<span class="va">x</span>
-<span class="fu"><a href="https://rdrr.io/r/base/format.html" class="external-link">format</a></span><span class="op">(</span><span class="va">x</span>, translate_ab <span class="op">=</span> <span class="st">"name (atc)"</span><span class="op">)</span>
-
-<span class="co"># Use FUN to change to transformation of microorganism codes</span>
-<span class="fu">bug_drug_combinations</span><span class="op">(</span><span class="va">example_isolates</span>,
- FUN <span class="op">=</span> <span class="va">mo_gramstain</span><span class="op">)</span>
-
-<span class="fu">bug_drug_combinations</span><span class="op">(</span><span class="va">example_isolates</span>,
- FUN <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">x</span> <span class="op">==</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>,
- <span class="st">"E. coli"</span>,
- <span class="st">"Others"</span><span class="op">)</span><span class="op">)</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/catalogue_of_life.html b/docs/reference/catalogue_of_life.html
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- <h1>The Catalogue of Life</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/catalogue_of_life.R" class="external-link"><code>R/catalogue_of_life.R</code></a></small>
- <div class="hidden name"><code>catalogue_of_life.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>This package contains the complete taxonomic tree (last updated: 5 October 2021) of almost all microorganisms from the authoritative and comprehensive Catalogue of Life (CoL), supplemented with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN).</p>
- </div>
-
-
- <div id="catalogue-of-life">
- <h2>Catalogue of Life</h2>
-
-
-<p><img src="figures/logo_col.png" height="40" style='margin-bottom:"5"'><br>
-This package contains the complete taxonomic tree of almost all microorganisms (~71,000 species) from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a>). The CoL is the most comprehensive and authoritative global index of species currently available. Nonetheless, we supplemented the CoL data with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de" class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/CatalogueOfLife/general" class="external-link">CoL+ project</a> is finished, which we await.</p>
-<p>Click here for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with <code><a href="catalogue_of_life_version.html">catalogue_of_life_version()</a></code>.</p>
- </div>
- <div id="included-taxa">
- <h2>Included Taxa</h2>
-
-
-<p>Included are:</p><ul><li><p>All ~58,000 (sub)species from the kingdoms of Archaea, Bacteria, Chromista and Protozoa</p></li>
-<li><p>All ~5,000 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Microascales, Mucorales, Onygenales, Pneumocystales, Saccharomycetales, Schizosaccharomycetales and Tremellales, as well as ~4,600 other fungal (sub)species. The kingdom of Fungi is a very large taxon with almost 300,000 different (sub)species, of which most are not microbial (but rather macroscopic, like mushrooms). Because of this, not all fungi fit the scope of this package and including everything would tremendously slow down our algorithms too. By only including the aforementioned taxonomic orders, the most relevant fungi are covered (such as all species of <em>Aspergillus</em>, <em>Candida</em>, <em>Cryptococcus</em>, <em>Histplasma</em>, <em>Pneumocystis</em>, <em>Saccharomyces</em> and <em>Trichophyton</em>).</p></li>
-<li><p>All ~2,200 (sub)species from ~50 other relevant genera from the kingdom of Animalia (such as <em>Strongyloides</em> and <em>Taenia</em>)</p></li>
-<li><p>All ~14,000 previously accepted names of all included (sub)species (these were taxonomically renamed)</p></li>
-<li><p>The complete taxonomic tree of all included (sub)species: from kingdom to subspecies</p></li>
-<li><p>The responsible author(s) and year of scientific publication</p></li>
-</ul><p>The Catalogue of Life (<a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a>) is the most comprehensive and authoritative global index of species currently available. It holds essential information on the names, relationships and distributions of over 1.9 million species. The Catalogue of Life is used to support the major biodiversity and conservation information services such as the Global Biodiversity Information Facility (GBIF), Encyclopedia of Life (EoL) and the International Union for Conservation of Nature Red List. It is recognised by the Convention on Biological Diversity as a significant component of the Global Taxonomy Initiative and a contribution to Target 1 of the Global Strategy for Plant Conservation.</p>
-<p>The syntax used to transform the original data to a cleansed <span style="R">R</span> format, can be found here: <a href="https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R" class="external-link">https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R</a>.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p>Data set <a href="microorganisms.html">microorganisms</a> for the actual data. <br>
-Function <code><a href="as.mo.html">as.mo()</a></code> to use the data for intelligent determination of microorganisms.</p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># Get version info of included data set</span>
-<span class="fu"><a href="catalogue_of_life_version.html">catalogue_of_life_version</a></span><span class="op">(</span><span class="op">)</span>
-
-
-<span class="co"># Get a note when a species was renamed</span>
-<span class="fu"><a href="mo_property.html">mo_shortname</a></span><span class="op">(</span><span class="st">"Chlamydophila psittaci"</span><span class="op">)</span>
-<span class="co"># Note: 'Chlamydophila psittaci' (Everett et al., 1999) was renamed back to</span>
-<span class="co"># 'Chlamydia psittaci' (Page, 1968)</span>
-<span class="co">#> [1] "C. psittaci"</span>
-
-<span class="co"># Get any property from the entire taxonomic tree for all included species</span>
-<span class="fu"><a href="mo_property.html">mo_class</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
-<span class="co">#> [1] "Gammaproteobacteria"</span>
-
-<span class="fu"><a href="mo_property.html">mo_family</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
-<span class="co">#> [1] "Enterobacteriaceae"</span>
-
-<span class="fu"><a href="mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># based on kingdom and phylum, see ?mo_gramstain</span>
-<span class="co">#> [1] "Gram-negative"</span>
-
-<span class="fu"><a href="mo_property.html">mo_ref</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
-<span class="co">#> [1] "Castellani et al., 1919"</span>
-
-<span class="co"># Do not get mistaken - this package is about microorganisms</span>
-<span class="fu"><a href="mo_property.html">mo_kingdom</a></span><span class="op">(</span><span class="st">"C. elegans"</span><span class="op">)</span>
-<span class="co">#> [1] "Fungi" # Fungi?!</span>
-<span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"C. elegans"</span><span class="op">)</span>
-<span class="co">#> [1] "Cladosporium elegans" # Because a microorganism was found</span>
-</code></pre></div>
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diff --git a/docs/reference/catalogue_of_life_version.html b/docs/reference/catalogue_of_life_version.html
deleted file mode 100644
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--- a/docs/reference/catalogue_of_life_version.html
+++ /dev/null
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- <h1>Version info of included Catalogue of Life</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/catalogue_of_life.R" class="external-link"><code>R/catalogue_of_life.R</code></a></small>
- <div class="hidden name"><code>catalogue_of_life_version.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>This function returns information about the included data from the Catalogue of Life.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">catalogue_of_life_version</span><span class="op">(</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="value">
- <h2>Value</h2>
- <p>a <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a>, which prints in pretty format</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>For LPSN, see <a href="microorganisms.html">microorganisms</a>.</p>
- </div>
- <div id="catalogue-of-life">
- <h2>Catalogue of Life</h2>
-
-
-<p><img src="figures/logo_col.png" height="40" style='margin-bottom:"5"'><br>
-This package contains the complete taxonomic tree of almost all microorganisms (~71,000 species) from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a>). The CoL is the most comprehensive and authoritative global index of species currently available. Nonetheless, we supplemented the CoL data with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de" class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/CatalogueOfLife/general" class="external-link">CoL+ project</a> is finished, which we await.</p>
-<p><a href="catalogue_of_life.html">Click here</a> for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with <code>catalogue_of_life_version()</code>.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><a href="microorganisms.html">microorganisms</a></p></div>
- </div>
-
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diff --git a/docs/reference/count.html b/docs/reference/count.html
deleted file mode 100644
index 276266464..000000000
--- a/docs/reference/count.html
+++ /dev/null
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-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Count Available Isolates — count • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link href="https://cdnjs.cloudflare.com/ajax/libs/bootswatch/3.4.0/flatly/bootstrap.min.css" rel="stylesheet" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Count Available Isolates — count"><meta property="og:description" content="These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in summarise() from the dplyr package and also support grouped variables, see Examples.
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- <div class="page-header">
- <h1>Count Available Isolates</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/count.R" class="external-link"><code>R/count.R</code></a></small>
- <div class="hidden name"><code>count.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code> from the <code>dplyr</code> package and also support grouped variables, see <em>Examples</em>.</p>
-<p><code>count_resistant()</code> should be used to count resistant isolates, <code>count_susceptible()</code> should be used to count susceptible isolates.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">count_resistant</span><span class="op">(</span><span class="va">...</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">count_susceptible</span><span class="op">(</span><span class="va">...</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">count_R</span><span class="op">(</span><span class="va">...</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">count_IR</span><span class="op">(</span><span class="va">...</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">count_I</span><span class="op">(</span><span class="va">...</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">count_SI</span><span class="op">(</span><span class="va">...</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">count_S</span><span class="op">(</span><span class="va">...</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">count_all</span><span class="op">(</span><span class="va">...</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">n_rsi</span><span class="op">(</span><span class="va">...</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">count_df</span><span class="op">(</span>
- <span class="va">data</span>,
- translate_ab <span class="op">=</span> <span class="st">"name"</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- combine_SI <span class="op">=</span> <span class="cn">TRUE</span>,
- combine_IR <span class="op">=</span> <span class="cn">FALSE</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>...</dt>
-<dd><p>one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with <code><a href="as.rsi.html">as.rsi()</a></code> if needed.</p></dd>
-<dt>only_all_tested</dt>
-<dd><p>(for combination therapies, i.e. using more than one variable for <code>...</code>): a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that isolates must be tested for all antibiotics, see section <em>Combination Therapy</em> below</p></dd>
-<dt>data</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing columns with class <code><a href="as.rsi.html">rsi</a></code> (see <code><a href="as.rsi.html">as.rsi()</a></code>)</p></dd>
-<dt>translate_ab</dt>
-<dd><p>a column name of the <a href="antibiotics.html">antibiotics</a> data set to translate the antibiotic abbreviations to, using <code><a href="ab_property.html">ab_property()</a></code></p></dd>
-<dt>language</dt>
-<dd><p>language of the returned text, defaults to system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with <code>getOption("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
-<dt>combine_SI</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument <code>combine_IR</code>, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is <code>TRUE</code>.</p></dd>
-<dt>combine_IR</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see argument <code>combine_SI</code>.</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a></p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>These functions are meant to count isolates. Use the <code><a href="proportion.html">resistance()</a></code>/<code><a href="proportion.html">susceptibility()</a></code> functions to calculate microbial resistance/susceptibility.</p>
-<p>The function <code>count_resistant()</code> is equal to the function <code>count_R()</code>. The function <code>count_susceptible()</code> is equal to the function <code>count_SI()</code>.</p>
-<p>The function <code>n_rsi()</code> is an alias of <code>count_all()</code>. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to <code><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct()</a></code>. Their function is equal to <code>count_susceptible(...) + count_resistant(...)</code>.</p>
-<p>The function <code>count_df()</code> takes any variable from <code>data</code> that has an <code><a href="as.rsi.html">rsi</a></code> class (created with <code><a href="as.rsi.html">as.rsi()</a></code>) and counts the number of S's, I's and R's. It also supports grouped variables. The function <code><a href="proportion.html">rsi_df()</a></code> works exactly like <code>count_df()</code>, but adds the percentage of S, I and R.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="interpretation-of-r-and-s-i">
- <h2>Interpretation of R and S/I</h2>
-
-
-<p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (<a href="https://www.eucast.org/newsiandr/" class="external-link">https://www.eucast.org/newsiandr/</a>).</p><ul><li><p><strong>R = Resistant</strong><br>
-A microorganism is categorised as <em>Resistant</em> when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p></li>
-<li><p><strong>S = Susceptible</strong><br>
-A microorganism is categorised as <em>Susceptible, standard dosing regimen</em>, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
-<li><p><strong>I = Susceptible, Increased exposure</strong><br>
-A microorganism is categorised as <em>Susceptible, Increased exposure</em> when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.</p></li>
-</ul><p>This AMR package honours this (new) insight. Use <code><a href="proportion.html">susceptibility()</a></code> (equal to <code><a href="proportion.html">proportion_SI()</a></code>) to determine antimicrobial susceptibility and <code>count_susceptible()</code> (equal to <code>count_SI()</code>) to count susceptible isolates.</p>
- </div>
- <div id="combination-therapy">
- <h2>Combination Therapy</h2>
-
-
-<p>When using more than one variable for <code>...</code> (= combination therapy), use <code>only_all_tested</code> to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Drug A and Drug B, about how <code><a href="proportion.html">susceptibility()</a></code> works to calculate the %SI:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>Please note that, in combination therapies, for <code>only_all_tested = TRUE</code> applies that:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>and that, in combination therapies, for <code>only_all_tested = FALSE</code> applies that:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>Using <code>only_all_tested</code> has no impact when only using one antibiotic as input.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="proportion.html">proportion_*</a></code> to calculate microbial resistance and susceptibility.</p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># example_isolates is a data set available in the AMR package.</span>
-<span class="op">?</span><span class="va">example_isolates</span>
-
-<span class="fu">count_resistant</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span> <span class="co"># counts "R"</span>
-<span class="fu">count_susceptible</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span> <span class="co"># counts "S" and "I"</span>
-<span class="fu">count_all</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span> <span class="co"># counts "S", "I" and "R"</span>
-
-<span class="co"># be more specific</span>
-<span class="fu">count_S</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu">count_SI</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu">count_I</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu">count_IR</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu">count_R</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-
-<span class="co"># Count all available isolates</span>
-<span class="fu">count_all</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu">n_rsi</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-
-<span class="co"># n_rsi() is an alias of count_all().</span>
-<span class="co"># Since it counts all available isolates, you can</span>
-<span class="co"># calculate back to count e.g. susceptible isolates.</span>
-<span class="co"># These results are the same:</span>
-<span class="fu">count_susceptible</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu"><a href="proportion.html">susceptibility</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span> <span class="op">*</span> <span class="fu">n_rsi</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>R <span class="op">=</span> <span class="fu">count_R</span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span>,
- I <span class="op">=</span> <span class="fu">count_I</span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span>,
- S <span class="op">=</span> <span class="fu">count_S</span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span>,
- n1 <span class="op">=</span> <span class="fu">count_all</span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span>, <span class="co"># the actual total; sum of all three</span>
- n2 <span class="op">=</span> <span class="fu">n_rsi</span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span>, <span class="co"># same - analogous to n_distinct</span>
- total <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/context.html" class="external-link">n</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co"># NOT the number of tested isolates!</span>
-
- <span class="co"># Number of available isolates for a whole antibiotic class</span>
- <span class="co"># (i.e., in this data set columns GEN, TOB, AMK, KAN)</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">n_rsi</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># Count co-resistance between amoxicillin/clav acid and gentamicin,</span>
- <span class="co"># so we can see that combination therapy does a lot more than mono therapy.</span>
- <span class="co"># Please mind that `susceptibility()` calculates percentages right away instead.</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">count_susceptible</span><span class="op">(</span><span class="va">AMC</span><span class="op">)</span> <span class="co"># 1433</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">count_all</span><span class="op">(</span><span class="va">AMC</span><span class="op">)</span> <span class="co"># 1879</span>
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">count_susceptible</span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span> <span class="co"># 1399</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">count_all</span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span> <span class="co"># 1855</span>
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">count_susceptible</span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span><span class="op">)</span> <span class="co"># 1764</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">count_all</span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span><span class="op">)</span> <span class="co"># 1936</span>
-
- <span class="co"># Get number of S+I vs. R immediately of selected columns</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">count_df</span><span class="op">(</span>translate <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
- <span class="co"># It also supports grouping variables</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">hospital_id</span>, <span class="va">AMX</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">count_df</span><span class="op">(</span>translate <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
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- <h1>Define Custom EUCAST Rules</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/custom_eucast_rules.R" class="external-link"><code>R/custom_eucast_rules.R</code></a></small>
- <div class="hidden name"><code>custom_eucast_rules.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in <code><a href="eucast_rules.html">eucast_rules()</a></code>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">custom_eucast_rules</span><span class="op">(</span><span class="va">...</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>...</dt>
-<dd><p>rules in formula notation, see <em>Examples</em></p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>A <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a> containing the custom rules</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>Some organisations have their own adoption of EUCAST rules. This function can be used to define custom EUCAST rules to be used in the <code><a href="eucast_rules.html">eucast_rules()</a></code> function.</p>
- </div>
- <div id="how-it-works">
- <h2>How it works</h2>
-
-
-<div class="section">
-<h3 id="basics">Basics<a class="anchor" aria-label="anchor" href="#basics"></a></h3>
-
-
-<p>If you are familiar with the <code><a href="https://dplyr.tidyverse.org/reference/case_when.html" class="external-link">case_when()</a></code> function of the <code>dplyr</code> package, you will recognise the input method to set your own rules. Rules must be set using what <span style="R">R</span> considers to be the 'formula notation'. The rule itself is written <em>before</em> the tilde (<code>~</code>) and the consequence of the rule is written <em>after</em> the tilde:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>The rules (the part <em>before</em> the tilde, in above example <code>TZP == "S"</code> and <code>TZP == "R"</code>) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column <code>TZP</code> must exist. We will create a sample data set and test the rules set:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-</div>
-
-<div class="section">
-<h3 id="using-taxonomic-properties-in-rules">Using taxonomic properties in rules<a class="anchor" aria-label="anchor" href="#using-taxonomic-properties-in-rules"></a></h3>
-
-
-<p>There is one exception in variables used for the rules: all column names of the <a href="microorganisms.html">microorganisms</a> data set can also be used, but do not have to exist in the data set. These column names are: mo, fullname, kingdom, phylum, class, order, family, genus, species, subspecies, rank, ref, species_id, source, prevalence and snomed. Thus, this next example will work as well, despite the fact that the <code>df</code> data set does not contain a column <code>genus</code>:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-</div>
-
-<div class="section">
-<h3 id="usage-of-antibiotic-group-names">Usage of antibiotic group names<a class="anchor" aria-label="anchor" href="#usage-of-antibiotic-group-names"></a></h3>
-
-
-<p>It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part <em>after</em> the tilde. In above examples, the antibiotic group <code>aminopenicillins</code> is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the agents that will be matched when running the rule.</p><ul><li><p>aminoglycosides<br>(amikacin, amikacin/fosfomycin, amphotericin B-high, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin and tobramycin-high)</p></li>
-<li><p>aminopenicillins<br>(amoxicillin and ampicillin)</p></li>
-<li><p>antifungals<br>(5-fluorocytosine, amphotericin B, anidulafungin, butoconazole, caspofungin, ciclopirox, clotrimazole, econazole, fluconazole, fosfluconazole, griseofulvin, hachimycin, ibrexafungerp, isavuconazole, isoconazole, itraconazole, ketoconazole, manogepix, micafungin, miconazole, nystatin, pimaricin, posaconazole, rezafungin, ribociclib, sulconazole, terbinafine, terconazole and voriconazole)</p></li>
-<li><p>antimycobacterials<br>(4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, morinamide, p-aminosalicylic acid, pretomanid, prothionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, simvastatin/fenofibrate, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone/isoniazid, tiocarlide and viomycin)</p></li>
-<li><p>betalactams<br>(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, biapenem, carbenicillin, carindacillin, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/nacubactam, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, tebipenem, temocillin, ticarcillin and ticarcillin/clavulanic acid)</p></li>
-<li><p>carbapenems<br>(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil and tebipenem)</p></li>
-<li><p>cephalosporins<br>(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)</p></li>
-<li><p>cephalosporins_1st<br>(cefacetrile, cefadroxil, cefaloridine, cefatrizine, cefazedone, cefazolin, cefroxadine, ceftezole, cephalexin, cephalothin, cephapirin and cephradine)</p></li>
-<li><p>cephalosporins_2nd<br>(cefaclor, cefamandole, cefmetazole, cefonicid, ceforanide, cefotetan, cefotiam, cefoxitin, cefoxitin screening, cefprozil, cefuroxime, cefuroxime axetil and loracarbef)</p></li>
-<li><p>cephalosporins_3rd<br>(cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefetamet, cefetamet pivoxil, cefixime, cefmenoxime, cefodizime, cefoperazone, cefoperazone/sulbactam, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotiam hexetil, cefovecin, cefpimizole, cefpiramide, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefsulodin, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftriaxone and latamoxef)</p></li>
-<li><p>cephalosporins_4th<br>(cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetecol, cefoselis, cefozopran, cefpirome and cefquinome)</p></li>
-<li><p>cephalosporins_5th<br>(ceftaroline, ceftaroline/avibactam, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor and ceftolozane/tazobactam)</p></li>
-<li><p>cephalosporins_except_caz<br>(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)</p></li>
-<li><p>fluoroquinolones<br>(besifloxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nifuroquine, norfloxacin, ofloxacin, orbifloxacin, pazufloxacin, pefloxacin, pradofloxacin, premafloxacin, prulifloxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)</p></li>
-<li><p>glycopeptides<br>(avoparcin, dalbavancin, norvancomycin, oritavancin, ramoplanin, teicoplanin, teicoplanin-macromethod, telavancin, vancomycin and vancomycin-macromethod)</p></li>
-<li><p>glycopeptides_except_lipo<br>(avoparcin, norvancomycin, ramoplanin, teicoplanin, teicoplanin-macromethod, vancomycin and vancomycin-macromethod)</p></li>
-<li><p>lincosamides<br>(acetylmidecamycin, acetylspiramycin, clindamycin, gamithromycin, kitasamycin, lincomycin, meleumycin, nafithromycin, pirlimycin, primycin, solithromycin, tildipirosin, tilmicosin, tulathromycin, tylosin and tylvalosin)</p></li>
-<li><p>lipoglycopeptides<br>(dalbavancin, oritavancin and telavancin)</p></li>
-<li><p>macrolides<br>(acetylmidecamycin, acetylspiramycin, azithromycin, clarithromycin, dirithromycin, erythromycin, flurithromycin, gamithromycin, josamycin, kitasamycin, meleumycin, midecamycin, miocamycin, nafithromycin, oleandomycin, pirlimycin, primycin, rokitamycin, roxithromycin, solithromycin, spiramycin, telithromycin, tildipirosin, tilmicosin, troleandomycin, tulathromycin, tylosin and tylvalosin)</p></li>
-<li><p>oxazolidinones<br>(cadazolid, cycloserine, linezolid, tedizolid and thiacetazone)</p></li>
-<li><p>penicillins<br>(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, carbenicillin, carindacillin, cefepime/nacubactam, ciclacillin, clometocillin, cloxacillin, dicloxacillin, epicillin, flucloxacillin, hetacillin, lenampicillin, mecillinam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, temocillin, ticarcillin and ticarcillin/clavulanic acid)</p></li>
-<li><p>polymyxins<br>(colistin, polymyxin B and polymyxin B/polysorbate 80)</p></li>
-<li><p>quinolones<br>(besifloxacin, cinoxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, flumequine, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nalidixic acid, nifuroquine, nitroxoline, norfloxacin, ofloxacin, orbifloxacin, oxolinic acid, pazufloxacin, pefloxacin, pipemidic acid, piromidic acid, pradofloxacin, premafloxacin, prulifloxacin, rosoxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)</p></li>
-<li><p>streptogramins<br>(pristinamycin and quinupristin/dalfopristin)</p></li>
-<li><p>tetracyclines<br>(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline, tetracycline and tigecycline)</p></li>
-<li><p>tetracyclines_except_tgc<br>(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline and tetracycline)</p></li>
-<li><p>trimethoprims<br>(brodimoprim, sulfadiazine, sulfadiazine/tetroxoprim, sulfadiazine/trimethoprim, sulfadimethoxine, sulfadimidine, sulfadimidine/trimethoprim, sulfafurazole, sulfaisodimidine, sulfalene, sulfamazone, sulfamerazine, sulfamerazine/trimethoprim, sulfamethizole, sulfamethoxazole, sulfamethoxypyridazine, sulfametomidine, sulfametoxydiazine, sulfametrole/trimethoprim, sulfamoxole, sulfamoxole/trimethoprim, sulfanilamide, sulfaperin, sulfaphenazole, sulfapyridine, sulfathiazole, sulfathiourea, trimethoprim and trimethoprim/sulfamethoxazole)</p></li>
-<li><p>ureidopenicillins<br>(azlocillin, mezlocillin, piperacillin and piperacillin/tazobactam)</p></li>
-</ul></div>
-
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- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
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-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
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- <h2>Read more on Our Website!</h2>
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- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">x</span> <span class="op"><-</span> <span class="fu">custom_eucast_rules</span><span class="op">(</span><span class="va">AMC</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&</span> <span class="va">genus</span> <span class="op">==</span> <span class="st">"Klebsiella"</span> <span class="op">~</span> <span class="va">aminopenicillins</span> <span class="op">==</span> <span class="st">"R"</span>,
- <span class="va">AMC</span> <span class="op">==</span> <span class="st">"I"</span> <span class="op">&</span> <span class="va">genus</span> <span class="op">==</span> <span class="st">"Klebsiella"</span> <span class="op">~</span> <span class="va">aminopenicillins</span> <span class="op">==</span> <span class="st">"I"</span><span class="op">)</span>
-<span class="fu"><a href="eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">example_isolates</span>,
- rules <span class="op">=</span> <span class="st">"custom"</span>,
- custom_rules <span class="op">=</span> <span class="va">x</span>,
- info <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="co"># combine rule sets</span>
-<span class="va">x2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">x</span>,
- <span class="fu">custom_eucast_rules</span><span class="op">(</span><span class="va">TZP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">~</span> <span class="va">carbapenems</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span>
-<span class="va">x2</span>
-</code></pre></div>
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diff --git a/docs/reference/dosage.html b/docs/reference/dosage.html
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- <h1>Data Set with Treatment Dosages as Defined by EUCAST</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>dosage.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with <code><a href="eucast_rules.html">eucast_dosage()</a></code>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">dosage</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 169 observations and 9 variables:</p><ul><li><p><code>ab</code><br> Antibiotic ID as used in this package (such as <code>AMC</code>), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available</p></li>
-<li><p><code>name</code><br> Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO</p></li>
-<li><p><code>type</code><br> Type of the dosage, either "high_dosage", "standard_dosage" or "uncomplicated_uti"</p></li>
-<li><p><code>dose</code><br> Dose, such as "2 g" or "25 mg/kg"</p></li>
-<li><p><code>dose_times</code><br> Number of times a dose must be administered</p></li>
-<li><p><code>administration</code><br> Route of administration, either "im", "iv" or "oral"</p></li>
-<li><p><code>notes</code><br> Additional dosage notes</p></li>
-<li><p><code>original_txt</code><br> Original text in the PDF file of EUCAST</p></li>
-<li><p><code>eucast_version</code><br> Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply</p></li>
-</ul></div>
- <div id="details">
- <h2>Details</h2>
- <p><a href="https://www.eucast.org/clinical_breakpoints/" class="external-link">'EUCAST Clinical Breakpoint Tables' v11.0</a> (2021) are based on the dosages in this data set.</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
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diff --git a/docs/reference/eucast_rules.html b/docs/reference/eucast_rules.html
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- <h1>Apply EUCAST Rules</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/eucast_rules.R" class="external-link"><code>R/eucast_rules.R</code></a></small>
- <div class="hidden name"><code>eucast_rules.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, <a href="https://eucast.org" class="external-link">https://eucast.org</a>), see <em>Source</em>. Use <code>eucast_dosage()</code> to get a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with advised dosages of a certain bug-drug combination, which is based on the <a href="dosage.html">dosage</a> data set.</p>
-<p>To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see <em>Details</em>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">eucast_rules</span><span class="op">(</span>
- <span class="va">x</span>,
- col_mo <span class="op">=</span> <span class="cn">NULL</span>,
- info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>,
- rules <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"AMR_eucastrules"</span>, default <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"breakpoints"</span>, <span class="st">"expert"</span><span class="op">)</span><span class="op">)</span>,
- verbose <span class="op">=</span> <span class="cn">FALSE</span>,
- version_breakpoints <span class="op">=</span> <span class="fl">11</span>,
- version_expertrules <span class="op">=</span> <span class="fl">3.3</span>,
- ampc_cephalosporin_resistance <span class="op">=</span> <span class="cn">NA</span>,
- only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>,
- custom_rules <span class="op">=</span> <span class="cn">NULL</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="fu">eucast_dosage</span><span class="op">(</span><span class="va">ab</span>, administration <span class="op">=</span> <span class="st">"iv"</span>, version_breakpoints <span class="op">=</span> <span class="fl">11</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="source">
- <h2>Source</h2>
-
-<ul><li><p>EUCAST Expert Rules. Version 2.0, 2012.<br>
-Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility testing.</strong> <em>Clin Microbiol Infect.</em> 2013;19(2):141-60; <a href="https://doi.org/10.1111/j.1469-0691.2011.03703.x" class="external-link">doi:10.1111/j.1469-0691.2011.03703.x</a></p></li>
-<li><p>EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes Tables. Version 3.1, 2016. <a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf" class="external-link">(link)</a></p></li>
-<li><p>EUCAST Intrinsic Resistance and Unusual Phenotypes. Version 3.2, 2020. <a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf" class="external-link">(link)</a></p></li>
-<li><p>EUCAST Intrinsic Resistance and Unusual Phenotypes. Version 3.3, 2021. <a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2021/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.3_20211018.pdf" class="external-link">(link)</a></p></li>
-<li><p>EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. <a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_9.0_Breakpoint_Tables.xlsx" class="external-link">(link)</a></p></li>
-<li><p>EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 10.0, 2020. <a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_10.0_Breakpoint_Tables.xlsx" class="external-link">(link)</a></p></li>
-<li><p>EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 11.0, 2021. <a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_11.0_Breakpoint_Tables.xlsx" class="external-link">(link)</a></p></li>
-</ul></div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>data with antibiotic columns, such as <code>amox</code>, <code>AMX</code> and <code>AMC</code></p></dd>
-<dt>col_mo</dt>
-<dd><p>column name of the IDs of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>), defaults to the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
-<dt>info</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether progress should be printed to the console, defaults to only print while in interactive sessions</p></dd>
-<dt>rules</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector that specifies which rules should be applied. Must be one or more of <code>"breakpoints"</code>, <code>"expert"</code>, <code>"other"</code>, <code>"custom"</code>, <code>"all"</code>, and defaults to <code>c("breakpoints", "expert")</code>. The default value can be set to another value, e.g. using <code>options(AMR_eucastrules = "all")</code>. If using <code>"custom"</code>, be sure to fill in argument <code>custom_rules</code> too. Custom rules can be created with <code><a href="custom_eucast_rules.html">custom_eucast_rules()</a></code>.</p></dd>
-<dt>verbose</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time.</p></dd>
-<dt>version_breakpoints</dt>
-<dd><p>the version number to use for the EUCAST Clinical Breakpoints guideline. Can be either "11.0" or "10.0".</p></dd>
-<dt>version_expertrules</dt>
-<dd><p>the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be either "3.3", "3.2" or "3.1".</p></dd>
-<dt>ampc_cephalosporin_resistance</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> value that should be applied to cefotaxime, ceftriaxone and ceftazidime for AmpC de-repressed cephalosporin-resistant mutants, defaults to <code>NA</code>. Currently only works when <code>version_expertrules</code> is <code>3.2</code> and higher; these version of '<em>EUCAST Expert Rules on Enterobacterales</em>' state that results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these three agents. A value of <code>NA</code> (the default) for this argument will remove results for these three agents, while e.g. a value of <code>"R"</code> will make the results for these agents resistant. Use <code>NULL</code> or <code>FALSE</code> to not alter results for these three agents of AmpC de-repressed cephalosporin-resistant mutants. Using <code>TRUE</code> is equal to using <code>"R"</code>. <br> For <em>EUCAST Expert Rules</em> v3.2, this rule applies to: <em>Citrobacter braakii</em>, <em>Citrobacter freundii</em>, <em>Citrobacter gillenii</em>, <em>Citrobacter murliniae</em>, <em>Citrobacter rodenticum</em>, <em>Citrobacter sedlakii</em>, <em>Citrobacter werkmanii</em>, <em>Citrobacter youngae</em>, <em>Enterobacter</em>, <em>Hafnia alvei</em>, <em>Klebsiella aerogenes</em>, <em>Morganella morganii</em>, <em>Providencia</em> and <em>Serratia</em>.</p></dd>
-<dt>only_rsi_columns</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only antibiotic columns must be detected that were transformed to class <code><rsi></code> (see <code><a href="as.rsi.html">as.rsi()</a></code>) on beforehand (defaults to <code>FALSE</code>)</p></dd>
-<dt>custom_rules</dt>
-<dd><p>custom rules to apply, created with <code><a href="custom_eucast_rules.html">custom_eucast_rules()</a></code></p></dd>
-<dt>...</dt>
-<dd><p>column name of an antibiotic, see section <em>Antibiotics</em> below</p></dd>
-<dt>ab</dt>
-<dd><p>any (vector of) text that can be coerced to a valid antibiotic code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
-<dt>administration</dt>
-<dd><p>route of administration, either "im", "iv" or "oral"</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>The input of <code>x</code>, possibly with edited values of antibiotics. Or, if <code>verbose = TRUE</code>, a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with all original and new values of the affected bug-drug combinations.</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p><strong>Note:</strong> This function does not translate MIC values to RSI values. Use <code><a href="as.rsi.html">as.rsi()</a></code> for that. <br><strong>Note:</strong> When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance. <br></p>
-<p>The file containing all EUCAST rules is located here: <a href="https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv" class="external-link">https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv</a>. <strong>Note:</strong> Old taxonomic names are replaced with the current taxonomy where applicable. For example, <em>Ochrobactrum anthropi</em> was renamed to <em>Brucella anthropi</em> in 2020; the original EUCAST rules v3.1 and v3.2 did not yet contain this new taxonomic name. The file used as input for this <code>AMR</code> package contains the taxonomy updated until <a href="catalogue_of_life.html">5 October 2021</a>.</p><div class="section">
-<h3 id="custom-rules">Custom Rules<a class="anchor" aria-label="anchor" href="#custom-rules"></a></h3>
-
-
-<p>Custom rules can be created using <code><a href="custom_eucast_rules.html">custom_eucast_rules()</a></code>, e.g.:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-</div>
-
-<div class="section">
-<h3 id="-other-rules">'Other' Rules<a class="anchor" aria-label="anchor" href="#-other-rules"></a></h3>
-
-
-<p>Before further processing, two non-EUCAST rules about drug combinations can be applied to improve the efficacy of the EUCAST rules, and the reliability of your data (analysis). These rules are:</p><ol><li><p>A drug <strong>with</strong> enzyme inhibitor will be set to S if the same drug <strong>without</strong> enzyme inhibitor is S</p></li>
-<li><p>A drug <strong>without</strong> enzyme inhibitor will be set to R if the same drug <strong>with</strong> enzyme inhibitor is R</p></li>
-</ol><p>Important examples include amoxicillin and amoxicillin/clavulanic acid, and trimethoprim and trimethoprim/sulfamethoxazole. Needless to say, for these rules to work, both drugs must be available in the data set.</p>
-<p>Since these rules are not officially approved by EUCAST, they are not applied at default. To use these rules, include <code>"other"</code> to the <code>rules</code> argument, or use <code>eucast_rules(..., rules = "all")</code>. You can also set the option <code>AMR_eucastrules</code>, i.e. run <code>options(AMR_eucastrules = "all")</code>.</p>
-</div>
-
- </div>
- <div id="antibiotics">
- <h2>Antibiotics</h2>
-
-
-<p>To define antibiotics column names, leave as it is to determine it automatically with <code><a href="guess_ab_col.html">guess_ab_col()</a></code> or input a text (case-insensitive), or use <code>NULL</code> to skip a column (e.g. <code>TIC = NULL</code> to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.</p>
-<p>The following antibiotics are eligible for the functions <code>eucast_rules()</code> and <code><a href="mdro.html">mdro()</a></code>. These are shown below in the format 'name (<code>antimicrobial ID</code>, <a href="https://www.whocc.no/atc/structure_and_principles/" class="external-link">ATC code</a>)', sorted alphabetically:</p>
-<p>Amikacin (<code>AMK</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB06&showdescription=no" class="external-link">S01AE08</a>), amoxicillin (<code>AMX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA04&showdescription=no" class="external-link">J01MA02</a>), amoxicillin/clavulanic acid (<code>AMC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR02&showdescription=no" class="external-link">J01MA23</a>), ampicillin (<code>AMP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA01&showdescription=no" class="external-link">J01MA04</a>), ampicillin/sulbactam (<code>SAM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR01&showdescription=no" class="external-link">J01MA08</a>), arbekacin (<code>ARB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB12&showdescription=no" class="external-link">J01MA19</a>), aspoxicillin (<code>APX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA19&showdescription=no" class="external-link">J01MA16</a>), azidocillin (<code>AZD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE04&showdescription=no" class="external-link">J01MA15</a>), azithromycin (<code>AZM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA10&showdescription=no" class="external-link">J01MA11</a>), azlocillin (<code>AZL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA09&showdescription=no" class="external-link">J01MA12</a>), aztreonam (<code>ATM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DF01&showdescription=no" class="external-link">J01MA24</a>), bacampicillin (<code>BAM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA06&showdescription=no" class="external-link">J01MA07</a>), bekanamycin (<code>BEK</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB13&showdescription=no" class="external-link">J01MA14</a>), benzathine benzylpenicillin (<code>BNB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE08&showdescription=no" class="external-link">D10AF05</a>), benzathine phenoxymethylpenicillin (<code>BNP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE10&showdescription=no" class="external-link">J01MA06</a>), benzylpenicillin (<code>PEN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE01&showdescription=no" class="external-link">J01MA01</a>), besifloxacin (<code>BES</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=S01AE08&showdescription=no" class="external-link">J01MA18</a>), biapenem (<code>BIA</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH05&showdescription=no" class="external-link">J01MA03</a>), carbenicillin (<code>CRB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA03&showdescription=no" class="external-link">J01MA17</a>), carindacillin (<code>CRN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA05&showdescription=no" class="external-link">J01MA10</a>), cefacetrile (<code>CAC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB10&showdescription=no" class="external-link">J01MA21</a>), cefaclor (<code>CEC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC04&showdescription=no" class="external-link">J01MA09</a>), cefadroxil (<code>CFR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB05&showdescription=no" class="external-link">J01MA05</a>), cefaloridine (<code>RID</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB02&showdescription=no" class="external-link">P01AA05</a>), cefamandole (<code>MAN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC03&showdescription=no" class="external-link">J01MA22</a>), cefatrizine (<code>CTZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB07&showdescription=no" class="external-link">J01MA13</a>), cefazedone (<code>CZD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB06&showdescription=no" class="external-link">J01CA01</a>), cefazolin (<code>CZO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB04&showdescription=no" class="external-link">J01CA04</a>), cefcapene (<code>CCP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD17&showdescription=no" class="external-link">J01CA12</a>), cefdinir (<code>CDR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD15&showdescription=no" class="external-link">J01CR05</a>), cefditoren (<code>DIT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD16&showdescription=no" class="external-link">J01CA13</a>), cefepime (<code>FEP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DE01&showdescription=no" class="external-link">J01AA02</a>), cefetamet (<code>CAT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD10&showdescription=no" class="external-link">J01FA10</a>), cefixime (<code>CFM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD08&showdescription=no" class="external-link">J01FA09</a>), cefmenoxime (<code>CMX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD05&showdescription=no" class="external-link">J01CR02</a>), cefmetazole (<code>CMZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC09&showdescription=no" class="external-link">J01AA08</a>), cefodizime (<code>DIZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD09&showdescription=no" class="external-link">J01FA06</a>), cefonicid (<code>CID</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC06&showdescription=no" class="external-link">J01CF04</a>), cefoperazone (<code>CFP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD12&showdescription=no" class="external-link">J01CF05</a>), cefoperazone/sulbactam (<code>CSL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD62&showdescription=no" class="external-link">J01CR01</a>), ceforanide (<code>CND</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC11&showdescription=no" class="external-link">J01CA19</a>), cefotaxime (<code>CTX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD01&showdescription=no" class="external-link">J01CE04</a>), cefotetan (<code>CTT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC05&showdescription=no" class="external-link">J01CA09</a>), cefotiam (<code>CTF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC07&showdescription=no" class="external-link">J01DF01</a>), cefoxitin (<code>FOX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC01&showdescription=no" class="external-link">J01CA06</a>), cefozopran (<code>ZOP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DE03&showdescription=no" class="external-link">J01CE08</a>), cefpiramide (<code>CPM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD11&showdescription=no" class="external-link">J01CE10</a>), cefpirome (<code>CPO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DE02&showdescription=no" class="external-link">J01CE01</a>), cefpodoxime (<code>CPD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD13&showdescription=no" class="external-link">J01CA03</a>), cefprozil (<code>CPR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC10&showdescription=no" class="external-link">J01CA05</a>), cefroxadine (<code>CRD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB11&showdescription=no" class="external-link">J01CE07</a>), cefsulodin (<code>CFS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD03&showdescription=no" class="external-link">J01CF02</a>), ceftaroline (<code>CPT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DI02&showdescription=no" class="external-link">J01CF01</a>), ceftazidime (<code>CAZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD02&showdescription=no" class="external-link">J01CA07</a>), ceftazidime/clavulanic acid (<code>CCV</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD52&showdescription=no" class="external-link">J01CA18</a>), cefteram (<code>CEM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD18&showdescription=no" class="external-link">J01CA11</a>), ceftezole (<code>CTL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB12&showdescription=no" class="external-link">J01CA14</a>), ceftibuten (<code>CTB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD14&showdescription=no" class="external-link">J01CF03</a>), ceftizoxime (<code>CZX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD07&showdescription=no" class="external-link">J01CA10</a>), ceftobiprole medocaril (<code>CFM1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DI01&showdescription=no" class="external-link">J01CF06</a>), ceftolozane/enzyme inhibitor (<code>CEI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DI54&showdescription=no" class="external-link">J01CE06</a>), ceftriaxone (<code>CRO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD04&showdescription=no" class="external-link">J01CE05</a>), cefuroxime (<code>CXM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC02&showdescription=no" class="external-link">J01CE02</a>), cephalexin (<code>LEX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB01&showdescription=no" class="external-link">J01CA02</a>), cephalothin (<code>CEP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB03&showdescription=no" class="external-link">J01CA08</a>), cephapirin (<code>HAP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB08&showdescription=no" class="external-link">J01CE09</a>), cephradine (<code>CED</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB09&showdescription=no" class="external-link">J01CE03</a>), chloramphenicol (<code>CHL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01BA01&showdescription=no" class="external-link">J01CG01</a>), ciprofloxacin (<code>CIP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA02&showdescription=no" class="external-link">J01CA16</a>), clarithromycin (<code>CLR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA09&showdescription=no" class="external-link">J01CR04</a>), clindamycin (<code>CLI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FF01&showdescription=no" class="external-link">J01CA15</a>), clometocillin (<code>CLM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE07&showdescription=no" class="external-link">J01CG02</a>), cloxacillin (<code>CLO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF02&showdescription=no" class="external-link">J01CA17</a>), colistin (<code>COL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XB01&showdescription=no" class="external-link">J01CR03</a>), cycloserine (<code>CYC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J04AB01&showdescription=no" class="external-link">J01DB10</a>), dalbavancin (<code>DAL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA04&showdescription=no" class="external-link">J01DC04</a>), daptomycin (<code>DAP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XX09&showdescription=no" class="external-link">J01DB05</a>), delafloxacin (<code>DFX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA23&showdescription=no" class="external-link">J01DB02</a>), dibekacin (<code>DKB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB09&showdescription=no" class="external-link">J01DC03</a>), dicloxacillin (<code>DIC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF01&showdescription=no" class="external-link">J01DB07</a>), dirithromycin (<code>DIR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA13&showdescription=no" class="external-link">J01DB06</a>), doripenem (<code>DOR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH04&showdescription=no" class="external-link">J01DB04</a>), doxycycline (<code>DOX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01AA02&showdescription=no" class="external-link">J01DD17</a>), enoxacin (<code>ENX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA04&showdescription=no" class="external-link">J01DD15</a>), epicillin (<code>EPC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA07&showdescription=no" class="external-link">J01DD16</a>), ertapenem (<code>ETP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH03&showdescription=no" class="external-link">J01DE01</a>), erythromycin (<code>ERY</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA01&showdescription=no" class="external-link">J01DD10</a>), fleroxacin (<code>FLE</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA08&showdescription=no" class="external-link">J01DD08</a>), flucloxacillin (<code>FLC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF05&showdescription=no" class="external-link">J01DD05</a>), flurithromycin (<code>FLR1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA14&showdescription=no" class="external-link">J01DC09</a>), fosfomycin (<code>FOS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XX01&showdescription=no" class="external-link">J01DD09</a>), framycetin (<code>FRM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=D09AA01&showdescription=no" class="external-link">J01DC06</a>), fusidic acid (<code>FUS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XC01&showdescription=no" class="external-link">J01DD12</a>), garenoxacin (<code>GRN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA19&showdescription=no" class="external-link">J01DD62</a>), gatifloxacin (<code>GAT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA16&showdescription=no" class="external-link">J01DC11</a>), gemifloxacin (<code>GEM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA15&showdescription=no" class="external-link">J01DD01</a>), gentamicin (<code>GEN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB03&showdescription=no" class="external-link">J01DC05</a>), grepafloxacin (<code>GRX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA11&showdescription=no" class="external-link">J01DC07</a>), hetacillin (<code>HET</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA18&showdescription=no" class="external-link">J01DC01</a>), imipenem (<code>IPM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH51&showdescription=no" class="external-link">J01DE03</a>), isepamicin (<code>ISE</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB11&showdescription=no" class="external-link">J01DD11</a>), josamycin (<code>JOS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA07&showdescription=no" class="external-link">J01DE02</a>), kanamycin (<code>KAN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB04&showdescription=no" class="external-link">J01DD13</a>), latamoxef (<code>LTM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD06&showdescription=no" class="external-link">J01DC10</a>), levofloxacin (<code>LVX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA12&showdescription=no" class="external-link">J01DB11</a>), levonadifloxacin (<code>LND</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA24&showdescription=no" class="external-link">J01DD03</a>), lincomycin (<code>LIN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FF02&showdescription=no" class="external-link">J01DI02</a>), linezolid (<code>LNZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XX08&showdescription=no" class="external-link">J01DD02</a>), lomefloxacin (<code>LOM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA07&showdescription=no" class="external-link">J01DD52</a>), loracarbef (<code>LOR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC08&showdescription=no" class="external-link">J01DD18</a>), mecillinam (<code>MEC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA11&showdescription=no" class="external-link">J01DB12</a>), meropenem (<code>MEM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH02&showdescription=no" class="external-link">J01DD14</a>), meropenem/vaborbactam (<code>MEV</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH52&showdescription=no" class="external-link">J01DD07</a>), metampicillin (<code>MTM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA14&showdescription=no" class="external-link">J01DI01</a>), methicillin (<code>MET</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF03&showdescription=no" class="external-link">J01DI54</a>), mezlocillin (<code>MEZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA10&showdescription=no" class="external-link">J01DD04</a>), micronomicin (<code>MCR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=S01AA22&showdescription=no" class="external-link">J01DC02</a>), midecamycin (<code>MID</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA03&showdescription=no" class="external-link">J01DB01</a>), minocycline (<code>MNO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01AA08&showdescription=no" class="external-link">J01DB03</a>), miocamycin (<code>MCM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA11&showdescription=no" class="external-link">J01DB08</a>), moxifloxacin (<code>MFX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA14&showdescription=no" class="external-link">J01DB09</a>), nadifloxacin (<code>NAD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=D10AF05&showdescription=no" class="external-link">J01DD06</a>), nafcillin (<code>NAF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF06&showdescription=no" class="external-link">J01DC08</a>), nalidixic acid (<code>NAL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MB02&showdescription=no" class="external-link">J01DH05</a>), neomycin (<code>NEO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB05&showdescription=no" class="external-link">J01DH04</a>), netilmicin (<code>NET</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB07&showdescription=no" class="external-link">J01DH03</a>), nitrofurantoin (<code>NIT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XE01&showdescription=no" class="external-link">J01DH51</a>), norfloxacin (<code>NOR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA06&showdescription=no" class="external-link">J01DH02</a>), ofloxacin (<code>OFX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA01&showdescription=no" class="external-link">J01DH52</a>), oleandomycin (<code>OLE</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA05&showdescription=no" class="external-link">J01XA02</a>), oritavancin (<code>ORI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA05&showdescription=no" class="external-link">J01XA01</a>), oxacillin (<code>OXA</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF04&showdescription=no" class="external-link">J01XC01</a>), pazufloxacin (<code>PAZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA18&showdescription=no" class="external-link">J01FA13</a>), pefloxacin (<code>PEF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA03&showdescription=no" class="external-link">J01FA01</a>), penamecillin (<code>PNM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE06&showdescription=no" class="external-link">J01FA14</a>), phenethicillin (<code>PHE</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE05&showdescription=no" class="external-link">J01FA07</a>), phenoxymethylpenicillin (<code>PHN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE02&showdescription=no" class="external-link">J01FA03</a>), piperacillin (<code>PIP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA12&showdescription=no" class="external-link">J01FA11</a>), piperacillin/tazobactam (<code>TZP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR05&showdescription=no" class="external-link">J01FA05</a>), pivampicillin (<code>PVM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA02&showdescription=no" class="external-link">J01FA12</a>), pivmecillinam (<code>PME</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA08&showdescription=no" class="external-link">J01FA16</a>), plazomicin (<code>PLZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB14&showdescription=no" class="external-link">J01FA02</a>), polymyxin B (<code>PLB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XB02&showdescription=no" class="external-link">J01FA15</a>), pristinamycin (<code>PRI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FG01&showdescription=no" class="external-link">J01FA08</a>), procaine benzylpenicillin (<code>PRB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE09&showdescription=no" class="external-link">J01FF02</a>), propicillin (<code>PRP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE03&showdescription=no" class="external-link">J01FG01</a>), prulifloxacin (<code>PRU</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA17&showdescription=no" class="external-link">J01FG02</a>), quinupristin/dalfopristin (<code>QDA</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FG02&showdescription=no" class="external-link">J04AB02</a>), ribostamycin (<code>RST</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB10&showdescription=no" class="external-link">J01XX09</a>), rifampicin (<code>RIF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J04AB02&showdescription=no" class="external-link">J01XX08</a>), rokitamycin (<code>ROK</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA12&showdescription=no" class="external-link">J01AA07</a>), roxithromycin (<code>RXT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA06&showdescription=no" class="external-link">J01XB01</a>), rufloxacin (<code>RFL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA10&showdescription=no" class="external-link">J01XB02</a>), sisomicin (<code>SIS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB08&showdescription=no" class="external-link">J01XE01</a>), sitafloxacin (<code>SIT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA21&showdescription=no" class="external-link">J01AA12</a>), solithromycin (<code>SOL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA16&showdescription=no" class="external-link">J01EA01</a>), sparfloxacin (<code>SPX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA09&showdescription=no" class="external-link">J01XX01</a>), spiramycin (<code>SPI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA02&showdescription=no" class="external-link">J01BA01</a>), streptoduocin (<code>STR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GA02&showdescription=no" class="external-link">J01GB06</a>), streptomycin (<code>STR1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GA01&showdescription=no" class="external-link">J01GB12</a>), sulbactam (<code>SUL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CG01&showdescription=no" class="external-link">J01GB13</a>), sulbenicillin (<code>SBC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA16&showdescription=no" class="external-link">J01GB09</a>), sulfadiazine (<code>SDI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EC02&showdescription=no" class="external-link">D09AA01</a>), sulfadiazine/trimethoprim (<code>SLT1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE02&showdescription=no" class="external-link">J01GB03</a>), sulfadimethoxine (<code>SUD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED01&showdescription=no" class="external-link">J01GB11</a>), sulfadimidine (<code>SDM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB03&showdescription=no" class="external-link">J01GB04</a>), sulfadimidine/trimethoprim (<code>SLT2</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE05&showdescription=no" class="external-link">S01AA22</a>), sulfafurazole (<code>SLF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB05&showdescription=no" class="external-link">J01GB05</a>), sulfaisodimidine (<code>SLF1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB01&showdescription=no" class="external-link">J01GB07</a>), sulfalene (<code>SLF2</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED02&showdescription=no" class="external-link">J01GB14</a>), sulfamazone (<code>SZO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED09&showdescription=no" class="external-link">J01GB10</a>), sulfamerazine (<code>SLF3</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED07&showdescription=no" class="external-link">J01GB08</a>), sulfamerazine/trimethoprim (<code>SLT3</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE07&showdescription=no" class="external-link">J01GA02</a>), sulfamethizole (<code>SLF4</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB02&showdescription=no" class="external-link">J01GA01</a>), sulfamethoxazole (<code>SMX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EC01&showdescription=no" class="external-link">J01GB01</a>), sulfamethoxypyridazine (<code>SLF5</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED05&showdescription=no" class="external-link">J01EE01</a>), sulfametomidine (<code>SLF6</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED03&showdescription=no" class="external-link">J01MB02</a>), sulfametoxydiazine (<code>SLF7</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED04&showdescription=no" class="external-link">J01FF01</a>), sulfametrole/trimethoprim (<code>SLT4</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE03&showdescription=no" class="external-link">J01XA04</a>), sulfamoxole (<code>SLF8</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EC03&showdescription=no" class="external-link">J01XA05</a>), sulfamoxole/trimethoprim (<code>SLT5</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE04&showdescription=no" class="external-link">J01XA03</a>), sulfanilamide (<code>SLF9</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB06&showdescription=no" class="external-link">J04AB01</a>), sulfaperin (<code>SLF10</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED06&showdescription=no" class="external-link">J01XX11</a>), sulfaphenazole (<code>SLF11</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED08&showdescription=no" class="external-link">J01EC02</a>), sulfapyridine (<code>SLF12</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB04&showdescription=no" class="external-link">J01ED01</a>), sulfathiazole (<code>SUT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB07&showdescription=no" class="external-link">J01EB03</a>), sulfathiourea (<code>SLF13</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB08&showdescription=no" class="external-link">J01EB05</a>), sultamicillin (<code>SLT6</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR04&showdescription=no" class="external-link">J01EB01</a>), talampicillin (<code>TAL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA15&showdescription=no" class="external-link">J01ED02</a>), tazobactam (<code>TAZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CG02&showdescription=no" class="external-link">J01ED09</a>), tedizolid (<code>TZD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XX11&showdescription=no" class="external-link">J01ED07</a>), teicoplanin (<code>TEC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA02&showdescription=no" class="external-link">J01EB02</a>), telavancin (<code>TLV</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA03&showdescription=no" class="external-link">J01EC01</a>), telithromycin (<code>TLT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA15&showdescription=no" class="external-link">J01ED05</a>), temafloxacin (<code>TMX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA05&showdescription=no" class="external-link">J01ED03</a>), temocillin (<code>TEM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA17&showdescription=no" class="external-link">J01ED04</a>), tetracycline (<code>TCY</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01AA07&showdescription=no" class="external-link">J01EC03</a>), ticarcillin (<code>TIC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA13&showdescription=no" class="external-link">J01EB06</a>), ticarcillin/clavulanic acid (<code>TCC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR03&showdescription=no" class="external-link">J01ED06</a>), tigecycline (<code>TGC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01AA12&showdescription=no" class="external-link">J01ED08</a>), tilbroquinol (<code>TBQ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=P01AA05&showdescription=no" class="external-link">J01EB04</a>), tobramycin (<code>TOB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB01&showdescription=no" class="external-link">J01EB07</a>), tosufloxacin (<code>TFX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA22&showdescription=no" class="external-link">J01EB08</a>), trimethoprim (<code>TMP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EA01&showdescription=no" class="external-link">J01EE02</a>), trimethoprim/sulfamethoxazole (<code>SXT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE01&showdescription=no" class="external-link">J01EE05</a>), troleandomycin (<code>TRL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA08&showdescription=no" class="external-link">J01EE07</a>), trovafloxacin (<code>TVA</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA13&showdescription=no" class="external-link">J01EE03</a>), vancomycin (<code>VAN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA01&showdescription=no" class="external-link">J01EE04</a>)</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># \donttest{</span>
-<span class="va">a</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span>,
- <span class="st">"Enterococcus faecalis"</span>,
- <span class="st">"Escherichia coli"</span>,
- <span class="st">"Klebsiella pneumoniae"</span>,
- <span class="st">"Pseudomonas aeruginosa"</span><span class="op">)</span>,
- VAN <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Vancomycin</span>
- AMX <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Amoxicillin</span>
- COL <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Colistin</span>
- CAZ <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Ceftazidime</span>
- CXM <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Cefuroxime</span>
- PEN <span class="op">=</span> <span class="st">"S"</span>, <span class="co"># Benzylpenicillin</span>
- FOX <span class="op">=</span> <span class="st">"S"</span>, <span class="co"># Cefoxitin</span>
- stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="va">a</span>
-<span class="co"># mo VAN AMX COL CAZ CXM PEN FOX</span>
-<span class="co"># 1 Staphylococcus aureus - - - - - S S</span>
-<span class="co"># 2 Enterococcus faecalis - - - - - S S</span>
-<span class="co"># 3 Escherichia coli - - - - - S S</span>
-<span class="co"># 4 Klebsiella pneumoniae - - - - - S S</span>
-<span class="co"># 5 Pseudomonas aeruginosa - - - - - S S</span>
-
-
-<span class="co"># apply EUCAST rules: some results wil be changed</span>
-<span class="va">b</span> <span class="op"><-</span> <span class="fu">eucast_rules</span><span class="op">(</span><span class="va">a</span><span class="op">)</span>
-
-<span class="va">b</span>
-<span class="co"># mo VAN AMX COL CAZ CXM PEN FOX</span>
-<span class="co"># 1 Staphylococcus aureus - S R R S S S</span>
-<span class="co"># 2 Enterococcus faecalis - - R R R S R</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"># 5 Pseudomonas aeruginosa R R - - R R R</span>
-
-
-<span class="co"># do not apply EUCAST rules, but rather get a data.frame</span>
-<span class="co"># containing all details about the transformations:</span>
-<span class="va">c</span> <span class="op"><-</span> <span class="fu">eucast_rules</span><span class="op">(</span><span class="va">a</span>, verbose <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>
-<span class="co"># }</span>
-
-<span class="fu">eucast_dosage</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"tobra"</span>, <span class="st">"genta"</span>, <span class="st">"cipro"</span><span class="op">)</span>, <span class="st">"iv"</span><span class="op">)</span>
-</code></pre></div>
- </div>
- </div>
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- <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2>
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- <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p>
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-<div class="pkgdown">
- <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.3.</p>
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- <h1>Data Set with 2,000 Example Isolates</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>example_isolates.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>A data set containing 2,000 microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR data analysis. For examples, please read <a href="https://msberends.github.io/AMR/articles/AMR.html">the tutorial on our website</a>.</p>
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- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">example_isolates</span></code></pre></div>
- </div>
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- <div id="format">
- <h2>Format</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 2,000 observations and 49 variables:</p><ul><li><p><code>date</code><br> date of receipt at the laboratory</p></li>
-<li><p><code>hospital_id</code><br> ID of the hospital, from A to D</p></li>
-<li><p><code>ward_icu</code><br><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to determine if ward is an intensive care unit</p></li>
-<li><p><code>ward_clinical</code><br><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to determine if ward is a regular clinical ward</p></li>
-<li><p><code>ward_outpatient</code><br><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to determine if ward is an outpatient clinic</p></li>
-<li><p><code>age</code><br> age of the patient</p></li>
-<li><p><code>gender</code><br> gender of the patient</p></li>
-<li><p><code>patient_id</code><br> ID of the patient</p></li>
-<li><p><code>mo</code><br> ID of microorganism created with <code><a href="as.mo.html">as.mo()</a></code>, see also <a href="microorganisms.html">microorganisms</a></p></li>
-<li><p><code>PEN:RIF</code><br> 40 different antibiotics with class <code><a href="as.rsi.html">rsi</a></code> (see <code><a href="as.rsi.html">as.rsi()</a></code>); these column names occur in the <a href="antibiotics.html">antibiotics</a> data set and can be translated with <code><a href="ab_property.html">ab_name()</a></code></p></li>
-</ul></div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
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-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
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diff --git a/docs/reference/example_isolates_unclean.html b/docs/reference/example_isolates_unclean.html
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-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Data Set with Unclean Data — example_isolates_unclean • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link href="https://cdnjs.cloudflare.com/ajax/libs/bootswatch/3.4.0/flatly/bootstrap.min.css" rel="stylesheet" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with Unclean Data — example_isolates_unclean"><meta property="og:description" content="A data set containing 3,000 microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@univgroningen"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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- <h1>Data Set with Unclean Data</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>example_isolates_unclean.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>A data set containing 3,000 microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">example_isolates_unclean</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 3,000 observations and 8 variables:</p><ul><li><p><code>patient_id</code><br> ID of the patient</p></li>
-<li><p><code>date</code><br> date of receipt at the laboratory</p></li>
-<li><p><code>hospital</code><br> ID of the hospital, from A to C</p></li>
-<li><p><code>bacteria</code><br> info about microorganism that can be transformed with <code><a href="as.mo.html">as.mo()</a></code>, see also <a href="microorganisms.html">microorganisms</a></p></li>
-<li><p><code>AMX:GEN</code><br> 4 different antibiotics that have to be transformed with <code><a href="as.rsi.html">as.rsi()</a></code></p></li>
-</ul></div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
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-<!DOCTYPE html>
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- </ul></div><!--/.nav-collapse -->
- </div><!--/.container -->
-</div><!--/.navbar -->
-
-
-
- </header><div class="row">
- <div class="col-md-9 contents">
- <div class="page-header">
- <h1>Determine First Isolates</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/first_isolate.R" class="external-link"><code>R/first_isolate.R</code></a></small>
- <div class="hidden name"><code>first_isolate.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler <em>et al.</em> in 2007 (doi: <a href="https://doi.org/10.1086/511864" class="external-link">10.1086/511864</a>
-). To determine patient episodes not necessarily based on microorganisms, use <code><a href="get_episode.html">is_new_episode()</a></code> that also supports grouping with the <code>dplyr</code> package.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">first_isolate</span><span class="op">(</span>
- x <span class="op">=</span> <span class="cn">NULL</span>,
- col_date <span class="op">=</span> <span class="cn">NULL</span>,
- col_patient_id <span class="op">=</span> <span class="cn">NULL</span>,
- col_mo <span class="op">=</span> <span class="cn">NULL</span>,
- col_testcode <span class="op">=</span> <span class="cn">NULL</span>,
- col_specimen <span class="op">=</span> <span class="cn">NULL</span>,
- col_icu <span class="op">=</span> <span class="cn">NULL</span>,
- col_keyantimicrobials <span class="op">=</span> <span class="cn">NULL</span>,
- episode_days <span class="op">=</span> <span class="fl">365</span>,
- testcodes_exclude <span class="op">=</span> <span class="cn">NULL</span>,
- icu_exclude <span class="op">=</span> <span class="cn">FALSE</span>,
- specimen_group <span class="op">=</span> <span class="cn">NULL</span>,
- type <span class="op">=</span> <span class="st">"points"</span>,
- method <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"phenotype-based"</span>, <span class="st">"episode-based"</span>, <span class="st">"patient-based"</span>, <span class="st">"isolate-based"</span><span class="op">)</span>,
- ignore_I <span class="op">=</span> <span class="cn">TRUE</span>,
- points_threshold <span class="op">=</span> <span class="fl">2</span>,
- info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>,
- include_unknown <span class="op">=</span> <span class="cn">FALSE</span>,
- include_untested_rsi <span class="op">=</span> <span class="cn">TRUE</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="fu">filter_first_isolate</span><span class="op">(</span>
- x <span class="op">=</span> <span class="cn">NULL</span>,
- col_date <span class="op">=</span> <span class="cn">NULL</span>,
- col_patient_id <span class="op">=</span> <span class="cn">NULL</span>,
- col_mo <span class="op">=</span> <span class="cn">NULL</span>,
- episode_days <span class="op">=</span> <span class="fl">365</span>,
- method <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"phenotype-based"</span>, <span class="st">"episode-based"</span>, <span class="st">"patient-based"</span>, <span class="st">"isolate-based"</span><span class="op">)</span>,
- <span class="va">...</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="source">
- <h2>Source</h2>
- <p>Methodology of this function is strictly based on:</p><ul><li><p><strong>M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition</strong>, 2014, <em>Clinical and Laboratory Standards Institute (CLSI)</em>. <a href="https://clsi.org/standards/products/microbiology/documents/m39/" class="external-link">https://clsi.org/standards/products/microbiology/documents/m39/</a>.</p></li>
-<li><p>Hindler JF and Stelling J (2007). <strong>Analysis and Presentation of Cumulative Antibiograms: A New Consensus Guideline from the Clinical and Laboratory Standards Institute.</strong> Clinical Infectious Diseases, 44(6), 867-873. doi: <a href="https://doi.org/10.1086/511864" class="external-link">10.1086/511864</a></p></li>
-</ul></div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing isolates. Can be left blank for automatic determination, see <em>Examples</em>.</p></dd>
-<dt>col_date</dt>
-<dd><p>column name of the result date (or date that is was received on the lab), defaults to the first column with a date class</p></dd>
-<dt>col_patient_id</dt>
-<dd><p>column name of the unique IDs of the patients, defaults to the first column that starts with 'patient' or 'patid' (case insensitive)</p></dd>
-<dt>col_mo</dt>
-<dd><p>column name of the IDs of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>), defaults to the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
-<dt>col_testcode</dt>
-<dd><p>column name of the test codes. Use <code>col_testcode = NULL</code> to <strong>not</strong> exclude certain test codes (such as test codes for screening). In that case <code>testcodes_exclude</code> will be ignored.</p></dd>
-<dt>col_specimen</dt>
-<dd><p>column name of the specimen type or group</p></dd>
-<dt>col_icu</dt>
-<dd><p>column name of the logicals (<code>TRUE</code>/<code>FALSE</code>) whether a ward or department is an Intensive Care Unit (ICU)</p></dd>
-<dt>col_keyantimicrobials</dt>
-<dd><p>(only useful when <code>method = "phenotype-based"</code>) column name of the key antimicrobials to determine first isolates, see <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code>. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use <code>col_keyantimicrobials = FALSE</code> to prevent this. Can also be the output of <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code>.</p></dd>
-<dt>episode_days</dt>
-<dd><p>episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see <em>Source</em>.</p></dd>
-<dt>testcodes_exclude</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector with test codes that should be excluded (case-insensitive)</p></dd>
-<dt>icu_exclude</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether ICU isolates should be excluded (rows with value <code>TRUE</code> in the column set with <code>col_icu</code>)</p></dd>
-<dt>specimen_group</dt>
-<dd><p>value in the column set with <code>col_specimen</code> to filter on</p></dd>
-<dt>type</dt>
-<dd><p>type to determine weighed isolates; can be <code>"keyantimicrobials"</code> or <code>"points"</code>, see <em>Details</em></p></dd>
-<dt>method</dt>
-<dd><p>the method to apply, either <code>"phenotype-based"</code>, <code>"episode-based"</code>, <code>"patient-based"</code> or <code>"isolate-based"</code> (can be abbreviated), see <em>Details</em>. The default is <code>"phenotype-based"</code> if antimicrobial test results are present in the data, and <code>"episode-based"</code> otherwise.</p></dd>
-<dt>ignore_I</dt>
-<dd><p><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether antibiotic interpretations with <code>"I"</code> will be ignored when <code>type = "keyantimicrobials"</code>, see <em>Details</em></p></dd>
-<dt>points_threshold</dt>
-<dd><p>minimum number of points to require before differences in the antibiogram will lead to inclusion of an isolate when <code>type = "points"</code>, see <em>Details</em></p></dd>
-<dt>info</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate info should be printed, defaults to <code>TRUE</code> only in interactive mode</p></dd>
-<dt>include_unknown</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether 'unknown' microorganisms should be included too, i.e. microbial code <code>"UNKNOWN"</code>, which defaults to <code>FALSE</code>. For WHONET users, this means that all records with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default. Isolates with a microbial ID of <code>NA</code> will always be excluded as first isolate.</p></dd>
-<dt>include_untested_rsi</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether also rows without antibiotic results are still eligible for becoming a first isolate. Use <code>include_untested_rsi = FALSE</code> to always return <code>FALSE</code> for such rows. This checks the data set for columns of class <code><rsi></code> and consequently requires transforming columns with antibiotic results using <code><a href="as.rsi.html">as.rsi()</a></code> first.</p></dd>
-<dt>...</dt>
-<dd><p>arguments passed on to <code>first_isolate()</code> when using <code>filter_first_isolate()</code>, otherwise arguments passed on to <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code> (such as <code>universal</code>, <code>gram_negative</code>, <code>gram_positive</code>)</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>A <code><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a></code> vector</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>To conduct epidemiological analyses on antimicrobial resistance data, only so-called first isolates should be included to prevent overestimation and underestimation of antimicrobial resistance. Different methods can be used to do so, see below.</p>
-<p>These functions are context-aware. This means that the <code>x</code> argument can be left blank if used inside a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> call, see <em>Examples</em>.</p>
-<p>The <code>first_isolate()</code> function is a wrapper around the <code><a href="get_episode.html">is_new_episode()</a></code> function, but more efficient for data sets containing microorganism codes or names.</p>
-<p>All isolates with a microbial ID of <code>NA</code> will be excluded as first isolate.</p><div class="section">
-<h3 id="different-methods">Different methods<a class="anchor" aria-label="anchor" href="#different-methods"></a></h3>
-
-
-<p>According to Hindler <em>et al.</em> (2007, doi: <a href="https://doi.org/10.1086/511864" class="external-link">10.1086/511864</a>
-), there are different methods (algorithms) to select first isolates with increasing reliability: isolate-based, patient-based, episode-based and phenotype-based. All methods select on a combination of the taxonomic genus and species (not subspecies).</p>
-<p>All mentioned methods are covered in the <code>first_isolate()</code> function:</p><table class="table table"><tr><td><strong>Method</strong></td><td><strong>Function to apply</strong></td></tr><tr><td><strong>Isolate-based</strong></td><td><code>first_isolate(x, method = "isolate-based")</code></td></tr><tr><td><em>(= all isolates)</em></td><td></td></tr><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td><strong>Patient-based</strong></td><td><code>first_isolate(x, method = "patient-based")</code></td></tr><tr><td><em>(= first isolate per patient)</em></td><td></td></tr><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td><strong>Episode-based</strong></td><td><code>first_isolate(x, method = "episode-based")</code>, or:</td></tr><tr><td><em>(= first isolate per episode)</em></td><td></td></tr><tr><td>- 7-Day interval from initial isolate</td><td>- <code>first_isolate(x, method = "e", episode_days = 7)</code></td></tr><tr><td>- 30-Day interval from initial isolate</td><td>- <code>first_isolate(x, method = "e", episode_days = 30)</code></td></tr><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td><strong>Phenotype-based</strong></td><td><code>first_isolate(x, method = "phenotype-based")</code>, or:</td></tr><tr><td><em>(= first isolate per phenotype)</em></td><td></td></tr><tr><td>- Major difference in any antimicrobial result</td><td>- <code>first_isolate(x, type = "points")</code></td></tr><tr><td>- Any difference in key antimicrobial results</td><td>- <code>first_isolate(x, type = "keyantimicrobials")</code></td></tr></table><div class="section">
-<h4 id="isolate-based">Isolate-based<a class="anchor" aria-label="anchor" href="#isolate-based"></a></h4>
-
-
-<p>This method does not require any selection, as all isolates should be included. It does, however, respect all arguments set in the <code>first_isolate()</code> function. For example, the default setting for <code>include_unknown</code> (<code>FALSE</code>) will omit selection of rows without a microbial ID.</p>
-</div>
-
-<div class="section">
-<h4 id="patient-based">Patient-based<a class="anchor" aria-label="anchor" href="#patient-based"></a></h4>
-
-
-<p>To include every genus-species combination per patient once, set the <code>episode_days</code> to <code>Inf</code>. Although often inappropriate, this method makes sure that no duplicate isolates are selected from the same patient. In a large longitudinal data set, this could mean that isolates are <em>excluded</em> that were found years after the initial isolate.</p>
-</div>
-
-<div class="section">
-<h4 id="episode-based">Episode-based<a class="anchor" aria-label="anchor" href="#episode-based"></a></h4>
-
-
-<p>To include every genus-species combination per patient episode once, set the <code>episode_days</code> to a sensible number of days. Depending on the type of analysis, this could be 14, 30, 60 or 365. Short episodes are common for analysing specific hospital or ward data, long episodes are common for analysing regional and national data.</p>
-<p>This is the most common method to correct for duplicate isolates. Patients are categorised into episodes based on their ID and dates (e.g., the date of specimen receipt or laboratory result). While this is a common method, it does not take into account antimicrobial test results. This means that e.g. a methicillin-resistant <em>Staphylococcus aureus</em> (MRSA) isolate cannot be differentiated from a wildtype <em>Staphylococcus aureus</em> isolate.</p>
-</div>
-
-<div class="section">
-<h4 id="phenotype-based">Phenotype-based<a class="anchor" aria-label="anchor" href="#phenotype-based"></a></h4>
-
-
-<p>This is a more reliable method, since it also <em>weighs</em> the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram:</p><ol><li><p>Using <code>type = "points"</code> and argument <code>points_threshold</code> (default)</p>
-<p>This method weighs <em>all</em> antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as <code>0.5</code> points, a difference from S to R (or vice versa) counts as <code>1</code> point. When the sum of points exceeds <code>points_threshold</code>, which defaults to <code>2</code>, an isolate will be selected as a first weighted isolate.</p>
-<p>All antimicrobials are internally selected using the <code><a href="key_antimicrobials.html">all_antimicrobials()</a></code> function. The output of this function does not need to be passed to the <code>first_isolate()</code> function.</p></li>
-<li><p>Using <code>type = "keyantimicrobials"</code> and argument <code>ignore_I</code></p>
-<p>This method only weighs specific antimicrobial agents, called <em>key antimicrobials</em>. Any difference from S to R (or vice versa) in these key antimicrobials will select an isolate as a first weighted isolate. With <code>ignore_I = FALSE</code>, also differences from I to S or R (or vice versa) will lead to this.</p>
-<p>Key antimicrobials are internally selected using the <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code> function, but can also be added manually as a variable to the data and set in the <code>col_keyantimicrobials</code> argument. Another option is to pass the output of the <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code> function directly to the <code>col_keyantimicrobials</code> argument.</p></li>
-</ol><p>The default method is phenotype-based (using <code>type = "points"</code>) and episode-based (using <code>episode_days = 365</code>). This makes sure that every genus-species combination is selected per patient once per year, while taking into account all antimicrobial test results. If no antimicrobial test results are available in the data set, only the episode-based method is applied at default.</p>
-</div>
-
-
-</div>
-
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="key_antimicrobials.html">key_antimicrobials()</a></code></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># `example_isolates` is a data set available in the AMR package.</span>
-<span class="co"># See ?example_isolates.</span>
-
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu">first_isolate</span><span class="op">(</span><span class="op">)</span>, <span class="op">]</span>
-<span class="co"># \donttest{</span>
-<span class="co"># get all first Gram-negatives</span>
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu">first_isolate</span><span class="op">(</span><span class="op">)</span> <span class="op">&</span> <span class="fu"><a href="mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>, <span class="op">]</span>
-
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="co"># filter on first isolates using dplyr:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu">first_isolate</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># short-hand version:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">filter_first_isolate</span><span class="op">(</span><span class="op">)</span>
-
- <span class="co"># grouped determination of first isolates (also prints group names):</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>first <span class="op">=</span> <span class="fu">first_isolate</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># now let's see if first isolates matter:</span>
- <span class="va">A</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>count <span class="op">=</span> <span class="fu"><a href="count.html">n_rsi</a></span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span>, <span class="co"># gentamicin availability</span>
- resistance <span class="op">=</span> <span class="fu"><a href="proportion.html">resistance</a></span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span><span class="op">)</span> <span class="co"># gentamicin resistance</span>
-
- <span class="va">B</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">filter_first_isolate</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># the 1st isolate filter</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>count <span class="op">=</span> <span class="fu"><a href="count.html">n_rsi</a></span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span>, <span class="co"># gentamicin availability</span>
- resistance <span class="op">=</span> <span class="fu"><a href="proportion.html">resistance</a></span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span><span class="op">)</span> <span class="co"># gentamicin resistance</span>
-
- <span class="co"># Have a look at A and B.</span>
- <span class="co"># B is more reliable because every isolate is counted only once.</span>
- <span class="co"># Gentamicin resistance in hospital D appears to be 4.2% higher than</span>
- <span class="co"># when you (erroneously) would have used all isolates for analysis.</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
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- <h1><em>G</em>-test for Count Data</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/g.test.R" class="external-link"><code>R/g.test.R</code></a></small>
- <div class="hidden name"><code>g.test.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p><code>g.test()</code> performs chi-squared contingency table tests and goodness-of-fit tests, just like <code><a href="https://rdrr.io/r/stats/chisq.test.html" class="external-link">chisq.test()</a></code> but is more reliable (1). A <em>G</em>-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a <strong><em>G</em>-test of goodness-of-fit</strong>), or to see whether the proportions of one variable are different for different values of the other variable (called a <strong><em>G</em>-test of independence</strong>).</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">g.test</span><span class="op">(</span><span class="va">x</span>, y <span class="op">=</span> <span class="cn">NULL</span>, p <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="fl">1</span><span class="op">/</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span>, rescale.p <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="source">
- <h2>Source</h2>
- <p>The code for this function is identical to that of <code><a href="https://rdrr.io/r/stats/chisq.test.html" class="external-link">chisq.test()</a></code>, except that:</p><ul><li><p>The calculation of the statistic was changed to \(2 * sum(x * log(x / E))\)</p></li>
-<li><p>Yates' continuity correction was removed as it does not apply to a <em>G</em>-test</p></li>
-<li><p>The possibility to simulate p values with <code>simulate.p.value</code> was removed</p></li>
-</ul></div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a numeric vector or matrix. <code>x</code> and <code>y</code> can also
- both be factors.</p></dd>
-<dt>y</dt>
-<dd><p>a numeric vector; ignored if <code>x</code> is a matrix. If
- <code>x</code> is a factor, <code>y</code> should be a factor of the same length.</p></dd>
-<dt>p</dt>
-<dd><p>a vector of probabilities of the same length as <code>x</code>.
- An error is given if any entry of <code>p</code> is negative.</p></dd>
-<dt>rescale.p</dt>
-<dd><p>a logical scalar; if TRUE then <code>p</code> is rescaled
- (if necessary) to sum to 1. If <code>rescale.p</code> is FALSE, and
- <code>p</code> does not sum to 1, an error is given.</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>A list with class <code>"htest"</code> containing the following
- components:</p>
-<dl><dt>statistic</dt>
-<dd><p>the value the chi-squared test statistic.</p></dd>
-<dt>parameter</dt>
-<dd><p>the degrees of freedom of the approximate
- chi-squared distribution of the test statistic, <code>NA</code> if the
- p-value is computed by Monte Carlo simulation.</p></dd>
-<dt>p.value</dt>
-<dd><p>the p-value for the test.</p></dd>
-<dt>method</dt>
-<dd><p>a character string indicating the type of test
- performed, and whether Monte Carlo simulation or continuity
- correction was used.</p></dd>
-<dt>data.name</dt>
-<dd><p>a character string giving the name(s) of the data.</p></dd>
-<dt>observed</dt>
-<dd><p>the observed counts.</p></dd>
-<dt>expected</dt>
-<dd><p>the expected counts under the null hypothesis.</p></dd>
-<dt>residuals</dt>
-<dd><p>the Pearson residuals,
- <code>(observed - expected) / sqrt(expected)</code>.</p></dd>
-<dt>stdres</dt>
-<dd><p>standardized residuals,
- <code>(observed - expected) / sqrt(V)</code>, where <code>V</code> is the residual cell variance (Agresti, 2007,
- section 2.4.5 for the case where <code>x</code> is a matrix, <code>n * p * (1 - p)</code> otherwise).</p></dd>
-</dl></div>
- <div id="details">
- <h2>Details</h2>
- <p>If <code>x</code> is a <a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a> with one row or column, or if <code>x</code> is a vector and <code>y</code> is not given, then a <em>goodness-of-fit test</em> is performed (<code>x</code> is treated as a one-dimensional contingency table). The entries of <code>x</code> must be non-negative integers. In this case, the hypothesis tested is whether the population probabilities equal those in <code>p</code>, or are all equal if <code>p</code> is not given.</p>
-<p>If <code>x</code> is a <a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a> with at least two rows and columns, it is taken as a two-dimensional contingency table: the entries of <code>x</code> must be non-negative integers. Otherwise, <code>x</code> and <code>y</code> must be vectors or factors of the same length; cases with missing values are removed, the objects are coerced to factors, and the contingency table is computed from these. Then Pearson's chi-squared test is performed of the null hypothesis that the joint distribution of the cell counts in a 2-dimensional contingency table is the product of the row and column marginals.</p>
-<p>The p-value is computed from the asymptotic chi-squared distribution of the test statistic.</p>
-<p>In the contingency table case simulation is done by random sampling from the set of all contingency tables with given marginals, and works only if the marginals are strictly positive. Note that this is not the usual sampling situation assumed for a chi-squared test (such as the <em>G</em>-test) but rather that for Fisher's exact test.</p>
-<p>In the goodness-of-fit case simulation is done by random sampling from the discrete distribution specified by <code>p</code>, each sample being of size <code>n = sum(x)</code>. This simulation is done in <span style="R">R</span> and may be slow.</p><div class="section">
-<h3 id="g-test-of-goodness-of-fit-likelihood-ratio-test-"><em>G</em>-test Of Goodness-of-Fit (Likelihood Ratio Test)<a class="anchor" aria-label="anchor" href="#g-test-of-goodness-of-fit-likelihood-ratio-test-"></a></h3>
-
-
-<p>Use the <em>G</em>-test of goodness-of-fit when you have one nominal variable with two or more values (such as male and female, or red, pink and white flowers). You compare the observed counts of numbers of observations in each category with the expected counts, which you calculate using some kind of theoretical expectation (such as a 1:1 sex ratio or a 1:2:1 ratio in a genetic cross).</p>
-<p>If the expected number of observations in any category is too small, the <em>G</em>-test may give inaccurate results, and you should use an exact test instead (<code><a href="https://rdrr.io/r/stats/fisher.test.html" class="external-link">fisher.test()</a></code>).</p>
-<p>The <em>G</em>-test of goodness-of-fit is an alternative to the chi-square test of goodness-of-fit (<code><a href="https://rdrr.io/r/stats/chisq.test.html" class="external-link">chisq.test()</a></code>); each of these tests has some advantages and some disadvantages, and the results of the two tests are usually very similar.</p>
-</div>
-
-<div class="section">
-<h3 id="g-test-of-independence"><em>G</em>-test of Independence<a class="anchor" aria-label="anchor" href="#g-test-of-independence"></a></h3>
-
-
-<p>Use the <em>G</em>-test of independence when you have two nominal variables, each with two or more possible values. You want to know whether the proportions for one variable are different among values of the other variable.</p>
-<p>It is also possible to do a <em>G</em>-test of independence with more than two nominal variables. For example, Jackson et al. (2013) also had data for children under 3, so you could do an analysis of old vs. young, thigh vs. arm, and reaction vs. no reaction, all analyzed together.</p>
-<p>Fisher's exact test (<code><a href="https://rdrr.io/r/stats/fisher.test.html" class="external-link">fisher.test()</a></code>) is an <strong>exact</strong> test, where the <em>G</em>-test is still only an <strong>approximation</strong>. For any 2x2 table, Fisher's Exact test may be slower but will still run in seconds, even if the sum of your observations is multiple millions.</p>
-<p>The <em>G</em>-test of independence is an alternative to the chi-square test of independence (<code><a href="https://rdrr.io/r/stats/chisq.test.html" class="external-link">chisq.test()</a></code>), and they will give approximately the same results.</p>
-</div>
-
-<div class="section">
-<h3 id="how-the-test-works">How the Test Works<a class="anchor" aria-label="anchor" href="#how-the-test-works"></a></h3>
-
-
-<p>Unlike the exact test of goodness-of-fit (<code><a href="https://rdrr.io/r/stats/fisher.test.html" class="external-link">fisher.test()</a></code>), the <em>G</em>-test does not directly calculate the probability of obtaining the observed results or something more extreme. Instead, like almost all statistical tests, the <em>G</em>-test has an intermediate step; it uses the data to calculate a test statistic that measures how far the observed data are from the null expectation. You then use a mathematical relationship, in this case the chi-square distribution, to estimate the probability of obtaining that value of the test statistic.</p>
-<p>The <em>G</em>-test uses the log of the ratio of two likelihoods as the test statistic, which is why it is also called a likelihood ratio test or log-likelihood ratio test. The formula to calculate a <em>G</em>-statistic is:</p>
-<p>\(G = 2 * sum(x * log(x / E))\)</p>
-<p>where <code>E</code> are the expected values. Since this is chi-square distributed, the p value can be calculated in <span style="R">R</span> with:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>where <code>df</code> are the degrees of freedom.</p>
-<p>If there are more than two categories and you want to find out which ones are significantly different from their null expectation, you can use the same method of testing each category vs. the sum of all categories, with the Bonferroni correction. You use <em>G</em>-tests for each category, of course.</p>
-</div>
-
- </div>
- <div id="questioning-lifecycle">
- <h2>Questioning Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_questioning.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>questioning</strong>. This function might be no longer be optimal approach, or is it questionable whether this function should be in this <code>AMR</code> package at all.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="references">
- <h2>References</h2>
-
-<ol><li><p>McDonald, J.H. 2014. <strong>Handbook of Biological Statistics (3rd ed.)</strong>. Sparky House Publishing, Baltimore, Maryland. <a href="http://www.biostathandbook.com/gtestgof.html" class="external-link">http://www.biostathandbook.com/gtestgof.html</a>.</p></li>
-</ol></div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="https://rdrr.io/r/stats/chisq.test.html" class="external-link">chisq.test()</a></code></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># = EXAMPLE 1 =</span>
-<span class="co"># Shivrain et al. (2006) crossed clearfield rice (which are resistant</span>
-<span class="co"># to the herbicide imazethapyr) with red rice (which are susceptible to</span>
-<span class="co"># imazethapyr). They then crossed the hybrid offspring and examined the</span>
-<span class="co"># F2 generation, where they found 772 resistant plants, 1611 moderately</span>
-<span class="co"># resistant plants, and 737 susceptible plants. If resistance is controlled</span>
-<span class="co"># by a single gene with two co-dominant alleles, you would expect a 1:2:1</span>
-<span class="co"># ratio.</span>
-
-<span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">772</span>, <span class="fl">1611</span>, <span class="fl">737</span><span class="op">)</span>
-<span class="va">G</span> <span class="op"><-</span> <span class="fu">g.test</span><span class="op">(</span><span class="va">x</span>, p <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">1</span><span class="op">)</span> <span class="op">/</span> <span class="fl">4</span><span class="op">)</span>
-<span class="co"># G$p.value = 0.12574.</span>
-
-<span class="co"># There is no significant difference from a 1:2:1 ratio.</span>
-<span class="co"># Meaning: resistance controlled by a single gene with two co-dominant</span>
-<span class="co"># alleles, is plausible.</span>
-
-
-<span class="co"># = EXAMPLE 2 =</span>
-<span class="co"># Red crossbills (Loxia curvirostra) have the tip of the upper bill either</span>
-<span class="co"># right or left of the lower bill, which helps them extract seeds from pine</span>
-<span class="co"># cones. Some have hypothesized that frequency-dependent selection would</span>
-<span class="co"># keep the number of right and left-billed birds at a 1:1 ratio. Groth (1992)</span>
-<span class="co"># observed 1752 right-billed and 1895 left-billed crossbills.</span>
-
-<span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1752</span>, <span class="fl">1895</span><span class="op">)</span>
-<span class="fu">g.test</span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-<span class="co"># p = 0.01787343</span>
-
-<span class="co"># There is a significant difference from a 1:1 ratio.</span>
-<span class="co"># Meaning: there are significantly more left-billed birds.</span>
-
-</code></pre></div>
- </div>
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- <h1>Determine (New) Episodes for Patients</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/episode.R" class="external-link"><code>R/episode.R</code></a></small>
- <div class="hidden name"><code>get_episode.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument <code>episode_days</code>. This can be used to determine clinical episodes for any epidemiological analysis. The <code>get_episode()</code> function returns the index number of the episode per group, while the <code>is_new_episode()</code> function returns values <code>TRUE</code>/<code>FALSE</code> to indicate whether an item in a vector is the start of a new episode.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">get_episode</span><span class="op">(</span><span class="va">x</span>, <span class="va">episode_days</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">is_new_episode</span><span class="op">(</span><span class="va">x</span>, <span class="va">episode_days</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>vector of dates (class <code>Date</code> or <code>POSIXt</code>), will be sorted internally to determine episodes</p></dd>
-<dt>episode_days</dt>
-<dd><p>required episode length in days, can also be less than a day or <code>Inf</code>, see <em>Details</em></p></dd>
-<dt>...</dt>
-<dd><p>ignored, only in place to allow future extensions</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <ul><li><p><code>get_episode()</code>: a <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> vector</p></li>
-<li><p><code>is_new_episode()</code>: a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector</p></li>
-</ul></div>
- <div id="details">
- <h2>Details</h2>
- <p>Dates are first sorted from old to new. The oldest date will mark the start of the first episode. After this date, the next date will be marked that is at least <code>episode_days</code> days later than the start of the first episode. From that second marked date on, the next date will be marked that is at least <code>episode_days</code> days later than the start of the second episode which will be the start of the third episode, and so on. Before the vector is being returned, the original order will be restored.</p>
-<p>The <code><a href="first_isolate.html">first_isolate()</a></code> function is a wrapper around the <code>is_new_episode()</code> function, but is more efficient for data sets containing microorganism codes or names and allows for different isolate selection methods.</p>
-<p>The <code>dplyr</code> package is not required for these functions to work, but these functions do support <a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">variable grouping</a> and work conveniently inside <code>dplyr</code> verbs such as <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="first_isolate.html">first_isolate()</a></code></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># `example_isolates` is a data set available in the AMR package.</span>
-<span class="co"># See ?example_isolates.</span>
-
-<span class="fu">get_episode</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># indices</span>
-<span class="fu">is_new_episode</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># TRUE/FALSE</span>
-
-<span class="co"># filter on results from the third 60-day episode only, using base R</span>
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu">get_episode</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span> <span class="op">==</span> <span class="fl">3</span><span class="op">)</span>, <span class="op">]</span>
-
-<span class="co"># the functions also work for less than a day, e.g. to include one per hour:</span>
-<span class="fu">get_episode</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Sys.time.html" class="external-link">Sys.time</a></span><span class="op">(</span><span class="op">)</span>,
- <span class="fu"><a href="https://rdrr.io/r/base/Sys.time.html" class="external-link">Sys.time</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> <span class="fl">60</span> <span class="op">*</span> <span class="fl">60</span><span class="op">)</span>,
- episode_days <span class="op">=</span> <span class="fl">1</span><span class="op">/</span><span class="fl">24</span><span class="op">)</span>
-
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="co"># is_new_episode() can also be used in dplyr verbs to determine patient</span>
- <span class="co"># episodes based on any (combination of) grouping variables:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>condition <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"A"</span>, <span class="st">"B"</span>, <span class="st">"C"</span><span class="op">)</span>,
- size <span class="op">=</span> <span class="fl">2000</span>,
- replace <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">condition</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>new_episode <span class="op">=</span> <span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">365</span><span class="op">)</span><span class="op">)</span>
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span>, <span class="va">patient_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">transmute</a></span><span class="op">(</span><span class="va">date</span>,
- <span class="va">patient_id</span>,
- new_index <span class="op">=</span> <span class="fu">get_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span>,
- new_logical <span class="op">=</span> <span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span><span class="op">)</span>
-
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>patients <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct</a></span><span class="op">(</span><span class="va">patient_id</span><span class="op">)</span>,
- n_episodes_365 <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">365</span><span class="op">)</span><span class="op">)</span>,
- n_episodes_60 <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span><span class="op">)</span>,
- n_episodes_30 <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">30</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>
-
-
- <span class="co"># grouping on patients and microorganisms leads to the same</span>
- <span class="co"># results as first_isolate() when using 'episode-based':</span>
- <span class="va">x</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="first_isolate.html">filter_first_isolate</a></span><span class="op">(</span>include_unknown <span class="op">=</span> <span class="cn">TRUE</span>,
- method <span class="op">=</span> <span class="st">"episode-based"</span><span class="op">)</span>
-
- <span class="va">y</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">patient_id</span>, <span class="va">mo</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">365</span><span class="op">)</span><span class="op">)</span>
-
- <span class="fu"><a href="https://rdrr.io/r/base/identical.html" class="external-link">identical</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">patient_id</span>, <span class="va">y</span><span class="op">$</span><span class="va">patient_id</span><span class="op">)</span>
-
- <span class="co"># but is_new_episode() has a lot more flexibility than first_isolate(),</span>
- <span class="co"># since you can now group on anything that seems relevant:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">patient_id</span>, <span class="va">mo</span>, <span class="va">hospital_id</span>, <span class="va">ward_icu</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>flag_episode <span class="op">=</span> <span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">365</span><span class="op">)</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
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- <h1>PCA Biplot with <code>ggplot2</code></h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ggplot_pca.R" class="external-link"><code>R/ggplot_pca.R</code></a></small>
- <div class="hidden name"><code>ggplot_pca.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Produces a <code>ggplot2</code> variant of a so-called <a href="https://en.wikipedia.org/wiki/Biplot" class="external-link">biplot</a> for PCA (principal component analysis), but is more flexible and more appealing than the base <span style="R">R</span> <code><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot()</a></code> function.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">ggplot_pca</span><span class="op">(</span>
- <span class="va">x</span>,
- choices <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">2</span>,
- scale <span class="op">=</span> <span class="fl">1</span>,
- pc.biplot <span class="op">=</span> <span class="cn">TRUE</span>,
- labels <span class="op">=</span> <span class="cn">NULL</span>,
- labels_textsize <span class="op">=</span> <span class="fl">3</span>,
- labels_text_placement <span class="op">=</span> <span class="fl">1.5</span>,
- groups <span class="op">=</span> <span class="cn">NULL</span>,
- ellipse <span class="op">=</span> <span class="cn">TRUE</span>,
- ellipse_prob <span class="op">=</span> <span class="fl">0.68</span>,
- ellipse_size <span class="op">=</span> <span class="fl">0.5</span>,
- ellipse_alpha <span class="op">=</span> <span class="fl">0.5</span>,
- points_size <span class="op">=</span> <span class="fl">2</span>,
- points_alpha <span class="op">=</span> <span class="fl">0.25</span>,
- arrows <span class="op">=</span> <span class="cn">TRUE</span>,
- arrows_colour <span class="op">=</span> <span class="st">"darkblue"</span>,
- arrows_size <span class="op">=</span> <span class="fl">0.5</span>,
- arrows_textsize <span class="op">=</span> <span class="fl">3</span>,
- arrows_textangled <span class="op">=</span> <span class="cn">TRUE</span>,
- arrows_alpha <span class="op">=</span> <span class="fl">0.75</span>,
- base_textsize <span class="op">=</span> <span class="fl">10</span>,
- <span class="va">...</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="source">
- <h2>Source</h2>
- <p>The <code>ggplot_pca()</code> function is based on the <code>ggbiplot()</code> function from the <code>ggbiplot</code> package by Vince Vu, as found on GitHub: <a href="https://github.com/vqv/ggbiplot" class="external-link">https://github.com/vqv/ggbiplot</a> (retrieved: 2 March 2020, their latest commit: <a href="https://github.com/vqv/ggbiplot/commit/7325e880485bea4c07465a0304c470608fffb5d9" class="external-link"><code>7325e88</code></a>; 12 February 2015).</p>
-<p>As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:</p><ol><li><p>Rewritten code to remove the dependency on packages <code>plyr</code>, <code>scales</code> and <code>grid</code></p></li>
-<li><p>Parametrised more options, like arrow and ellipse settings</p></li>
-<li><p>Hardened all input possibilities by defining the exact type of user input for every argument</p></li>
-<li><p>Added total amount of explained variance as a caption in the plot</p></li>
-<li><p>Cleaned all syntax based on the <code>lintr</code> package, fixed grammatical errors and added integrity checks</p></li>
-<li><p>Updated documentation</p></li>
-</ol></div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>an object returned by <code><a href="pca.html">pca()</a></code>, <code><a href="https://rdrr.io/r/stats/prcomp.html" class="external-link">prcomp()</a></code> or <code><a href="https://rdrr.io/r/stats/princomp.html" class="external-link">princomp()</a></code></p></dd>
-<dt>choices</dt>
-<dd><p>length 2 vector specifying the components to plot. Only the default
- is a biplot in the strict sense.</p></dd>
-<dt>scale</dt>
-<dd><p>The variables are scaled by <code>lambda ^ scale</code> and the
- observations are scaled by <code>lambda ^ (1-scale)</code> where
- <code>lambda</code> are the singular values as computed by
- <code><a href="https://rdrr.io/r/stats/princomp.html" class="external-link">princomp</a></code>. Normally <code>0 <= scale <= 1</code>, and a warning
- will be issued if the specified <code>scale</code> is outside this range.</p></dd>
-<dt>pc.biplot</dt>
-<dd><p>If true, use what Gabriel (1971) refers to as a "principal component
- biplot", with <code>lambda = 1</code> and observations scaled up by sqrt(n) and
- variables scaled down by sqrt(n). Then inner products between
- variables approximate covariances and distances between observations
- approximate Mahalanobis distance.</p></dd>
-<dt>labels</dt>
-<dd><p>an optional vector of labels for the observations. If set, the labels will be placed below their respective points. When using the <code><a href="pca.html">pca()</a></code> function as input for <code>x</code>, this will be determined automatically based on the attribute <code>non_numeric_cols</code>, see <code><a href="pca.html">pca()</a></code>.</p></dd>
-<dt>labels_textsize</dt>
-<dd><p>the size of the text used for the labels</p></dd>
-<dt>labels_text_placement</dt>
-<dd><p>adjustment factor the placement of the variable names (<code>>=1</code> means further away from the arrow head)</p></dd>
-<dt>groups</dt>
-<dd><p>an optional vector of groups for the labels, with the same length as <code>labels</code>. If set, the points and labels will be coloured according to these groups. When using the <code><a href="pca.html">pca()</a></code> function as input for <code>x</code>, this will be determined automatically based on the attribute <code>non_numeric_cols</code>, see <code><a href="pca.html">pca()</a></code>.</p></dd>
-<dt>ellipse</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a normal data ellipse should be drawn for each group (set with <code>groups</code>)</p></dd>
-<dt>ellipse_prob</dt>
-<dd><p>statistical size of the ellipse in normal probability</p></dd>
-<dt>ellipse_size</dt>
-<dd><p>the size of the ellipse line</p></dd>
-<dt>ellipse_alpha</dt>
-<dd><p>the alpha (transparency) of the ellipse line</p></dd>
-<dt>points_size</dt>
-<dd><p>the size of the points</p></dd>
-<dt>points_alpha</dt>
-<dd><p>the alpha (transparency) of the points</p></dd>
-<dt>arrows</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether arrows should be drawn</p></dd>
-<dt>arrows_colour</dt>
-<dd><p>the colour of the arrow and their text</p></dd>
-<dt>arrows_size</dt>
-<dd><p>the size (thickness) of the arrow lines</p></dd>
-<dt>arrows_textsize</dt>
-<dd><p>the size of the text at the end of the arrows</p></dd>
-<dt>arrows_textangled</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> whether the text at the end of the arrows should be angled</p></dd>
-<dt>arrows_alpha</dt>
-<dd><p>the alpha (transparency) of the arrows and their text</p></dd>
-<dt>base_textsize</dt>
-<dd><p>the text size for all plot elements except the labels and arrows</p></dd>
-<dt>...</dt>
-<dd><p>arguments passed on to functions</p></dd>
-</dl></div>
- <div id="details">
- <h2>Details</h2>
- <p>The colours for labels and points can be changed by adding another scale layer for colour, such as <code><a href="https://ggplot2.tidyverse.org/reference/scale_viridis.html" class="external-link">scale_colour_viridis_d()</a></code> and <code><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_colour_brewer()</a></code>.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># `example_isolates` is a data set available in the AMR package.</span>
-<span class="co"># See ?example_isolates.</span>
-
-<span class="co"># See ?pca for more info about Principal Component Analysis (PCA).</span>
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">pca_model</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Staphylococcus"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>species <span class="op">=</span> <span class="fu"><a href="mo_property.html">mo_shortname</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html" class="external-link">summarise_if</a></span> <span class="op">(</span><span class="va">is.rsi</span>, <span class="va">resistance</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="pca.html">pca</a></span><span class="op">(</span><span class="va">FLC</span>, <span class="va">AMC</span>, <span class="va">CXM</span>, <span class="va">GEN</span>, <span class="va">TOB</span>, <span class="va">TMP</span>, <span class="va">SXT</span>, <span class="va">CIP</span>, <span class="va">TEC</span>, <span class="va">TCY</span>, <span class="va">ERY</span><span class="op">)</span>
-
- <span class="co"># old (base R)</span>
- <span class="fu"><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot</a></span><span class="op">(</span><span class="va">pca_model</span><span class="op">)</span>
-
- <span class="co"># new </span>
- <span class="fu">ggplot_pca</span><span class="op">(</span><span class="va">pca_model</span><span class="op">)</span>
-
- <span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://ggplot2.tidyverse.org" class="external-link">"ggplot2"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="fu">ggplot_pca</span><span class="op">(</span><span class="va">pca_model</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_viridis.html" class="external-link">scale_colour_viridis_d</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"Title here"</span><span class="op">)</span>
- <span class="op">}</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
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- <h1>AMR Plots with <code>ggplot2</code></h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ggplot_rsi.R" class="external-link"><code>R/ggplot_rsi.R</code></a></small>
- <div class="hidden name"><code>ggplot_rsi.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Use these functions to create bar plots for AMR data analysis. All functions rely on <a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot2</a> functions.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">ggplot_rsi</span><span class="op">(</span>
- <span class="va">data</span>,
- position <span class="op">=</span> <span class="cn">NULL</span>,
- x <span class="op">=</span> <span class="st">"antibiotic"</span>,
- fill <span class="op">=</span> <span class="st">"interpretation"</span>,
- facet <span class="op">=</span> <span class="cn">NULL</span>,
- breaks <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">0.1</span><span class="op">)</span>,
- limits <span class="op">=</span> <span class="cn">NULL</span>,
- translate_ab <span class="op">=</span> <span class="st">"name"</span>,
- combine_SI <span class="op">=</span> <span class="cn">TRUE</span>,
- combine_IR <span class="op">=</span> <span class="cn">FALSE</span>,
- minimum <span class="op">=</span> <span class="fl">30</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- nrow <span class="op">=</span> <span class="cn">NULL</span>,
- colours <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>S <span class="op">=</span> <span class="st">"#3CAEA3"</span>, SI <span class="op">=</span> <span class="st">"#3CAEA3"</span>, I <span class="op">=</span> <span class="st">"#F6D55C"</span>, IR <span class="op">=</span> <span class="st">"#ED553B"</span>, R <span class="op">=</span>
- <span class="st">"#ED553B"</span><span class="op">)</span>,
- datalabels <span class="op">=</span> <span class="cn">TRUE</span>,
- datalabels.size <span class="op">=</span> <span class="fl">2.5</span>,
- datalabels.colour <span class="op">=</span> <span class="st">"grey15"</span>,
- title <span class="op">=</span> <span class="cn">NULL</span>,
- subtitle <span class="op">=</span> <span class="cn">NULL</span>,
- caption <span class="op">=</span> <span class="cn">NULL</span>,
- x.title <span class="op">=</span> <span class="st">"Antimicrobial"</span>,
- y.title <span class="op">=</span> <span class="st">"Proportion"</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="fu">geom_rsi</span><span class="op">(</span>
- position <span class="op">=</span> <span class="cn">NULL</span>,
- x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"antibiotic"</span>, <span class="st">"interpretation"</span><span class="op">)</span>,
- fill <span class="op">=</span> <span class="st">"interpretation"</span>,
- translate_ab <span class="op">=</span> <span class="st">"name"</span>,
- minimum <span class="op">=</span> <span class="fl">30</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- combine_SI <span class="op">=</span> <span class="cn">TRUE</span>,
- combine_IR <span class="op">=</span> <span class="cn">FALSE</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="fu">facet_rsi</span><span class="op">(</span>facet <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"interpretation"</span>, <span class="st">"antibiotic"</span><span class="op">)</span>, nrow <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span>
-
-<span class="fu">scale_y_percent</span><span class="op">(</span>breaks <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">0.1</span><span class="op">)</span>, limits <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span>
-
-<span class="fu">scale_rsi_colours</span><span class="op">(</span><span class="va">...</span>, aesthetics <span class="op">=</span> <span class="st">"fill"</span><span class="op">)</span>
-
-<span class="fu">theme_rsi</span><span class="op">(</span><span class="op">)</span>
-
-<span class="fu">labels_rsi_count</span><span class="op">(</span>
- position <span class="op">=</span> <span class="cn">NULL</span>,
- x <span class="op">=</span> <span class="st">"antibiotic"</span>,
- translate_ab <span class="op">=</span> <span class="st">"name"</span>,
- minimum <span class="op">=</span> <span class="fl">30</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- combine_SI <span class="op">=</span> <span class="cn">TRUE</span>,
- combine_IR <span class="op">=</span> <span class="cn">FALSE</span>,
- datalabels.size <span class="op">=</span> <span class="fl">3</span>,
- datalabels.colour <span class="op">=</span> <span class="st">"grey15"</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>data</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with column(s) of class <code><a href="as.rsi.html">rsi</a></code> (see <code><a href="as.rsi.html">as.rsi()</a></code>)</p></dd>
-<dt>position</dt>
-<dd><p>position adjustment of bars, either <code>"fill"</code>, <code>"stack"</code> or <code>"dodge"</code></p></dd>
-<dt>x</dt>
-<dd><p>variable to show on x axis, either <code>"antibiotic"</code> (default) or <code>"interpretation"</code> or a grouping variable</p></dd>
-<dt>fill</dt>
-<dd><p>variable to categorise using the plots legend, either <code>"antibiotic"</code> (default) or <code>"interpretation"</code> or a grouping variable</p></dd>
-<dt>facet</dt>
-<dd><p>variable to split plots by, either <code>"interpretation"</code> (default) or <code>"antibiotic"</code> or a grouping variable</p></dd>
-<dt>breaks</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> vector of positions</p></dd>
-<dt>limits</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> vector of length two providing limits of the scale, use <code>NA</code> to refer to the existing minimum or maximum</p></dd>
-<dt>translate_ab</dt>
-<dd><p>a column name of the <a href="antibiotics.html">antibiotics</a> data set to translate the antibiotic abbreviations to, using <code><a href="ab_property.html">ab_property()</a></code></p></dd>
-<dt>combine_SI</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument <code>combine_IR</code>, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is <code>TRUE</code>.</p></dd>
-<dt>combine_IR</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see argument <code>combine_SI</code>.</p></dd>
-<dt>minimum</dt>
-<dd><p>the minimum allowed number of available (tested) isolates. Any isolate count lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see <em>Source</em>.</p></dd>
-<dt>language</dt>
-<dd><p>language of the returned text, defaults to system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with <code>getOption("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
-<dt>nrow</dt>
-<dd><p>(when using <code>facet</code>) number of rows</p></dd>
-<dt>colours</dt>
-<dd><p>a named vactor with colour to be used for filling. The default colours are colour-blind friendly.</p></dd>
-<dt>datalabels</dt>
-<dd><p>show datalabels using <code>labels_rsi_count()</code></p></dd>
-<dt>datalabels.size</dt>
-<dd><p>size of the datalabels</p></dd>
-<dt>datalabels.colour</dt>
-<dd><p>colour of the datalabels</p></dd>
-<dt>title</dt>
-<dd><p>text to show as title of the plot</p></dd>
-<dt>subtitle</dt>
-<dd><p>text to show as subtitle of the plot</p></dd>
-<dt>caption</dt>
-<dd><p>text to show as caption of the plot</p></dd>
-<dt>x.title</dt>
-<dd><p>text to show as x axis description</p></dd>
-<dt>y.title</dt>
-<dd><p>text to show as y axis description</p></dd>
-<dt>...</dt>
-<dd><p>other arguments passed on to <code>geom_rsi()</code> or, in case of <code>scale_rsi_colours()</code>, named values to set colours. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red. See <em>Examples</em>.</p></dd>
-<dt>aesthetics</dt>
-<dd><p>aesthetics to apply the colours to, defaults to "fill" but can also be (a combination of) "alpha", "colour", "fill", "linetype", "shape" or "size"</p></dd>
-</dl></div>
- <div id="details">
- <h2>Details</h2>
- <p>At default, the names of antibiotics will be shown on the plots using <code><a href="ab_property.html">ab_name()</a></code>. This can be set with the <code>translate_ab</code> argument. See <code><a href="count.html">count_df()</a></code>.</p><div class="section">
-<h3 id="the-functions">The Functions<a class="anchor" aria-label="anchor" href="#the-functions"></a></h3>
-
-
-<p><code>geom_rsi()</code> will take any variable from the data that has an <code><a href="as.rsi.html">rsi</a></code> class (created with <code><a href="as.rsi.html">as.rsi()</a></code>) using <code><a href="proportion.html">rsi_df()</a></code> and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.</p>
-<p><code>facet_rsi()</code> creates 2d plots (at default based on S/I/R) using <code><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">ggplot2::facet_wrap()</a></code>.</p>
-<p><code>scale_y_percent()</code> transforms the y axis to a 0 to 100% range using <code><a href="https://ggplot2.tidyverse.org/reference/scale_continuous.html" class="external-link">ggplot2::scale_y_continuous()</a></code>.</p>
-<p><code>scale_rsi_colours()</code> sets colours to the bars (green for S, yellow for I, and red for R). with multilingual support. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red.</p>
-<p><code>theme_rsi()</code> is a [ggplot2 theme][<code><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">ggplot2::theme()</a></code> with minimal distraction.</p>
-<p><code>labels_rsi_count()</code> print datalabels on the bars with percentage and amount of isolates using <code><a href="https://ggplot2.tidyverse.org/reference/geom_text.html" class="external-link">ggplot2::geom_text()</a></code>.</p>
-<p><code>ggplot_rsi()</code> is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (<code>%>%</code>). See <em>Examples</em>.</p>
-</div>
-
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://ggplot2.tidyverse.org" class="external-link">"ggplot2"</a></span><span class="op">)</span> <span class="op">&</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
-
- <span class="co"># get antimicrobial results for drugs against a UTI:</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">NIT</span>, <span class="va">FOS</span>, <span class="va">TMP</span>, <span class="va">CIP</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu">geom_rsi</span><span class="op">(</span><span class="op">)</span>
-
- <span class="co"># prettify the plot using some additional functions:</span>
- <span class="va">df</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">NIT</span>, <span class="va">FOS</span>, <span class="va">TMP</span>, <span class="va">CIP</span><span class="op">)</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">df</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu">geom_rsi</span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu">scale_y_percent</span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu">scale_rsi_colours</span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu">labels_rsi_count</span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu">theme_rsi</span><span class="op">(</span><span class="op">)</span>
-
- <span class="co"># or better yet, simplify this using the wrapper function - a single command:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">NIT</span>, <span class="va">FOS</span>, <span class="va">TMP</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">ggplot_rsi</span><span class="op">(</span><span class="op">)</span>
-
- <span class="co"># get only proportions and no counts:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">NIT</span>, <span class="va">FOS</span>, <span class="va">TMP</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">ggplot_rsi</span><span class="op">(</span>datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
- <span class="co"># add other ggplot2 arguments as you like:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">NIT</span>, <span class="va">FOS</span>, <span class="va">TMP</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">ggplot_rsi</span><span class="op">(</span>width <span class="op">=</span> <span class="fl">0.5</span>,
- colour <span class="op">=</span> <span class="st">"black"</span>,
- size <span class="op">=</span> <span class="fl">1</span>,
- linetype <span class="op">=</span> <span class="fl">2</span>,
- alpha <span class="op">=</span> <span class="fl">0.25</span><span class="op">)</span>
-
- <span class="co"># you can alter the colours with colour names:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">ggplot_rsi</span><span class="op">(</span>colours <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>SI <span class="op">=</span> <span class="st">"yellow"</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># but you can also use the built-in colour-blind friendly colours for</span>
- <span class="co"># your plots, where "S" is green, "I" is yellow and "R" is red:</span>
- <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Value1"</span>, <span class="st">"Value2"</span>, <span class="st">"Value3"</span><span class="op">)</span>,
- y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">3</span><span class="op">)</span>,
- z <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Value4"</span>, <span class="st">"Value5"</span>, <span class="st">"Value6"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html" class="external-link">geom_col</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">x</span>, y <span class="op">=</span> <span class="va">y</span>, fill <span class="op">=</span> <span class="va">z</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu">scale_rsi_colours</span><span class="op">(</span>Value4 <span class="op">=</span> <span class="st">"S"</span>, Value5 <span class="op">=</span> <span class="st">"I"</span>, Value6 <span class="op">=</span> <span class="st">"R"</span><span class="op">)</span>
-
- <span class="co"># resistance of ciprofloxacine per age group</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>first_isolate <span class="op">=</span> <span class="fu"><a href="first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">first_isolate</span> <span class="op">==</span> <span class="cn">TRUE</span>,
- <span class="va">mo</span> <span class="op">==</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># age_groups() is also a function in this AMR package:</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>age_group <span class="op">=</span> <span class="fu"><a href="age_groups.html">age_groups</a></span><span class="op">(</span><span class="va">age</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">age_group</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">ggplot_rsi</span><span class="op">(</span>x <span class="op">=</span> <span class="st">"age_group"</span><span class="op">)</span>
-
- <span class="co"># a shorter version which also adjusts data label colours:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">NIT</span>, <span class="va">FOS</span>, <span class="va">TMP</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">ggplot_rsi</span><span class="op">(</span>colours <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-
- <span class="co"># it also supports groups (don't forget to use the group var on `x` or `facet`):</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="co"># select only UTI-specific drugs</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">hospital_id</span>, <span class="va">AMX</span>, <span class="va">NIT</span>, <span class="va">FOS</span>, <span class="va">TMP</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">ggplot_rsi</span><span class="op">(</span>x <span class="op">=</span> <span class="st">"hospital_id"</span>,
- facet <span class="op">=</span> <span class="st">"antibiotic"</span>,
- nrow <span class="op">=</span> <span class="fl">1</span>,
- title <span class="op">=</span> <span class="st">"AMR of Anti-UTI Drugs Per Hospital"</span>,
- x.title <span class="op">=</span> <span class="st">"Hospital"</span>,
- datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
- <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2>
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- <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p>
-</div>
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-<div class="pkgdown">
- <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.3.</p>
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diff --git a/docs/reference/guess_ab_col.html b/docs/reference/guess_ab_col.html
deleted file mode 100644
index 636d182b5..000000000
--- a/docs/reference/guess_ab_col.html
+++ /dev/null
@@ -1,261 +0,0 @@
-<!DOCTYPE html>
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- <h1>Guess Antibiotic Column</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/guess_ab_col.R" class="external-link"><code>R/guess_ab_col.R</code></a></small>
- <div class="hidden name"><code>guess_ab_col.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>This tries to find a column name in a data set based on information from the <a href="antibiotics.html">antibiotics</a> data set. Also supports WHONET abbreviations.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">guess_ab_col</span><span class="op">(</span>
- x <span class="op">=</span> <span class="cn">NULL</span>,
- search_string <span class="op">=</span> <span class="cn">NULL</span>,
- verbose <span class="op">=</span> <span class="cn">FALSE</span>,
- only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p></dd>
-<dt>search_string</dt>
-<dd><p>a text to search <code>x</code> for, will be checked with <code><a href="as.ab.html">as.ab()</a></code> if this value is not a column in <code>x</code></p></dd>
-<dt>verbose</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether additional info should be printed</p></dd>
-<dt>only_rsi_columns</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only antibiotic columns must be detected that were transformed to class <code><rsi></code> (see <code><a href="as.rsi.html">as.rsi()</a></code>) on beforehand (defaults to <code>FALSE</code>)</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>A column name of <code>x</code>, or <code>NULL</code> when no result is found.</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>You can look for an antibiotic (trade) name or abbreviation and it will search <code>x</code> and the <a href="antibiotics.html">antibiotics</a> data set for any column containing a name or code of that antibiotic. <strong>Longer columns names take precedence over shorter column names.</strong></p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">df</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>amox <span class="op">=</span> <span class="st">"S"</span>,
- tetr <span class="op">=</span> <span class="st">"R"</span><span class="op">)</span>
-
-<span class="fu">guess_ab_col</span><span class="op">(</span><span class="va">df</span>, <span class="st">"amoxicillin"</span><span class="op">)</span>
-<span class="co"># [1] "amox"</span>
-<span class="fu">guess_ab_col</span><span class="op">(</span><span class="va">df</span>, <span class="st">"J01AA07"</span><span class="op">)</span> <span class="co"># ATC code of tetracycline</span>
-<span class="co"># [1] "tetr"</span>
-
-<span class="fu">guess_ab_col</span><span class="op">(</span><span class="va">df</span>, <span class="st">"J01AA07"</span>, verbose <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>
-<span class="co"># NOTE: Using column 'tetr' as input for J01AA07 (tetracycline).</span>
-<span class="co"># [1] "tetr"</span>
-
-<span class="co"># WHONET codes</span>
-<span class="va">df</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>AMP_ND10 <span class="op">=</span> <span class="st">"R"</span>,
- AMC_ED20 <span class="op">=</span> <span class="st">"S"</span><span class="op">)</span>
-<span class="fu">guess_ab_col</span><span class="op">(</span><span class="va">df</span>, <span class="st">"ampicillin"</span><span class="op">)</span>
-<span class="co"># [1] "AMP_ND10"</span>
-<span class="fu">guess_ab_col</span><span class="op">(</span><span class="va">df</span>, <span class="st">"J01CR02"</span><span class="op">)</span>
-<span class="co"># [1] "AMC_ED20"</span>
-<span class="fu">guess_ab_col</span><span class="op">(</span><span class="va">df</span>, <span class="fu"><a href="as.ab.html">as.ab</a></span><span class="op">(</span><span class="st">"augmentin"</span><span class="op">)</span><span class="op">)</span>
-<span class="co"># [1] "AMC_ED20"</span>
-
-<span class="co"># Longer names take precendence:</span>
-<span class="va">df</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>AMP_ED2 <span class="op">=</span> <span class="st">"S"</span>,
- AMP_ED20 <span class="op">=</span> <span class="st">"S"</span><span class="op">)</span>
-<span class="fu">guess_ab_col</span><span class="op">(</span><span class="va">df</span>, <span class="st">"ampicillin"</span><span class="op">)</span>
-<span class="co"># [1] "AMP_ED20"</span>
-</code></pre></div>
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- <h1>Reference</h1>
- </div>
-
- <table class="ref-index"><colgroup><col class="alias"><col class="title"></colgroup><tbody><tr><th colspan="2">
- <h2 id="preparing-data-microorganisms">Preparing data: microorganisms <a href="#preparing-data-microorganisms" class="anchor" aria-hidden="true"></a></h2>
- <p class="section-desc"></p><p>These functions are meant to get taxonomically valid properties of microorganisms from any input. Use <code><a href="../reference/mo_source.html">mo_source()</a></code> to teach this package how to translate your own codes to valid microorganism codes.</p>
- </th>
- </tr></tbody><tbody><tr><td>
- <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><p>Transform Input to a Microorganism Code</p></td>
- </tr><tr><td>
- <p><code><a href="mo_property.html">mo_name()</a></code> <code><a href="mo_property.html">mo_fullname()</a></code> <code><a href="mo_property.html">mo_shortname()</a></code> <code><a href="mo_property.html">mo_subspecies()</a></code> <code><a href="mo_property.html">mo_species()</a></code> <code><a href="mo_property.html">mo_genus()</a></code> <code><a href="mo_property.html">mo_family()</a></code> <code><a href="mo_property.html">mo_order()</a></code> <code><a href="mo_property.html">mo_class()</a></code> <code><a href="mo_property.html">mo_phylum()</a></code> <code><a href="mo_property.html">mo_kingdom()</a></code> <code><a href="mo_property.html">mo_domain()</a></code> <code><a href="mo_property.html">mo_type()</a></code> <code><a href="mo_property.html">mo_gramstain()</a></code> <code><a href="mo_property.html">mo_is_gram_negative()</a></code> <code><a href="mo_property.html">mo_is_gram_positive()</a></code> <code><a href="mo_property.html">mo_is_yeast()</a></code> <code><a href="mo_property.html">mo_is_intrinsic_resistant()</a></code> <code><a href="mo_property.html">mo_snomed()</a></code> <code><a href="mo_property.html">mo_ref()</a></code> <code><a href="mo_property.html">mo_authors()</a></code> <code><a href="mo_property.html">mo_year()</a></code> <code><a href="mo_property.html">mo_lpsn()</a></code> <code><a href="mo_property.html">mo_rank()</a></code> <code><a href="mo_property.html">mo_taxonomy()</a></code> <code><a href="mo_property.html">mo_synonyms()</a></code> <code><a href="mo_property.html">mo_info()</a></code> <code><a href="mo_property.html">mo_url()</a></code> <code><a href="mo_property.html">mo_property()</a></code> </p>
- </td>
- <td><p>Get Properties of a Microorganism</p></td>
- </tr><tr><td>
- <p><code><a href="mo_source.html">set_mo_source()</a></code> <code><a href="mo_source.html">get_mo_source()</a></code> </p>
- </td>
- <td><p>User-Defined Reference Data Set for Microorganisms</p></td>
- </tr></tbody><tbody><tr><th colspan="2">
- <h2 id="preparing-data-antibiotics">Preparing data: antibiotics <a href="#preparing-data-antibiotics" class="anchor" aria-hidden="true"></a></h2>
- <p class="section-desc"></p><p>Use these functions to get valid properties of antibiotics from any input or to clean your input. You can even retrieve drug names and doses from clinical text records, using <code><a href="../reference/ab_from_text.html">ab_from_text()</a></code>.</p>
- </th>
- </tr></tbody><tbody><tr><td>
- <p><code><a href="as.ab.html">as.ab()</a></code> <code><a href="as.ab.html">is.ab()</a></code> </p>
- </td>
- <td><p>Transform Input to an Antibiotic ID</p></td>
- </tr><tr><td>
- <p><code><a href="ab_property.html">ab_name()</a></code> <code><a href="ab_property.html">ab_cid()</a></code> <code><a href="ab_property.html">ab_synonyms()</a></code> <code><a href="ab_property.html">ab_tradenames()</a></code> <code><a href="ab_property.html">ab_group()</a></code> <code><a href="ab_property.html">ab_atc()</a></code> <code><a href="ab_property.html">ab_atc_group1()</a></code> <code><a href="ab_property.html">ab_atc_group2()</a></code> <code><a href="ab_property.html">ab_loinc()</a></code> <code><a href="ab_property.html">ab_ddd()</a></code> <code><a href="ab_property.html">ab_ddd_units()</a></code> <code><a href="ab_property.html">ab_info()</a></code> <code><a href="ab_property.html">ab_url()</a></code> <code><a href="ab_property.html">ab_property()</a></code> <code><a href="ab_property.html">set_ab_names()</a></code> </p>
- </td>
- <td><p>Get Properties of an Antibiotic</p></td>
- </tr><tr><td>
- <p><code><a href="ab_from_text.html">ab_from_text()</a></code> </p>
- </td>
- <td><p>Retrieve Antimicrobial Drug Names and Doses from Clinical Text</p></td>
- </tr><tr><td>
- <p><code><a href="atc_online.html">atc_online_property()</a></code> <code><a href="atc_online.html">atc_online_groups()</a></code> <code><a href="atc_online.html">atc_online_ddd()</a></code> <code><a href="atc_online.html">atc_online_ddd_units()</a></code> </p>
- </td>
- <td><p>Get ATC Properties from WHOCC Website</p></td>
- </tr></tbody><tbody><tr><th colspan="2">
- <h2 id="preparing-data-antimicrobial-resistance">Preparing data: antimicrobial resistance <a href="#preparing-data-antimicrobial-resistance" class="anchor" aria-hidden="true"></a></h2>
- <p class="section-desc"></p><p>With <code><a href="../reference/as.mic.html">as.mic()</a></code> and <code><a href="../reference/as.disk.html">as.disk()</a></code> you can transform your raw input to valid MIC or disk diffusion values. Use <code><a href="../reference/as.rsi.html">as.rsi()</a></code> for cleaning raw data to let it only contain “R”, “I” and “S”, or to interpret MIC or disk diffusion values as R/SI based on the lastest EUCAST and CLSI guidelines. Afterwards, you can extend antibiotic interpretations by applying <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">EUCAST rules</a> with <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>.</p>
- </th>
- </tr></tbody><tbody><tr><td>
- <p><code><a href="as.rsi.html">as.rsi()</a></code> <code><a href="as.rsi.html">NA_rsi_</a></code> <code><a href="as.rsi.html">is.rsi()</a></code> <code><a href="as.rsi.html">is.rsi.eligible()</a></code> </p>
- </td>
- <td><p>Interpret MIC and Disk Values, or Clean Raw R/SI Data</p></td>
- </tr><tr><td>
- <p><code><a href="as.mic.html">as.mic()</a></code> <code><a href="as.mic.html">NA_mic_</a></code> <code><a href="as.mic.html">is.mic()</a></code> <code><a href="as.mic.html">droplevels(<i><mic></i>)</a></code> </p>
- </td>
- <td><p>Transform Input to Minimum Inhibitory Concentrations (MIC)</p></td>
- </tr><tr><td>
- <p><code><a href="as.disk.html">as.disk()</a></code> <code><a href="as.disk.html">NA_disk_</a></code> <code><a href="as.disk.html">is.disk()</a></code> </p>
- </td>
- <td><p>Transform Input to Disk Diffusion Diameters</p></td>
- </tr><tr><td>
- <p><code><a href="eucast_rules.html">eucast_rules()</a></code> <code><a href="eucast_rules.html">eucast_dosage()</a></code> </p>
- </td>
- <td><p>Apply EUCAST Rules</p></td>
- </tr><tr><td>
- <p><code><a href="custom_eucast_rules.html">custom_eucast_rules()</a></code> </p>
- </td>
- <td><p>Define Custom EUCAST Rules</p></td>
- </tr></tbody><tbody><tr><th colspan="2">
- <h2 id="analysing-data-antimicrobial-resistance">Analysing data: antimicrobial resistance <a href="#analysing-data-antimicrobial-resistance" class="anchor" aria-hidden="true"></a></h2>
- <p class="section-desc"></p><p>Use these function for the analysis part. You can use <code><a href="../reference/proportion.html">susceptibility()</a></code> or <code><a href="../reference/proportion.html">resistance()</a></code> on any antibiotic column. Be sure to first select the isolates that are appropiate for analysis, by using <code><a href="../reference/first_isolate.html">first_isolate()</a></code> or <code><a href="../reference/get_episode.html">is_new_episode()</a></code>. You can also filter your data on certain resistance in certain antibiotic classes (<code><a href="../reference/antibiotic_class_selectors.html">carbapenems()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code>), or determine multi-drug resistant microorganisms (MDRO, <code><a href="../reference/mdro.html">mdro()</a></code>).</p>
- </th>
- </tr></tbody><tbody><tr><td>
- <p><code><a href="proportion.html">resistance()</a></code> <code><a href="proportion.html">susceptibility()</a></code> <code><a href="proportion.html">proportion_R()</a></code> <code><a href="proportion.html">proportion_IR()</a></code> <code><a href="proportion.html">proportion_I()</a></code> <code><a href="proportion.html">proportion_SI()</a></code> <code><a href="proportion.html">proportion_S()</a></code> <code><a href="proportion.html">proportion_df()</a></code> <code><a href="proportion.html">rsi_df()</a></code> </p>
- </td>
- <td><p>Calculate Microbial Resistance</p></td>
- </tr><tr><td>
- <p><code><a href="count.html">count_resistant()</a></code> <code><a href="count.html">count_susceptible()</a></code> <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><p>Count Available Isolates</p></td>
- </tr><tr><td>
- <p><code><a href="get_episode.html">get_episode()</a></code> <code><a href="get_episode.html">is_new_episode()</a></code> </p>
- </td>
- <td><p>Determine (New) Episodes for Patients</p></td>
- </tr><tr><td>
- <p><code><a href="first_isolate.html">first_isolate()</a></code> <code><a href="first_isolate.html">filter_first_isolate()</a></code> </p>
- </td>
- <td><p>Determine First Isolates</p></td>
- </tr><tr><td>
- <p><code><a href="key_antimicrobials.html">key_antimicrobials()</a></code> <code><a href="key_antimicrobials.html">all_antimicrobials()</a></code> <code><a href="key_antimicrobials.html">antimicrobials_equal()</a></code> </p>
- </td>
- <td><p>(Key) Antimicrobials for First Weighted Isolates</p></td>
- </tr><tr><td>
- <p><code><a href="mdro.html">mdro()</a></code> <code><a href="mdro.html">custom_mdro_guideline()</a></code> <code><a href="mdro.html">brmo()</a></code> <code><a href="mdro.html">mrgn()</a></code> <code><a href="mdro.html">mdr_tb()</a></code> <code><a href="mdro.html">mdr_cmi2012()</a></code> <code><a href="mdro.html">eucast_exceptional_phenotypes()</a></code> </p>
- </td>
- <td><p>Determine Multidrug-Resistant Organisms (MDRO)</p></td>
- </tr><tr><td>
- <p><code><a href="plot.html">plot(<i><mic></i>)</a></code> <code><a href="plot.html">autoplot(<i><mic></i>)</a></code> <code><a href="plot.html">fortify(<i><mic></i>)</a></code> <code><a href="plot.html">plot(<i><disk></i>)</a></code> <code><a href="plot.html">autoplot(<i><disk></i>)</a></code> <code><a href="plot.html">fortify(<i><disk></i>)</a></code> <code><a href="plot.html">plot(<i><rsi></i>)</a></code> <code><a href="plot.html">autoplot(<i><rsi></i>)</a></code> <code><a href="plot.html">fortify(<i><rsi></i>)</a></code> </p>
- </td>
- <td><p>Plotting for Classes <code>rsi</code>, <code>mic</code> and <code>disk</code></p></td>
- </tr><tr><td>
- <p><code><a href="ggplot_rsi.html">ggplot_rsi()</a></code> <code><a href="ggplot_rsi.html">geom_rsi()</a></code> <code><a href="ggplot_rsi.html">facet_rsi()</a></code> <code><a href="ggplot_rsi.html">scale_y_percent()</a></code> <code><a href="ggplot_rsi.html">scale_rsi_colours()</a></code> <code><a href="ggplot_rsi.html">theme_rsi()</a></code> <code><a href="ggplot_rsi.html">labels_rsi_count()</a></code> </p>
- </td>
- <td><p>AMR Plots with <code>ggplot2</code></p></td>
- </tr><tr><td>
- <p><code><a href="bug_drug_combinations.html">bug_drug_combinations()</a></code> <code><a href="bug_drug_combinations.html">format(<i><bug_drug_combinations></i>)</a></code> </p>
- </td>
- <td><p>Determine Bug-Drug Combinations</p></td>
- </tr><tr><td>
- <p><code><a href="antibiotic_class_selectors.html">ab_class()</a></code> <code><a href="antibiotic_class_selectors.html">ab_selector()</a></code> <code><a href="antibiotic_class_selectors.html">aminoglycosides()</a></code> <code><a href="antibiotic_class_selectors.html">aminopenicillins()</a></code> <code><a href="antibiotic_class_selectors.html">antifungals()</a></code> <code><a href="antibiotic_class_selectors.html">antimycobacterials()</a></code> <code><a href="antibiotic_class_selectors.html">betalactams()</a></code> <code><a href="antibiotic_class_selectors.html">carbapenems()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_1st()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_2nd()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_3rd()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_4th()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_5th()</a></code> <code><a href="antibiotic_class_selectors.html">fluoroquinolones()</a></code> <code><a href="antibiotic_class_selectors.html">glycopeptides()</a></code> <code><a href="antibiotic_class_selectors.html">lincosamides()</a></code> <code><a href="antibiotic_class_selectors.html">lipoglycopeptides()</a></code> <code><a href="antibiotic_class_selectors.html">macrolides()</a></code> <code><a href="antibiotic_class_selectors.html">oxazolidinones()</a></code> <code><a href="antibiotic_class_selectors.html">penicillins()</a></code> <code><a href="antibiotic_class_selectors.html">polymyxins()</a></code> <code><a href="antibiotic_class_selectors.html">streptogramins()</a></code> <code><a href="antibiotic_class_selectors.html">quinolones()</a></code> <code><a href="antibiotic_class_selectors.html">tetracyclines()</a></code> <code><a href="antibiotic_class_selectors.html">trimethoprims()</a></code> <code><a href="antibiotic_class_selectors.html">ureidopenicillins()</a></code> <code><a href="antibiotic_class_selectors.html">administrable_per_os()</a></code> <code><a href="antibiotic_class_selectors.html">administrable_iv()</a></code> <code><a href="antibiotic_class_selectors.html">not_intrinsic_resistant()</a></code> </p>
- </td>
- <td><p>Antibiotic Selectors</p></td>
- </tr><tr><td>
- <p><code><a href="resistance_predict.html">resistance_predict()</a></code> <code><a href="resistance_predict.html">rsi_predict()</a></code> <code><a href="resistance_predict.html">plot(<i><resistance_predict></i>)</a></code> <code><a href="resistance_predict.html">ggplot_rsi_predict()</a></code> <code><a href="resistance_predict.html">autoplot(<i><resistance_predict></i>)</a></code> </p>
- </td>
- <td><p>Predict Antimicrobial Resistance</p></td>
- </tr><tr><td>
- <p><code><a href="guess_ab_col.html">guess_ab_col()</a></code> </p>
- </td>
- <td><p>Guess Antibiotic Column</p></td>
- </tr></tbody><tbody><tr><th colspan="2">
- <h2 id="background-information-on-included-data">Background information on included data <a href="#background-information-on-included-data" class="anchor" aria-hidden="true"></a></h2>
- <p class="section-desc"></p><p>Some pages about our package and its external sources. Be sure to read our <a href="./../articles/index.html">How To’s</a> for more information about how to work with functions in this package.</p>
- </th>
- </tr></tbody><tbody><tr><td>
- <p><code><a href="AMR.html">AMR</a></code> </p>
- </td>
- <td><p>The <code>AMR</code> Package</p></td>
- </tr><tr><td>
- <p><code><a href="example_isolates.html">example_isolates</a></code> </p>
- </td>
- <td><p>Data Set with 2,000 Example Isolates</p></td>
- </tr><tr><td>
- <p><code><a href="microorganisms.html">microorganisms</a></code> </p>
- </td>
- <td><p>Data Set with 70,764 Microorganisms</p></td>
- </tr><tr><td>
- <p><code><a href="microorganisms.codes.html">microorganisms.codes</a></code> </p>
- </td>
- <td><p>Data Set with 5,604 Common Microorganism Codes</p></td>
- </tr><tr><td>
- <p><code><a href="microorganisms.old.html">microorganisms.old</a></code> </p>
- </td>
- <td><p>Data Set with Previously Accepted Taxonomic Names</p></td>
- </tr><tr><td>
- <p><code><a href="antibiotics.html">antibiotics</a></code> <code><a href="antibiotics.html">antivirals</a></code> </p>
- </td>
- <td><p>Data Sets with 566 Antimicrobial Drugs</p></td>
- </tr><tr><td>
- <p><code><a href="intrinsic_resistant.html">intrinsic_resistant</a></code> </p>
- </td>
- <td><p>Data Set with Bacterial Intrinsic Resistance</p></td>
- </tr><tr><td>
- <p><code><a href="dosage.html">dosage</a></code> </p>
- </td>
- <td><p>Data Set with Treatment Dosages as Defined by EUCAST</p></td>
- </tr><tr><td>
- <p><code><a href="catalogue_of_life.html">catalogue_of_life</a></code> </p>
- </td>
- <td><p>The Catalogue of Life</p></td>
- </tr><tr><td>
- <p><code><a href="catalogue_of_life_version.html">catalogue_of_life_version()</a></code> </p>
- </td>
- <td><p>Version info of included Catalogue of Life</p></td>
- </tr><tr><td>
- <p><code><a href="WHOCC.html">WHOCC</a></code> </p>
- </td>
- <td><p>WHOCC: WHO Collaborating Centre for Drug Statistics Methodology</p></td>
- </tr><tr><td>
- <p><code><a href="lifecycle.html">lifecycle</a></code> </p>
- </td>
- <td><p>Lifecycles of Functions in the <code>AMR</code> Package</p></td>
- </tr><tr><td>
- <p><code><a href="example_isolates_unclean.html">example_isolates_unclean</a></code> </p>
- </td>
- <td><p>Data Set with Unclean Data</p></td>
- </tr><tr><td>
- <p><code><a href="rsi_translation.html">rsi_translation</a></code> </p>
- </td>
- <td><p>Data Set for R/SI Interpretation</p></td>
- </tr><tr><td>
- <p><code><a href="WHONET.html">WHONET</a></code> </p>
- </td>
- <td><p>Data Set with 500 Isolates - WHONET Example</p></td>
- </tr></tbody><tbody><tr><th colspan="2">
- <h2 id="other-miscellaneous-functions">Other: miscellaneous functions <a href="#other-miscellaneous-functions" class="anchor" aria-hidden="true"></a></h2>
- <p class="section-desc"></p><p>These functions are mostly for internal use, but some of them may also be suitable for your analysis. Especially the ‘like’ function can be useful: <code>if (x %like% y) {...}</code>.</p>
- </th>
- </tr></tbody><tbody><tr><td>
- <p><code><a href="age_groups.html">age_groups()</a></code> </p>
- </td>
- <td><p>Split Ages into Age Groups</p></td>
- </tr><tr><td>
- <p><code><a href="age.html">age()</a></code> </p>
- </td>
- <td><p>Age in Years of Individuals</p></td>
- </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>
- <p><code><a href="translate.html">get_AMR_locale()</a></code> </p>
- </td>
- <td><p>Translate Strings from AMR Package</p></td>
- </tr><tr><td>
- <p><code><a href="ggplot_pca.html">ggplot_pca()</a></code> </p>
- </td>
- <td><p>PCA Biplot with <code>ggplot2</code></p></td>
- </tr><tr><td>
- <p><code><a href="italicise_taxonomy.html">italicise_taxonomy()</a></code> <code><a href="italicise_taxonomy.html">italicize_taxonomy()</a></code> </p>
- </td>
- <td><p>Italicise Taxonomic Families, Genera, Species, Subspecies</p></td>
- </tr><tr><td>
- <p><code><a href="join.html">inner_join_microorganisms()</a></code> <code><a href="join.html">left_join_microorganisms()</a></code> <code><a href="join.html">right_join_microorganisms()</a></code> <code><a href="join.html">full_join_microorganisms()</a></code> <code><a href="join.html">semi_join_microorganisms()</a></code> <code><a href="join.html">anti_join_microorganisms()</a></code> </p>
- </td>
- <td><p>Join microorganisms to a Data Set</p></td>
- </tr><tr><td>
- <p><code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> <code><a href="like.html">`%unlike%`</a></code> <code><a href="like.html">`%like_case%`</a></code> <code><a href="like.html">`%unlike_case%`</a></code> </p>
- </td>
- <td><p>Vectorised Pattern Matching with Keyboard Shortcut</p></td>
- </tr><tr><td>
- <p><code><a href="mo_matching_score.html">mo_matching_score()</a></code> </p>
- </td>
- <td><p>Calculate the Matching Score for Microorganisms</p></td>
- </tr><tr><td>
- <p><code><a href="pca.html">pca()</a></code> </p>
- </td>
- <td><p>Principal Component Analysis (for AMR)</p></td>
- </tr><tr><td>
- <p><code><a href="random.html">random_mic()</a></code> <code><a href="random.html">random_disk()</a></code> <code><a href="random.html">random_rsi()</a></code> </p>
- </td>
- <td><p>Random MIC Values/Disk Zones/RSI Generation</p></td>
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- <h1>Data Set with Bacterial Intrinsic Resistance</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>intrinsic_resistant.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">intrinsic_resistant</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 134,956 observations and 2 variables:</p><ul><li><p><code>mo</code><br> Microorganism ID</p></li>
-<li><p><code>ab</code><br> Antibiotic ID</p></li>
-</ul></div>
- <div id="details">
- <h2>Details</h2>
- <p>The repository of this <code>AMR</code> package contains a file comprising this data set with full taxonomic and antibiotic names: <a href="https://github.com/msberends/AMR/blob/main/data-raw/intrinsic_resistant.txt" class="external-link">https://github.com/msberends/AMR/blob/main/data-raw/intrinsic_resistant.txt</a>. This file <strong>allows for machine reading EUCAST guidelines about intrinsic resistance</strong>, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically.</p>
-<p>This data set is based on <a href="https://www.eucast.org/expert_rules_and_expected_phenotypes/" class="external-link">'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3</a> (2021).</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">intrinsic_resistant</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>,
- ab <span class="op">=</span> <span class="fu"><a href="ab_property.html">ab_name</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">ab</span> <span class="op">==</span> <span class="st">"Vancomycin"</span> <span class="op">&</span> <span class="va">mo</span> <span class="op"><a href="like.html">%like%</a></span> <span class="st">"Enterococcus"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>
- <span class="co">#> [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
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diff --git a/docs/reference/italicise_taxonomy.html b/docs/reference/italicise_taxonomy.html
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- <span class="fa fa-bug"></span>
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- Get properties of a microorganism
- </a>
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- <li>
- <a href="../reference/ab_property.html">
- <span class="fa fa-capsules"></span>
-
- Get properties of an antibiotic
- </a>
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- <div class="col-md-9 contents">
- <div class="page-header">
- <h1>Italicise Taxonomic Families, Genera, Species, Subspecies</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/italicise_taxonomy.R" class="external-link"><code>R/italicise_taxonomy.R</code></a></small>
- <div class="hidden name"><code>italicise_taxonomy.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italic. This function finds taxonomic names within strings and makes them italic.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">italicise_taxonomy</span><span class="op">(</span><span class="va">string</span>, type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"markdown"</span>, <span class="st">"ansi"</span><span class="op">)</span><span class="op">)</span>
-
-<span class="fu">italicize_taxonomy</span><span class="op">(</span><span class="va">string</span>, type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"markdown"</span>, <span class="st">"ansi"</span><span class="op">)</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>string</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vector)</p></dd>
-<dt>type</dt>
-<dd><p>type of conversion of the taxonomic names, either "markdown" or "ansi", see <em>Details</em></p></dd>
-</dl></div>
- <div id="details">
- <h2>Details</h2>
- <p>This function finds the taxonomic names and makes them italic based on the <a href="microorganisms.html">microorganisms</a> data set.</p>
-<p>The taxonomic names can be italicised using markdown (the default) by adding <code>*</code> before and after the taxonomic names, or using ANSI colours by adding <code>\033[3m</code> before and <code>\033[23m</code> after the taxonomic names. If multiple ANSI colours are not available, no conversion will occur.</p>
-<p>This function also supports abbreviation of the genus if it is followed by a species, such as "E. coli" and "K. pneumoniae ozaenae".</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">italicise_taxonomy</span><span class="op">(</span><span class="st">"An overview of Staphylococcus aureus isolates"</span><span class="op">)</span>
-<span class="fu">italicise_taxonomy</span><span class="op">(</span><span class="st">"An overview of S. aureus isolates"</span><span class="op">)</span>
-
-<span class="fu"><a href="https://rdrr.io/r/base/cat.html" class="external-link">cat</a></span><span class="op">(</span><span class="fu">italicise_taxonomy</span><span class="op">(</span><span class="st">"An overview of S. aureus isolates"</span>, type <span class="op">=</span> <span class="st">"ansi"</span><span class="op">)</span><span class="op">)</span>
-
-<span class="co"># since ggplot2 supports no markdown (yet), use</span>
-<span class="co"># italicise_taxonomy() and the `ggtext` package for titles:</span>
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://ggplot2.tidyverse.org" class="external-link">"ggplot2"</a></span><span class="op">)</span> <span class="op">&&</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://wilkelab.org/ggtext/" class="external-link">"ggtext"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMC</span>,
- title <span class="op">=</span> <span class="fu">italicise_taxonomy</span><span class="op">(</span><span class="st">"Amoxi/clav in E. coli"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>plot.title <span class="op">=</span> <span class="fu">ggtext</span><span class="fu">::</span><span class="fu">element_markdown</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
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- <div class="page-header">
- <h1>Join <a href="microorganisms.html">microorganisms</a> to a Data Set</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/join_microorganisms.R" class="external-link"><code>R/join_microorganisms.R</code></a></small>
- <div class="hidden name"><code>join.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Join the data set <a href="microorganisms.html">microorganisms</a> easily to an existing data set or to a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">inner_join_microorganisms</span><span class="op">(</span><span class="va">x</span>, by <span class="op">=</span> <span class="cn">NULL</span>, suffix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"2"</span>, <span class="st">""</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">left_join_microorganisms</span><span class="op">(</span><span class="va">x</span>, by <span class="op">=</span> <span class="cn">NULL</span>, suffix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"2"</span>, <span class="st">""</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">right_join_microorganisms</span><span class="op">(</span><span class="va">x</span>, by <span class="op">=</span> <span class="cn">NULL</span>, suffix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"2"</span>, <span class="st">""</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">full_join_microorganisms</span><span class="op">(</span><span class="va">x</span>, by <span class="op">=</span> <span class="cn">NULL</span>, suffix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"2"</span>, <span class="st">""</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">semi_join_microorganisms</span><span class="op">(</span><span class="va">x</span>, by <span class="op">=</span> <span class="cn">NULL</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">anti_join_microorganisms</span><span class="op">(</span><span class="va">x</span>, by <span class="op">=</span> <span class="cn">NULL</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>existing data set to join, or <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector. In case of a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector, the resulting <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> will contain a column 'x' with these values.</p></dd>
-<dt>by</dt>
-<dd><p>a variable to join by - if left empty will search for a column with class <code><a href="as.mo.html">mo</a></code> (created with <code><a href="as.mo.html">as.mo()</a></code>) or will be <code>"mo"</code> if that column name exists in <code>x</code>, could otherwise be a column name of <code>x</code> with values that exist in <code>microorganisms$mo</code> (such as <code>by = "bacteria_id"</code>), or another column in <a href="microorganisms.html">microorganisms</a> (but then it should be named, like <code>by = c("bacteria_id" = "fullname")</code>)</p></dd>
-<dt>suffix</dt>
-<dd><p>if there are non-joined duplicate variables in <code>x</code> and <code>y</code>, these suffixes will be added to the output to disambiguate them. Should be a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector of length 2.</p></dd>
-<dt>...</dt>
-<dd><p>ignored, only in place to allow future extensions</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p><strong>Note:</strong> As opposed to the <code>join()</code> functions of <code>dplyr</code>, <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vectors are supported and at default existing columns will get a suffix <code>"2"</code> and the newly joined columns will not get a suffix.</p>
-<p>If the <code>dplyr</code> package is installed, their join functions will be used. Otherwise, the much slower <code><a href="https://rdrr.io/r/base/merge.html" class="external-link">merge()</a></code> and <code><a href="https://rdrr.io/r/base/interaction.html" class="external-link">interaction()</a></code> functions from base <span style="R">R</span> will be used.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">left_join_microorganisms</span><span class="op">(</span><span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span><span class="op">)</span>
-<span class="fu">left_join_microorganisms</span><span class="op">(</span><span class="st">"B_KLBSL_PNMN"</span><span class="op">)</span>
-
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">left_join_microorganisms</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span>
-
- <span class="va">df</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>date <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span>from <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/as.Date.html" class="external-link">as.Date</a></span><span class="op">(</span><span class="st">"2018-01-01"</span><span class="op">)</span>,
- to <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/as.Date.html" class="external-link">as.Date</a></span><span class="op">(</span><span class="st">"2018-01-07"</span><span class="op">)</span>,
- by <span class="op">=</span> <span class="fl">1</span><span class="op">)</span>,
- bacteria <span class="op">=</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"S. aureus"</span>, <span class="st">"MRSA"</span>, <span class="st">"MSSA"</span>, <span class="st">"STAAUR"</span>,
- <span class="st">"E. coli"</span>, <span class="st">"E. coli"</span>, <span class="st">"E. coli"</span><span class="op">)</span><span class="op">)</span>,
- stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
- <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="va">df</span><span class="op">)</span>
- <span class="va">df_joined</span> <span class="op"><-</span> <span class="fu">left_join_microorganisms</span><span class="op">(</span><span class="va">df</span>, <span class="st">"bacteria"</span><span class="op">)</span>
- <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="va">df_joined</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
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- <h1>(Key) Antimicrobials for First Weighted Isolates</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/key_antimicrobials.R" class="external-link"><code>R/key_antimicrobials.R</code></a></small>
- <div class="hidden name"><code>key_antimicrobials.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>These functions can be used to determine first weighted isolates by considering the phenotype for isolate selection (see <code><a href="first_isolate.html">first_isolate()</a></code>). Using a phenotype-based method to determine first isolates is more reliable than methods that disregard phenotypes.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">key_antimicrobials</span><span class="op">(</span></span>
-<span> x <span class="op">=</span> <span class="cn">NULL</span>,</span>
-<span> col_mo <span class="op">=</span> <span class="cn">NULL</span>,</span>
-<span> universal <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"amoxicillin/clavulanic acid"</span>, <span class="st">"cefuroxime"</span>,</span>
-<span> <span class="st">"piperacillin/tazobactam"</span>, <span class="st">"ciprofloxacin"</span>, <span class="st">"trimethoprim/sulfamethoxazole"</span><span class="op">)</span>,</span>
-<span> gram_negative <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"gentamicin"</span>, <span class="st">"tobramycin"</span>, <span class="st">"colistin"</span>, <span class="st">"cefotaxime"</span>, <span class="st">"ceftazidime"</span>,</span>
-<span> <span class="st">"meropenem"</span><span class="op">)</span>,</span>
-<span> gram_positive <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"vancomycin"</span>, <span class="st">"teicoplanin"</span>, <span class="st">"tetracycline"</span>, <span class="st">"erythromycin"</span>,</span>
-<span> <span class="st">"oxacillin"</span>, <span class="st">"rifampin"</span><span class="op">)</span>,</span>
-<span> antifungal <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"anidulafungin"</span>, <span class="st">"caspofungin"</span>, <span class="st">"fluconazole"</span>, <span class="st">"miconazole"</span>, <span class="st">"nystatin"</span>,</span>
-<span> <span class="st">"voriconazole"</span><span class="op">)</span>,</span>
-<span> only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>,</span>
-<span> <span class="va">...</span></span>
-<span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">all_antimicrobials</span><span class="op">(</span>x <span class="op">=</span> <span class="cn">NULL</span>, only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">antimicrobials_equal</span><span class="op">(</span></span>
-<span> <span class="va">y</span>,</span>
-<span> <span class="va">z</span>,</span>
-<span> type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"points"</span>, <span class="st">"keyantimicrobials"</span><span class="op">)</span>,</span>
-<span> ignore_I <span class="op">=</span> <span class="cn">TRUE</span>,</span>
-<span> points_threshold <span class="op">=</span> <span class="fl">2</span>,</span>
-<span> <span class="va">...</span></span>
-<span><span class="op">)</span></span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with antibiotics columns, like <code>AMX</code> or <code>amox</code>. Can be left blank to determine automatically</p></dd>
-
-
-<dt>col_mo</dt>
-<dd><p>column name of the IDs of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>), defaults to the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
-
-
-<dt>universal</dt>
-<dd><p>names of <strong>broad-spectrum</strong> antimicrobial agents, case-insensitive. Set to <code>NULL</code> to ignore. See <em>Details</em> for the default agents.</p></dd>
-
-
-<dt>gram_negative</dt>
-<dd><p>names of antibiotic agents for <strong>Gram-positives</strong>, case-insensitive. Set to <code>NULL</code> to ignore. See <em>Details</em> for the default agents.</p></dd>
-
-
-<dt>gram_positive</dt>
-<dd><p>names of antibiotic agents for <strong>Gram-negatives</strong>, case-insensitive. Set to <code>NULL</code> to ignore. See <em>Details</em> for the default agents.</p></dd>
-
-
-<dt>antifungal</dt>
-<dd><p>names of antifungal agents for <strong>fungi</strong>, case-insensitive. Set to <code>NULL</code> to ignore. See <em>Details</em> for the default agents.</p></dd>
-
-
-<dt>only_rsi_columns</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only columns must be included that were transformed to class <code><rsi></code> (see <code><a href="as.rsi.html">as.rsi()</a></code>) on beforehand (defaults to <code>FALSE</code>)</p></dd>
-
-
-<dt>...</dt>
-<dd><p>ignored, only in place to allow future extensions</p></dd>
-
-
-<dt>y, z</dt>
-<dd><p><a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vectors to compare</p></dd>
-
-
-<dt>type</dt>
-<dd><p>type to determine weighed isolates; can be <code>"keyantimicrobials"</code> or <code>"points"</code>, see <em>Details</em></p></dd>
-
-
-<dt>ignore_I</dt>
-<dd><p><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether antibiotic interpretations with <code>"I"</code> will be ignored when <code>type = "keyantimicrobials"</code>, see <em>Details</em></p></dd>
-
-
-<dt>points_threshold</dt>
-<dd><p>minimum number of points to require before differences in the antibiogram will lead to inclusion of an isolate when <code>type = "points"</code>, see <em>Details</em></p></dd>
-
-</dl></div>
- <div id="details">
- <h2>Details</h2>
- <p>The <code>key_antimicrobials()</code> and <code>all_antimicrobials()</code> functions are context-aware. This means that the <code>x</code> argument can be left blank if used inside a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> call, see <em>Examples</em>.</p>
-<p>The function <code>key_antimicrobials()</code> returns a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector with 12 antimicrobial results for every isolate. The function <code>all_antimicrobials()</code> returns a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector with all antimicrobial results for every isolate. These vectors can then be compared using <code>antimicrobials_equal()</code>, to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (<code>"."</code>) by <code>key_antimicrobials()</code> and ignored by <code>antimicrobials_equal()</code>.</p>
-<p>Please see the <code><a href="first_isolate.html">first_isolate()</a></code> function how these important functions enable the 'phenotype-based' method for determination of first isolates.</p>
-<p>The default antimicrobial agents used for <strong>all rows</strong> (set in <code>universal</code>) are:</p><ul><li><p>Ampicillin</p></li>
-<li><p>Amoxicillin/clavulanic acid</p></li>
-<li><p>Cefuroxime</p></li>
-<li><p>Ciprofloxacin</p></li>
-<li><p>Piperacillin/tazobactam</p></li>
-<li><p>Trimethoprim/sulfamethoxazole</p></li>
-</ul><p>The default antimicrobial agents used for <strong>Gram-negative bacteria</strong> (set in <code>gram_negative</code>) are:</p><ul><li><p>Cefotaxime</p></li>
-<li><p>Ceftazidime</p></li>
-<li><p>Colistin</p></li>
-<li><p>Gentamicin</p></li>
-<li><p>Meropenem</p></li>
-<li><p>Tobramycin</p></li>
-</ul><p>The default antimicrobial agents used for <strong>Gram-positive bacteria</strong> (set in <code>gram_positive</code>) are:</p><ul><li><p>Erythromycin</p></li>
-<li><p>Oxacillin</p></li>
-<li><p>Rifampin</p></li>
-<li><p>Teicoplanin</p></li>
-<li><p>Tetracycline</p></li>
-<li><p>Vancomycin</p></li>
-</ul><p>The default antimicrobial agents used for <strong>fungi</strong> (set in <code>antifungal</code>) are:</p><ul><li><p>Anidulafungin</p></li>
-<li><p>Caspofungin</p></li>
-<li><p>Fluconazole</p></li>
-<li><p>Miconazole</p></li>
-<li><p>Nystatin</p></li>
-<li><p>Voriconazole</p></li>
-</ul></div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
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- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="first_isolate.html">first_isolate()</a></code></p></div>
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- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># `example_isolates` is a data set available in the AMR package.</span></span>
-<span><span class="co"># See ?example_isolates.</span></span>
-<span></span>
-<span><span class="co"># output of the `key_antimicrobials()` function could be like this:</span></span>
-<span><span class="va">strainA</span> <span class="op"><-</span> <span class="st">"SSSRR.S.R..S"</span></span>
-<span><span class="va">strainB</span> <span class="op"><-</span> <span class="st">"SSSIRSSSRSSS"</span></span>
-<span></span>
-<span><span class="co"># those strings can be compared with:</span></span>
-<span><span class="fu">antimicrobials_equal</span><span class="op">(</span><span class="va">strainA</span>, <span class="va">strainB</span>, type <span class="op">=</span> <span class="st">"keyantimicrobials"</span><span class="op">)</span></span>
-<span><span class="co"># TRUE, because I is ignored (as well as missing values)</span></span>
-<span></span>
-<span><span class="fu">antimicrobials_equal</span><span class="op">(</span><span class="va">strainA</span>, <span class="va">strainB</span>, type <span class="op">=</span> <span class="st">"keyantimicrobials"</span>, ignore_I <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
-<span><span class="co"># FALSE, because I is not ignored and so the 4th [character] differs</span></span>
-<span></span>
-<span><span class="co"># \donttest{</span></span>
-<span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span>
-<span> <span class="co"># set key antibiotics to a new variable</span></span>
-<span> <span class="va">my_patients</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>keyab <span class="op">=</span> <span class="fu">key_antimicrobials</span><span class="op">(</span>antifungal <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># no need to define `x`</span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span></span>
-<span> <span class="co"># now calculate first isolates</span></span>
-<span> first_regular <span class="op">=</span> <span class="fu"><a href="first_isolate.html">first_isolate</a></span><span class="op">(</span>col_keyantimicrobials <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span>
-<span> <span class="co"># and first WEIGHTED isolates</span></span>
-<span> first_weighted <span class="op">=</span> <span class="fu"><a href="first_isolate.html">first_isolate</a></span><span class="op">(</span>col_keyantimicrobials <span class="op">=</span> <span class="st">"keyab"</span><span class="op">)</span></span>
-<span> <span class="op">)</span></span>
-<span> </span>
-<span> <span class="co"># Check the difference, in this data set it results in more isolates:</span></span>
-<span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="va">my_patients</span><span class="op">$</span><span class="va">first_regular</span>, na.rm <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
-<span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="va">my_patients</span><span class="op">$</span><span class="va">first_weighted</span>, na.rm <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
-<span><span class="op">}</span></span>
-<span><span class="co"># }</span></span></code></pre></div>
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- <h1>Kurtosis of the Sample</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/kurtosis.R" class="external-link"><code>R/kurtosis.R</code></a></small>
- <div class="hidden name"><code>kurtosis.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. A normal distribution has a kurtosis of 3 and a excess kurtosis of 0.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">kurtosis</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span>, excess <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="co"># S3 method for default</span>
-<span class="fu">kurtosis</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span>, excess <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="co"># S3 method for matrix</span>
-<span class="fu">kurtosis</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span>, excess <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="co"># S3 method for data.frame</span>
-<span class="fu">kurtosis</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span>, excess <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a vector of values, a <a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a> or a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p></dd>
-<dt>na.rm</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether <code>NA</code> values should be stripped before the computation proceeds</p></dd>
-<dt>excess</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the <em>excess kurtosis</em> should be returned, defined as the kurtosis minus 3.</p></dd>
-</dl></div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
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- <h2>Read more on Our Website!</h2>
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- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="skewness.html">skewness()</a></code></p></div>
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- <h1>Lifecycles of Functions in the <code>AMR</code> Package</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/lifecycle.R" class="external-link"><code>R/lifecycle.R</code></a></small>
- <div class="hidden name"><code>lifecycle.Rd</code></div>
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- <p>Functions in this <code>AMR</code> package are categorised using <a href="https://lifecycle.r-lib.org/articles/stages.html" class="external-link">the lifecycle circle of the Tidyverse as found on www.tidyverse.org/lifecycle</a>.</p>
-<p><img src="figures/lifecycle_tidyverse.svg" height="200" style='margin-bottom:"5"'><br>
-This page contains a section for every lifecycle (with text borrowed from the aforementioned Tidyverse website), so they can be used in the manual pages of the functions.</p>
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- <div id="experimental-lifecycle">
- <h2>Experimental Lifecycle</h2>
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-<p><img src="figures/lifecycle_experimental.svg" style='margin-bottom:"5"'><br>
-The lifecycle of this function is <strong>experimental</strong>. An experimental function is in early stages of development. The unlying code might be changing frequently. Experimental functions might be removed without deprecation, so you are generally best off waiting until a function is more mature before you use it in production code. Experimental functions are only available in development versions of this <code>AMR</code> package and will thus not be included in releases that are submitted to CRAN, since such functions have not yet matured enough.</p>
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- <h2>Maturing Lifecycle</h2>
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-The lifecycle of this function is <strong>maturing</strong>. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome <a href="https://github.com/msberends/AMR/issues" class="external-link">to suggest changes at our repository</a> or <a href="AMR.html">write us an email (see section 'Contact Us')</a>.</p>
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- <h2>Stable Lifecycle</h2>
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-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The lifecycle of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
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-The lifecycle of this function is <strong>retired</strong>. A retired function is no longer under active development, and (if appropiate) a better alternative is available. No new arguments will be added, and only the most critical bugs will be fixed. In a future version, this function will be removed.</p>
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- <h2>Questioning Lifecycle</h2>
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-<p><img src="figures/lifecycle_questioning.svg" style='margin-bottom:"5"'><br>
-The lifecycle of this function is <strong>questioning</strong>. This function might be no longer be optimal approach, or is it questionable whether this function should be in this <code>AMR</code> package at all.</p>
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diff --git a/docs/reference/like.html b/docs/reference/like.html
deleted file mode 100644
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--- a/docs/reference/like.html
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- <h1>Vectorised Pattern Matching with Keyboard Shortcut</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/like.R" class="external-link"><code>R/like.R</code></a></small>
- <div class="hidden name"><code>like.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Convenient wrapper around <code><a href="https://rdrr.io/r/base/grep.html" class="external-link">grepl()</a></code> to match a pattern: <code>x %like% pattern</code>. It always returns a <code><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a></code> vector and is always case-insensitive (use <code>x %like_case% pattern</code> for case-sensitive matching). Also, <code>pattern</code> can be as long as <code>x</code> to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">like</span><span class="op">(</span><span class="va">x</span>, <span class="va">pattern</span>, ignore.case <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>
-
-<span class="va">x</span> <span class="op">%like%</span> <span class="va">pattern</span>
-
-<span class="va">x</span> <span class="op">%unlike%</span> <span class="va">pattern</span>
-
-<span class="va">x</span> <span class="op">%like_case%</span> <span class="va">pattern</span>
-
-<span class="va">x</span> <span class="op">%unlike_case%</span> <span class="va">pattern</span></code></pre></div>
- </div>
-
- <div id="source">
- <h2>Source</h2>
- <p>Idea from the <a href="https://github.com/Rdatatable/data.table/blob/ec1259af1bf13fc0c96a1d3f9e84d55d8106a9a4/R/like.R" class="external-link"><code>like</code> function from the <code>data.table</code> package</a>, although altered as explained in <em>Details</em>.</p>
- </div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector where matches are sought, or an object which can be coerced by <code><a href="https://rdrr.io/r/base/character.html" class="external-link">as.character()</a></code> to a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector.</p></dd>
-<dt>pattern</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector containing regular expressions (or a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> string for <code>fixed = TRUE</code>) to be matched in the given <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector. Coerced by <code><a href="https://rdrr.io/r/base/character.html" class="external-link">as.character()</a></code> to a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> string if possible.</p></dd>
-<dt>ignore.case</dt>
-<dd><p>if <code>FALSE</code>, the pattern matching is <em>case sensitive</em> and if <code>TRUE</code>, case is ignored during matching.</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>These <code>like()</code> and <code>%like%</code>/<code>%unlike%</code> functions:</p><ul><li><p>Are case-insensitive (use <code>%like_case%</code>/<code>%unlike_case%</code> for case-sensitive matching)</p></li>
-<li><p>Support multiple patterns</p></li>
-<li><p>Check if <code>pattern</code> is a valid regular expression and sets <code>fixed = TRUE</code> if not, to greatly improve speed (vectorised over <code>pattern</code>)</p></li>
-<li><p>Always use compatibility with Perl unless <code>fixed = TRUE</code>, to greatly improve speed</p></li>
-</ul><p>Using RStudio? The <code>%like%</code>/<code>%unlike%</code> functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like <code>Shift+Ctrl+L</code> or <code>Shift+Cmd+L</code> (see menu <code>Tools</code> > <code>Modify Keyboard Shortcuts...</code>). If you keep pressing your shortcut, the inserted text will be iterated over <code>%like%</code> -> <code>%unlike%</code> -> <code>%like_case%</code> -> <code>%unlike_case%</code>.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="https://rdrr.io/r/base/grep.html" class="external-link">grepl()</a></code></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">a</span> <span class="op"><-</span> <span class="st">"This is a test"</span>
-<span class="va">b</span> <span class="op"><-</span> <span class="st">"TEST"</span>
-<span class="va">a</span> <span class="op">%like%</span> <span class="va">b</span>
-<span class="co">#> TRUE</span>
-<span class="va">b</span> <span class="op">%like%</span> <span class="va">a</span>
-<span class="co">#> FALSE</span>
-
-<span class="co"># also supports multiple patterns</span>
-<span class="va">a</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Test case"</span>, <span class="st">"Something different"</span>, <span class="st">"Yet another thing"</span><span class="op">)</span>
-<span class="va">b</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span> <span class="st">"case"</span>, <span class="st">"diff"</span>, <span class="st">"yet"</span><span class="op">)</span>
-<span class="va">a</span> <span class="op">%like%</span> <span class="va">b</span>
-<span class="co">#> TRUE TRUE TRUE</span>
-<span class="va">a</span> <span class="op">%unlike%</span> <span class="va">b</span>
-<span class="co">#> FALSE FALSE FALSE</span>
-
-<span class="va">a</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span> <span class="op">%like%</span> <span class="va">b</span>
-<span class="co">#> TRUE FALSE FALSE</span>
-<span class="va">a</span> <span class="op">%like%</span> <span class="va">b</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span>
-<span class="co">#> TRUE FALSE FALSE</span>
-
-<span class="co"># get isolates whose name start with 'Ent' or 'ent'</span>
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">mo</span><span class="op">)</span> <span class="op">%like%</span> <span class="st">"^ent"</span><span class="op">)</span>, <span class="op">]</span>
-<span class="co"># \donttest{</span>
-<span class="co"># faster way, since mo_name() is context-aware:</span>
-<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="op">)</span> <span class="op">%like%</span> <span class="st">"^ent"</span><span class="op">)</span>, <span class="op">]</span>
-
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="op">)</span> <span class="op">%like%</span> <span class="st">"^ent"</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
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- <h1>Determine Multidrug-Resistant Organisms (MDRO)</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mdro.R" class="external-link"><code>R/mdro.R</code></a></small>
- <div class="hidden name"><code>mdro.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Determine which isolates are multidrug-resistant organisms (MDRO) according to international, national and custom guidelines.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">mdro</span><span class="op">(</span>
- x <span class="op">=</span> <span class="cn">NULL</span>,
- guideline <span class="op">=</span> <span class="st">"CMI2012"</span>,
- col_mo <span class="op">=</span> <span class="cn">NULL</span>,
- info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>,
- pct_required_classes <span class="op">=</span> <span class="fl">0.5</span>,
- combine_SI <span class="op">=</span> <span class="cn">TRUE</span>,
- verbose <span class="op">=</span> <span class="cn">FALSE</span>,
- only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="fu">custom_mdro_guideline</span><span class="op">(</span><span class="va">...</span>, as_factor <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>
-
-<span class="fu">brmo</span><span class="op">(</span>x <span class="op">=</span> <span class="cn">NULL</span>, only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">mrgn</span><span class="op">(</span>x <span class="op">=</span> <span class="cn">NULL</span>, only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">mdr_tb</span><span class="op">(</span>x <span class="op">=</span> <span class="cn">NULL</span>, only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">mdr_cmi2012</span><span class="op">(</span>x <span class="op">=</span> <span class="cn">NULL</span>, only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">eucast_exceptional_phenotypes</span><span class="op">(</span>x <span class="op">=</span> <span class="cn">NULL</span>, only_rsi_columns <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="source">
- <h2>Source</h2>
- <p>See the supported guidelines above for the <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a> of publications used for this function.</p>
- </div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with antibiotics columns, like <code>AMX</code> or <code>amox</code>. Can be left blank for automatic determination.</p></dd>
-<dt>guideline</dt>
-<dd><p>a specific guideline to follow, see sections <em>Supported international / national guidelines</em> and <em>Using Custom Guidelines</em> below. When left empty, the publication by Magiorakos <em>et al.</em> (see below) will be followed.</p></dd>
-<dt>col_mo</dt>
-<dd><p>column name of the IDs of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>), defaults to the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
-<dt>info</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether progress should be printed to the console, defaults to only print while in interactive sessions</p></dd>
-<dt>pct_required_classes</dt>
-<dd><p>minimal required percentage of antimicrobial classes that must be available per isolate, rounded down. For example, with the default guideline, 17 antimicrobial classes must be available for <em>S. aureus</em>. Setting this <code>pct_required_classes</code> argument to <code>0.5</code> (default) means that for every <em>S. aureus</em> isolate at least 8 different classes must be available. Any lower number of available classes will return <code>NA</code> for that isolate.</p></dd>
-<dt>combine_SI</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so resistance is only considered when isolates are R, not I. As this is the default behaviour of the <code>mdro()</code> function, it follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. When using <code>combine_SI = FALSE</code>, resistance is considered when isolates are R or I.</p></dd>
-<dt>verbose</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to turn Verbose mode on and off (default is off). In Verbose mode, the function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.</p></dd>
-<dt>only_rsi_columns</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only antibiotic columns must be detected that were transformed to class <code><rsi></code> (see <code><a href="as.rsi.html">as.rsi()</a></code>) on beforehand (defaults to <code>FALSE</code>)</p></dd>
-<dt>...</dt>
-<dd><p>in case of <code>custom_mdro_guideline()</code>: a set of rules, see section <em>Using Custom Guidelines</em> below. Otherwise: column name of an antibiotic, see section <em>Antibiotics</em> below.</p></dd>
-<dt>as_factor</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the returned value should be an ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> (<code>TRUE</code>, default), or otherwise a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <ul><li><p>CMI 2012 paper - function <code>mdr_cmi2012()</code> or <code>mdro()</code>:<br>
-Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with levels <code>Negative</code> < <code>Multi-drug-resistant (MDR)</code> < <code>Extensively drug-resistant (XDR)</code> < <code>Pandrug-resistant (PDR)</code></p></li>
-<li><p>TB guideline - function <code>mdr_tb()</code> or <code>mdro(..., guideline = "TB")</code>:<br>
-Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with levels <code>Negative</code> < <code>Mono-resistant</code> < <code>Poly-resistant</code> < <code>Multi-drug-resistant</code> < <code>Extensively drug-resistant</code></p></li>
-<li><p>German guideline - function <code>mrgn()</code> or <code>mdro(..., guideline = "MRGN")</code>:<br>
-Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with levels <code>Negative</code> < <code>3MRGN</code> < <code>4MRGN</code></p></li>
-<li><p>Everything else, except for custom guidelines:<br>
-Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with levels <code>Negative</code> < <code>Positive, unconfirmed</code> < <code>Positive</code>. The value <code>"Positive, unconfirmed"</code> means that, according to the guideline, it is not entirely sure if the isolate is multi-drug resistant and this should be confirmed with additional (e.g. molecular) tests</p></li>
-</ul></div>
- <div id="details">
- <h2>Details</h2>
- <p>These functions are context-aware. This means that the <code>x</code> argument can be left blank if used inside a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> call, see <em>Examples</em>.</p>
-<p>For the <code>pct_required_classes</code> argument, values above 1 will be divided by 100. This is to support both fractions (<code>0.75</code> or <code>3/4</code>) and percentages (<code>75</code>).</p>
-<p><strong>Note:</strong> Every test that involves the Enterobacteriaceae family, will internally be performed using its newly named <em>order</em> Enterobacterales, since the Enterobacteriaceae family has been taxonomically reclassified by Adeolu <em>et al.</em> in 2016. Before that, Enterobacteriaceae was the only family under the Enterobacteriales (with an i) order. All species under the old Enterobacteriaceae family are still under the new Enterobacterales (without an i) order, but divided into multiple families. The way tests are performed now by this <code>mdro()</code> function makes sure that results from before 2016 and after 2016 are identical.</p>
- </div>
- <div id="supported-international-national-guidelines">
- <h2>Supported International / National Guidelines</h2>
-
-
-
-<p>Currently supported guidelines are (case-insensitive):</p><ul><li><p><code>guideline = "CMI2012"</code> (default)</p>
-<p>Magiorakos AP, Srinivasan A <em>et al.</em> "Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance." Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext" class="external-link">link</a>)</p></li>
-<li><p><code>guideline = "EUCAST3.3"</code> (or simply <code>guideline = "EUCAST"</code>)</p>
-<p>The European international guideline - EUCAST Expert Rules Version 3.3 "Intrinsic Resistance and Unusual Phenotypes" (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2021/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.3_20211018.pdf" class="external-link">link</a>)</p></li>
-<li><p><code>guideline = "EUCAST3.2"</code></p>
-<p>The European international guideline - EUCAST Expert Rules Version 3.2 "Intrinsic Resistance and Unusual Phenotypes" (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf" class="external-link">link</a>)</p></li>
-<li><p><code>guideline = "EUCAST3.1"</code></p>
-<p>The European international guideline - EUCAST Expert Rules Version 3.1 "Intrinsic Resistance and Exceptional Phenotypes Tables" (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf" class="external-link">link</a>)</p></li>
-<li><p><code>guideline = "TB"</code></p>
-<p>The international guideline for multi-drug resistant tuberculosis - World Health Organization "Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis" (<a href="https://www.who.int/publications/i/item/9789241548809" class="external-link">link</a>)</p></li>
-<li><p><code>guideline = "MRGN"</code></p>
-<p>The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7; <a href="https://doi.org/10.1186/s13756-015-0047-6" class="external-link">doi:10.1186/s13756-015-0047-6</a></p></li>
-<li><p><code>guideline = "BRMO"</code></p>
-<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)" (<a href="https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh" class="external-link">link</a>)</p></li>
-</ul><p>Please suggest your own (country-specific) guidelines by letting us know: <a href="https://github.com/msberends/AMR/issues/new" class="external-link">https://github.com/msberends/AMR/issues/new</a>.</p>
- </div>
- <div id="using-custom-guidelines">
- <h2>Using Custom Guidelines</h2>
-
-
-
-<p>Custom guidelines can be set with the <code>custom_mdro_guideline()</code> function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.</p>
-<p>If you are familiar with the <code><a href="https://dplyr.tidyverse.org/reference/case_when.html" class="external-link">case_when()</a></code> function of the <code>dplyr</code> package, you will recognise the input method to set your own rules. Rules must be set using what <span style="R">R</span> considers to be the 'formula notation'. The rule is written <em>before</em> the tilde (<code>~</code>) and the consequence of the rule is written <em>after</em> the tilde:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>If a row/an isolate matches the first rule, the value after the first <code>~</code> (in this case <em>'Elderly Type A'</em>) will be set as MDRO value. Otherwise, the second rule will be tried and so on. The number of rules is unlimited.</p>
-<p>You can print the rules set in the console for an overview. Colours will help reading it if your console supports colours.</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>The outcome of the function can be used for the <code>guideline</code> argument in the <code>mdro()</code> function:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>Rules can also be combined with other custom rules by using <code><a href="https://rdrr.io/r/base/c.html" class="external-link">c()</a></code>:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>The rules set (the <code>custom</code> object in this case) could be exported to a shared file location using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">saveRDS()</a></code> if you collaborate with multiple users. The custom rules set could then be imported using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">readRDS()</a></code>.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="antibiotics">
- <h2>Antibiotics</h2>
-
-
-<p>To define antibiotics column names, leave as it is to determine it automatically with <code><a href="guess_ab_col.html">guess_ab_col()</a></code> or input a text (case-insensitive), or use <code>NULL</code> to skip a column (e.g. <code>TIC = NULL</code> to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.</p>
-<p>The following antibiotics are eligible for the functions <code><a href="eucast_rules.html">eucast_rules()</a></code> and <code>mdro()</code>. These are shown below in the format 'name (<code>antimicrobial ID</code>, <a href="https://www.whocc.no/atc/structure_and_principles/" class="external-link">ATC code</a>)', sorted alphabetically:</p>
-<p>Amikacin (<code>AMK</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB06&showdescription=no" class="external-link">S01AE08</a>), amoxicillin (<code>AMX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA04&showdescription=no" class="external-link">J01MA02</a>), amoxicillin/clavulanic acid (<code>AMC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR02&showdescription=no" class="external-link">J01MA23</a>), ampicillin (<code>AMP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA01&showdescription=no" class="external-link">J01MA04</a>), ampicillin/sulbactam (<code>SAM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR01&showdescription=no" class="external-link">J01MA08</a>), arbekacin (<code>ARB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB12&showdescription=no" class="external-link">J01MA19</a>), aspoxicillin (<code>APX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA19&showdescription=no" class="external-link">J01MA16</a>), azidocillin (<code>AZD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE04&showdescription=no" class="external-link">J01MA15</a>), azithromycin (<code>AZM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA10&showdescription=no" class="external-link">J01MA11</a>), azlocillin (<code>AZL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA09&showdescription=no" class="external-link">J01MA12</a>), aztreonam (<code>ATM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DF01&showdescription=no" class="external-link">J01MA24</a>), bacampicillin (<code>BAM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA06&showdescription=no" class="external-link">J01MA07</a>), bekanamycin (<code>BEK</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB13&showdescription=no" class="external-link">J01MA14</a>), benzathine benzylpenicillin (<code>BNB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE08&showdescription=no" class="external-link">D10AF05</a>), benzathine phenoxymethylpenicillin (<code>BNP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE10&showdescription=no" class="external-link">J01MA06</a>), benzylpenicillin (<code>PEN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE01&showdescription=no" class="external-link">J01MA01</a>), besifloxacin (<code>BES</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=S01AE08&showdescription=no" class="external-link">J01MA18</a>), biapenem (<code>BIA</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH05&showdescription=no" class="external-link">J01MA03</a>), carbenicillin (<code>CRB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA03&showdescription=no" class="external-link">J01MA17</a>), carindacillin (<code>CRN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA05&showdescription=no" class="external-link">J01MA10</a>), cefacetrile (<code>CAC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB10&showdescription=no" class="external-link">J01MA21</a>), cefaclor (<code>CEC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC04&showdescription=no" class="external-link">J01MA09</a>), cefadroxil (<code>CFR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB05&showdescription=no" class="external-link">J01MA05</a>), cefaloridine (<code>RID</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB02&showdescription=no" class="external-link">P01AA05</a>), cefamandole (<code>MAN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC03&showdescription=no" class="external-link">J01MA22</a>), cefatrizine (<code>CTZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB07&showdescription=no" class="external-link">J01MA13</a>), cefazedone (<code>CZD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB06&showdescription=no" class="external-link">J01CA01</a>), cefazolin (<code>CZO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB04&showdescription=no" class="external-link">J01CA04</a>), cefcapene (<code>CCP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD17&showdescription=no" class="external-link">J01CA12</a>), cefdinir (<code>CDR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD15&showdescription=no" class="external-link">J01CR05</a>), cefditoren (<code>DIT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD16&showdescription=no" class="external-link">J01CA13</a>), cefepime (<code>FEP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DE01&showdescription=no" class="external-link">J01AA02</a>), cefetamet (<code>CAT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD10&showdescription=no" class="external-link">J01FA10</a>), cefixime (<code>CFM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD08&showdescription=no" class="external-link">J01FA09</a>), cefmenoxime (<code>CMX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD05&showdescription=no" class="external-link">J01CR02</a>), cefmetazole (<code>CMZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC09&showdescription=no" class="external-link">J01AA08</a>), cefodizime (<code>DIZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD09&showdescription=no" class="external-link">J01FA06</a>), cefonicid (<code>CID</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC06&showdescription=no" class="external-link">J01CF04</a>), cefoperazone (<code>CFP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD12&showdescription=no" class="external-link">J01CF05</a>), cefoperazone/sulbactam (<code>CSL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD62&showdescription=no" class="external-link">J01CR01</a>), ceforanide (<code>CND</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC11&showdescription=no" class="external-link">J01CA19</a>), cefotaxime (<code>CTX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD01&showdescription=no" class="external-link">J01CE04</a>), cefotetan (<code>CTT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC05&showdescription=no" class="external-link">J01CA09</a>), cefotiam (<code>CTF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC07&showdescription=no" class="external-link">J01DF01</a>), cefoxitin (<code>FOX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC01&showdescription=no" class="external-link">J01CA06</a>), cefozopran (<code>ZOP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DE03&showdescription=no" class="external-link">J01CE08</a>), cefpiramide (<code>CPM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD11&showdescription=no" class="external-link">J01CE10</a>), cefpirome (<code>CPO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DE02&showdescription=no" class="external-link">J01CE01</a>), cefpodoxime (<code>CPD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD13&showdescription=no" class="external-link">J01CA03</a>), cefprozil (<code>CPR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC10&showdescription=no" class="external-link">J01CA05</a>), cefroxadine (<code>CRD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB11&showdescription=no" class="external-link">J01CE07</a>), cefsulodin (<code>CFS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD03&showdescription=no" class="external-link">J01CF02</a>), ceftaroline (<code>CPT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DI02&showdescription=no" class="external-link">J01CF01</a>), ceftazidime (<code>CAZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD02&showdescription=no" class="external-link">J01CA07</a>), ceftazidime/clavulanic acid (<code>CCV</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD52&showdescription=no" class="external-link">J01CA18</a>), cefteram (<code>CEM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD18&showdescription=no" class="external-link">J01CA11</a>), ceftezole (<code>CTL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB12&showdescription=no" class="external-link">J01CA14</a>), ceftibuten (<code>CTB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD14&showdescription=no" class="external-link">J01CF03</a>), ceftizoxime (<code>CZX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD07&showdescription=no" class="external-link">J01CA10</a>), ceftobiprole medocaril (<code>CFM1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DI01&showdescription=no" class="external-link">J01CF06</a>), ceftolozane/enzyme inhibitor (<code>CEI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DI54&showdescription=no" class="external-link">J01CE06</a>), ceftriaxone (<code>CRO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD04&showdescription=no" class="external-link">J01CE05</a>), cefuroxime (<code>CXM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC02&showdescription=no" class="external-link">J01CE02</a>), cephalexin (<code>LEX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB01&showdescription=no" class="external-link">J01CA02</a>), cephalothin (<code>CEP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB03&showdescription=no" class="external-link">J01CA08</a>), cephapirin (<code>HAP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB08&showdescription=no" class="external-link">J01CE09</a>), cephradine (<code>CED</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DB09&showdescription=no" class="external-link">J01CE03</a>), chloramphenicol (<code>CHL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01BA01&showdescription=no" class="external-link">J01CG01</a>), ciprofloxacin (<code>CIP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA02&showdescription=no" class="external-link">J01CA16</a>), clarithromycin (<code>CLR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA09&showdescription=no" class="external-link">J01CR04</a>), clindamycin (<code>CLI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FF01&showdescription=no" class="external-link">J01CA15</a>), clometocillin (<code>CLM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE07&showdescription=no" class="external-link">J01CG02</a>), cloxacillin (<code>CLO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF02&showdescription=no" class="external-link">J01CA17</a>), colistin (<code>COL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XB01&showdescription=no" class="external-link">J01CR03</a>), cycloserine (<code>CYC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J04AB01&showdescription=no" class="external-link">J01DB10</a>), dalbavancin (<code>DAL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA04&showdescription=no" class="external-link">J01DC04</a>), daptomycin (<code>DAP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XX09&showdescription=no" class="external-link">J01DB05</a>), delafloxacin (<code>DFX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA23&showdescription=no" class="external-link">J01DB02</a>), dibekacin (<code>DKB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB09&showdescription=no" class="external-link">J01DC03</a>), dicloxacillin (<code>DIC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF01&showdescription=no" class="external-link">J01DB07</a>), dirithromycin (<code>DIR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA13&showdescription=no" class="external-link">J01DB06</a>), doripenem (<code>DOR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH04&showdescription=no" class="external-link">J01DB04</a>), doxycycline (<code>DOX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01AA02&showdescription=no" class="external-link">J01DD17</a>), enoxacin (<code>ENX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA04&showdescription=no" class="external-link">J01DD15</a>), epicillin (<code>EPC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA07&showdescription=no" class="external-link">J01DD16</a>), ertapenem (<code>ETP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH03&showdescription=no" class="external-link">J01DE01</a>), erythromycin (<code>ERY</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA01&showdescription=no" class="external-link">J01DD10</a>), fleroxacin (<code>FLE</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA08&showdescription=no" class="external-link">J01DD08</a>), flucloxacillin (<code>FLC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF05&showdescription=no" class="external-link">J01DD05</a>), flurithromycin (<code>FLR1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA14&showdescription=no" class="external-link">J01DC09</a>), fosfomycin (<code>FOS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XX01&showdescription=no" class="external-link">J01DD09</a>), framycetin (<code>FRM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=D09AA01&showdescription=no" class="external-link">J01DC06</a>), fusidic acid (<code>FUS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XC01&showdescription=no" class="external-link">J01DD12</a>), garenoxacin (<code>GRN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA19&showdescription=no" class="external-link">J01DD62</a>), gatifloxacin (<code>GAT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA16&showdescription=no" class="external-link">J01DC11</a>), gemifloxacin (<code>GEM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA15&showdescription=no" class="external-link">J01DD01</a>), gentamicin (<code>GEN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB03&showdescription=no" class="external-link">J01DC05</a>), grepafloxacin (<code>GRX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA11&showdescription=no" class="external-link">J01DC07</a>), hetacillin (<code>HET</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA18&showdescription=no" class="external-link">J01DC01</a>), imipenem (<code>IPM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH51&showdescription=no" class="external-link">J01DE03</a>), isepamicin (<code>ISE</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB11&showdescription=no" class="external-link">J01DD11</a>), josamycin (<code>JOS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA07&showdescription=no" class="external-link">J01DE02</a>), kanamycin (<code>KAN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB04&showdescription=no" class="external-link">J01DD13</a>), latamoxef (<code>LTM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DD06&showdescription=no" class="external-link">J01DC10</a>), levofloxacin (<code>LVX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA12&showdescription=no" class="external-link">J01DB11</a>), levonadifloxacin (<code>LND</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA24&showdescription=no" class="external-link">J01DD03</a>), lincomycin (<code>LIN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FF02&showdescription=no" class="external-link">J01DI02</a>), linezolid (<code>LNZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XX08&showdescription=no" class="external-link">J01DD02</a>), lomefloxacin (<code>LOM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA07&showdescription=no" class="external-link">J01DD52</a>), loracarbef (<code>LOR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DC08&showdescription=no" class="external-link">J01DD18</a>), mecillinam (<code>MEC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA11&showdescription=no" class="external-link">J01DB12</a>), meropenem (<code>MEM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH02&showdescription=no" class="external-link">J01DD14</a>), meropenem/vaborbactam (<code>MEV</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01DH52&showdescription=no" class="external-link">J01DD07</a>), metampicillin (<code>MTM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA14&showdescription=no" class="external-link">J01DI01</a>), methicillin (<code>MET</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF03&showdescription=no" class="external-link">J01DI54</a>), mezlocillin (<code>MEZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA10&showdescription=no" class="external-link">J01DD04</a>), micronomicin (<code>MCR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=S01AA22&showdescription=no" class="external-link">J01DC02</a>), midecamycin (<code>MID</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA03&showdescription=no" class="external-link">J01DB01</a>), minocycline (<code>MNO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01AA08&showdescription=no" class="external-link">J01DB03</a>), miocamycin (<code>MCM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA11&showdescription=no" class="external-link">J01DB08</a>), moxifloxacin (<code>MFX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA14&showdescription=no" class="external-link">J01DB09</a>), nadifloxacin (<code>NAD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=D10AF05&showdescription=no" class="external-link">J01DD06</a>), nafcillin (<code>NAF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF06&showdescription=no" class="external-link">J01DC08</a>), nalidixic acid (<code>NAL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MB02&showdescription=no" class="external-link">J01DH05</a>), neomycin (<code>NEO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB05&showdescription=no" class="external-link">J01DH04</a>), netilmicin (<code>NET</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB07&showdescription=no" class="external-link">J01DH03</a>), nitrofurantoin (<code>NIT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XE01&showdescription=no" class="external-link">J01DH51</a>), norfloxacin (<code>NOR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA06&showdescription=no" class="external-link">J01DH02</a>), ofloxacin (<code>OFX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA01&showdescription=no" class="external-link">J01DH52</a>), oleandomycin (<code>OLE</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA05&showdescription=no" class="external-link">J01XA02</a>), oritavancin (<code>ORI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA05&showdescription=no" class="external-link">J01XA01</a>), oxacillin (<code>OXA</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CF04&showdescription=no" class="external-link">J01XC01</a>), pazufloxacin (<code>PAZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA18&showdescription=no" class="external-link">J01FA13</a>), pefloxacin (<code>PEF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA03&showdescription=no" class="external-link">J01FA01</a>), penamecillin (<code>PNM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE06&showdescription=no" class="external-link">J01FA14</a>), phenethicillin (<code>PHE</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE05&showdescription=no" class="external-link">J01FA07</a>), phenoxymethylpenicillin (<code>PHN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE02&showdescription=no" class="external-link">J01FA03</a>), piperacillin (<code>PIP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA12&showdescription=no" class="external-link">J01FA11</a>), piperacillin/tazobactam (<code>TZP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR05&showdescription=no" class="external-link">J01FA05</a>), pivampicillin (<code>PVM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA02&showdescription=no" class="external-link">J01FA12</a>), pivmecillinam (<code>PME</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA08&showdescription=no" class="external-link">J01FA16</a>), plazomicin (<code>PLZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB14&showdescription=no" class="external-link">J01FA02</a>), polymyxin B (<code>PLB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XB02&showdescription=no" class="external-link">J01FA15</a>), pristinamycin (<code>PRI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FG01&showdescription=no" class="external-link">J01FA08</a>), procaine benzylpenicillin (<code>PRB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE09&showdescription=no" class="external-link">J01FF02</a>), propicillin (<code>PRP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE03&showdescription=no" class="external-link">J01FG01</a>), prulifloxacin (<code>PRU</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA17&showdescription=no" class="external-link">J01FG02</a>), quinupristin/dalfopristin (<code>QDA</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FG02&showdescription=no" class="external-link">J04AB02</a>), ribostamycin (<code>RST</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB10&showdescription=no" class="external-link">J01XX09</a>), rifampicin (<code>RIF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J04AB02&showdescription=no" class="external-link">J01XX08</a>), rokitamycin (<code>ROK</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA12&showdescription=no" class="external-link">J01AA07</a>), roxithromycin (<code>RXT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA06&showdescription=no" class="external-link">J01XB01</a>), rufloxacin (<code>RFL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA10&showdescription=no" class="external-link">J01XB02</a>), sisomicin (<code>SIS</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB08&showdescription=no" class="external-link">J01XE01</a>), sitafloxacin (<code>SIT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA21&showdescription=no" class="external-link">J01AA12</a>), solithromycin (<code>SOL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA16&showdescription=no" class="external-link">J01EA01</a>), sparfloxacin (<code>SPX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA09&showdescription=no" class="external-link">J01XX01</a>), spiramycin (<code>SPI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA02&showdescription=no" class="external-link">J01BA01</a>), streptoduocin (<code>STR</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GA02&showdescription=no" class="external-link">J01GB06</a>), streptomycin (<code>STR1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GA01&showdescription=no" class="external-link">J01GB12</a>), sulbactam (<code>SUL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CG01&showdescription=no" class="external-link">J01GB13</a>), sulbenicillin (<code>SBC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA16&showdescription=no" class="external-link">J01GB09</a>), sulfadiazine (<code>SDI</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EC02&showdescription=no" class="external-link">D09AA01</a>), sulfadiazine/trimethoprim (<code>SLT1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE02&showdescription=no" class="external-link">J01GB03</a>), sulfadimethoxine (<code>SUD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED01&showdescription=no" class="external-link">J01GB11</a>), sulfadimidine (<code>SDM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB03&showdescription=no" class="external-link">J01GB04</a>), sulfadimidine/trimethoprim (<code>SLT2</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE05&showdescription=no" class="external-link">S01AA22</a>), sulfafurazole (<code>SLF</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB05&showdescription=no" class="external-link">J01GB05</a>), sulfaisodimidine (<code>SLF1</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB01&showdescription=no" class="external-link">J01GB07</a>), sulfalene (<code>SLF2</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED02&showdescription=no" class="external-link">J01GB14</a>), sulfamazone (<code>SZO</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED09&showdescription=no" class="external-link">J01GB10</a>), sulfamerazine (<code>SLF3</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED07&showdescription=no" class="external-link">J01GB08</a>), sulfamerazine/trimethoprim (<code>SLT3</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE07&showdescription=no" class="external-link">J01GA02</a>), sulfamethizole (<code>SLF4</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB02&showdescription=no" class="external-link">J01GA01</a>), sulfamethoxazole (<code>SMX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EC01&showdescription=no" class="external-link">J01GB01</a>), sulfamethoxypyridazine (<code>SLF5</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED05&showdescription=no" class="external-link">J01EE01</a>), sulfametomidine (<code>SLF6</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED03&showdescription=no" class="external-link">J01MB02</a>), sulfametoxydiazine (<code>SLF7</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED04&showdescription=no" class="external-link">J01FF01</a>), sulfametrole/trimethoprim (<code>SLT4</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE03&showdescription=no" class="external-link">J01XA04</a>), sulfamoxole (<code>SLF8</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EC03&showdescription=no" class="external-link">J01XA05</a>), sulfamoxole/trimethoprim (<code>SLT5</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE04&showdescription=no" class="external-link">J01XA03</a>), sulfanilamide (<code>SLF9</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB06&showdescription=no" class="external-link">J04AB01</a>), sulfaperin (<code>SLF10</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED06&showdescription=no" class="external-link">J01XX11</a>), sulfaphenazole (<code>SLF11</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01ED08&showdescription=no" class="external-link">J01EC02</a>), sulfapyridine (<code>SLF12</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB04&showdescription=no" class="external-link">J01ED01</a>), sulfathiazole (<code>SUT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB07&showdescription=no" class="external-link">J01EB03</a>), sulfathiourea (<code>SLF13</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EB08&showdescription=no" class="external-link">J01EB05</a>), sultamicillin (<code>SLT6</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR04&showdescription=no" class="external-link">J01EB01</a>), talampicillin (<code>TAL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA15&showdescription=no" class="external-link">J01ED02</a>), tazobactam (<code>TAZ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CG02&showdescription=no" class="external-link">J01ED09</a>), tedizolid (<code>TZD</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XX11&showdescription=no" class="external-link">J01ED07</a>), teicoplanin (<code>TEC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA02&showdescription=no" class="external-link">J01EB02</a>), telavancin (<code>TLV</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA03&showdescription=no" class="external-link">J01EC01</a>), telithromycin (<code>TLT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA15&showdescription=no" class="external-link">J01ED05</a>), temafloxacin (<code>TMX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA05&showdescription=no" class="external-link">J01ED03</a>), temocillin (<code>TEM</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA17&showdescription=no" class="external-link">J01ED04</a>), tetracycline (<code>TCY</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01AA07&showdescription=no" class="external-link">J01EC03</a>), ticarcillin (<code>TIC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CA13&showdescription=no" class="external-link">J01EB06</a>), ticarcillin/clavulanic acid (<code>TCC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01CR03&showdescription=no" class="external-link">J01ED06</a>), tigecycline (<code>TGC</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01AA12&showdescription=no" class="external-link">J01ED08</a>), tilbroquinol (<code>TBQ</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=P01AA05&showdescription=no" class="external-link">J01EB04</a>), tobramycin (<code>TOB</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01GB01&showdescription=no" class="external-link">J01EB07</a>), tosufloxacin (<code>TFX</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA22&showdescription=no" class="external-link">J01EB08</a>), trimethoprim (<code>TMP</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EA01&showdescription=no" class="external-link">J01EE02</a>), trimethoprim/sulfamethoxazole (<code>SXT</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01EE01&showdescription=no" class="external-link">J01EE05</a>), troleandomycin (<code>TRL</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01FA08&showdescription=no" class="external-link">J01EE07</a>), trovafloxacin (<code>TVA</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01MA13&showdescription=no" class="external-link">J01EE03</a>), vancomycin (<code>VAN</code>, <a href="https://www.whocc.no/atc_ddd_index/?code=J01XA01&showdescription=no" class="external-link">J01EE04</a>)</p>
- </div>
- <div id="interpretation-of-r-and-s-i">
- <h2>Interpretation of R and S/I</h2>
-
-
-<p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (<a href="https://www.eucast.org/newsiandr/" class="external-link">https://www.eucast.org/newsiandr/</a>).</p><ul><li><p><strong>R = Resistant</strong><br>
-A microorganism is categorised as <em>Resistant</em> when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p></li>
-<li><p><strong>S = Susceptible</strong><br>
-A microorganism is categorised as <em>Susceptible, standard dosing regimen</em>, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
-<li><p><strong>I = Susceptible, Increased exposure</strong><br>
-A microorganism is categorised as <em>Susceptible, Increased exposure</em> when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.</p></li>
-</ul><p>This AMR package honours this (new) insight. Use <code><a href="proportion.html">susceptibility()</a></code> (equal to <code><a href="proportion.html">proportion_SI()</a></code>) to determine antimicrobial susceptibility and <code><a href="count.html">count_susceptible()</a></code> (equal to <code><a href="count.html">count_SI()</a></code>) to count susceptible isolates.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">mdro</span><span class="op">(</span><span class="va">example_isolates</span>, guideline <span class="op">=</span> <span class="st">"EUCAST"</span><span class="op">)</span>
-
-<span class="fu">mdro</span><span class="op">(</span><span class="va">example_isolates</span>,
- guideline <span class="op">=</span> <span class="fu">custom_mdro_guideline</span><span class="op">(</span><span class="va">AMX</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">~</span> <span class="st">"Custom MDRO 1"</span>,
- <span class="va">VAN</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">~</span> <span class="st">"Custom MDRO 2"</span><span class="op">)</span><span class="op">)</span>
-
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">mdro</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://rdrr.io/r/base/table.html" class="external-link">table</a></span><span class="op">(</span><span class="op">)</span>
-
- <span class="co"># no need to define `x` when used inside dplyr verbs:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>MDRO <span class="op">=</span> <span class="fu">mdro</span><span class="op">(</span><span class="op">)</span>,
- EUCAST <span class="op">=</span> <span class="fu">eucast_exceptional_phenotypes</span><span class="op">(</span><span class="op">)</span>,
- BRMO <span class="op">=</span> <span class="fu">brmo</span><span class="op">(</span><span class="op">)</span>,
- MRGN <span class="op">=</span> <span class="fu">mrgn</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/microorganisms.codes.html b/docs/reference/microorganisms.codes.html
deleted file mode 100644
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--- a/docs/reference/microorganisms.codes.html
+++ /dev/null
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-<!DOCTYPE html>
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- <h1>Data Set with 5,604 Common Microorganism Codes</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>microorganisms.codes.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <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>. They will all be searched when using <code><a href="as.mo.html">as.mo()</a></code> and consequently all the <code><a href="mo_property.html">mo_*</a></code> functions.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">microorganisms.codes</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 5,604 observations and 2 variables:</p><ul><li><p><code>code</code><br> Commonly used code of a microorganism</p></li>
-<li><p><code>mo</code><br> ID of the microorganism in the <a href="microorganisms.html">microorganisms</a> data set</p></li>
-</ul></div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="catalogue-of-life">
- <h2>Catalogue of Life</h2>
-
-
-<p><img src="figures/logo_col.png" height="40" style='margin-bottom:"5"'><br>
-This package contains the complete taxonomic tree of almost all microorganisms (~71,000 species) from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a>). The CoL is the most comprehensive and authoritative global index of species currently available. Nonetheless, we supplemented the CoL data with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de" class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/CatalogueOfLife/general" class="external-link">CoL+ project</a> is finished, which we await.</p>
-<p><a href="catalogue_of_life.html">Click here</a> for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with <code><a href="catalogue_of_life_version.html">catalogue_of_life_version()</a></code>.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="as.mo.html">as.mo()</a></code> <a href="microorganisms.html">microorganisms</a></p></div>
- </div>
-
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diff --git a/docs/reference/microorganisms.html b/docs/reference/microorganisms.html
deleted file mode 100644
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--- a/docs/reference/microorganisms.html
+++ /dev/null
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- <h1>Data Set with 70,764 Microorganisms</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>microorganisms.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>A data set containing the full microbial taxonomy (<strong>last updated: 5 October 2021</strong>) of six kingdoms from the Catalogue of Life (CoL) and the List of Prokaryotic names with Standing in Nomenclature (LPSN). MO codes can be looked up using <code><a href="as.mo.html">as.mo()</a></code>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">microorganisms</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 70,764 observations and 16 variables:</p><ul><li><p><code>mo</code><br> ID of microorganism as used by this package</p></li>
-<li><p><code>fullname</code><br> Full name, like <code>"Escherichia coli"</code></p></li>
-<li><p><code>kingdom</code>, <code>phylum</code>, <code>class</code>, <code>order</code>, <code>family</code>, <code>genus</code>, <code>species</code>, <code>subspecies</code><br> Taxonomic rank of the microorganism</p></li>
-<li><p><code>rank</code><br> Text of the taxonomic rank of the microorganism, like <code>"species"</code> or <code>"genus"</code></p></li>
-<li><p><code>ref</code><br> Author(s) and year of concerning scientific publication</p></li>
-<li><p><code>species_id</code><br> ID of the species as used by the Catalogue of Life</p></li>
-<li><p><code>source</code><br> Either "CoL", "LPSN" or "manually added" (see <em>Source</em>)</p></li>
-<li><p><code>prevalence</code><br> Prevalence of the microorganism, see <code><a href="as.mo.html">as.mo()</a></code></p></li>
-<li><p><code>snomed</code><br> Systematized Nomenclature of Medicine (SNOMED) code of the microorganism, according to the US Edition of SNOMED CT from 1 September 2020 (see <em>Source</em>). Use <code><a href="mo_property.html">mo_snomed()</a></code> to retrieve it quickly, see <code><a href="mo_property.html">mo_property()</a></code>.</p></li>
-</ul></div>
- <div id="source">
- <h2>Source</h2>
- <p>Catalogue of Life: 2019 Annual Checklist as currently implemented in this <code>AMR</code> package:</p><ul><li><p>Annual Checklist (public online taxonomic database), <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a></p></li>
-</ul><p>List of Prokaryotic names with Standing in Nomenclature (5 October 2021) as currently implemented in this <code>AMR</code> package:</p><ul><li><p>Parte, A.C., Sarda Carbasse, J., Meier-Kolthoff, J.P., Reimer, L.C. and Goker, M. (2020). List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ. International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; <a href="https://doi.org/10.1099/ijsem.0.004332" class="external-link">doi:10.1099/ijsem.0.004332</a></p></li>
-<li><p>Parte, A.C. (2018). LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; <a href="https://doi.org/10.1099/ijsem.0.002786" class="external-link">doi:10.1099/ijsem.0.002786</a></p></li>
-<li><p>Parte, A.C. (2014). LPSN - List of Prokaryotic names with Standing in Nomenclature. Nucleic Acids Research, 42, Issue D1, D613-D616; <a href="https://doi.org/10.1093/nar/gkt1111" class="external-link">doi:10.1093/nar/gkt1111</a></p></li>
-<li><p>Euzeby, J.P. (1997). List of Bacterial Names with Standing in Nomenclature: a Folder Available on the Internet. International Journal of Systematic Bacteriology, 47, 590-592; <a href="https://doi.org/10.1099/00207713-47-2-590" class="external-link">doi:10.1099/00207713-47-2-590</a></p></li>
-</ul><p>US Edition of SNOMED CT from 1 September 2020 as currently implemented in this <code>AMR</code> package:</p><ul><li><p>Retrieved from the Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS), OID 2.16.840.1.114222.4.11.1009, version 12; url: <a href="https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009" class="external-link">https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009</a></p></li>
-</ul></div>
- <div id="details">
- <h2>Details</h2>
- <p>Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.</p>
-<p>For example, <em>Staphylococcus pettenkoferi</em> was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (<a href="https://doi.org/10.1016/s0732-8893%2802%2900399-1" class="external-link">doi:10.1016/s0732-8893(02)00399-1</a>
-), but it was not before 2007 that a publication in IJSEM followed (<a href="https://doi.org/10.1099/ijs.0.64381-0" class="external-link">doi:10.1099/ijs.0.64381-0</a>
-). Consequently, the <code>AMR</code> package returns 2007 for <code>mo_year("S. pettenkoferi")</code>.</p><div class="section">
-<h3 id="manual-additions">Manual additions<a class="anchor" aria-label="anchor" href="#manual-additions"></a></h3>
-
-
-<p>For convenience, some entries were added manually:</p><ul><li><p>11 entries of <em>Streptococcus</em> (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri)</p></li>
-<li><p>2 entries of <em>Staphylococcus</em> (coagulase-negative (CoNS) and coagulase-positive (CoPS))</p></li>
-<li><p>3 entries of <em>Trichomonas</em> (<em>T. vaginalis</em>, and its family and genus)</p></li>
-<li><p>4 entries of <em>Toxoplasma</em> (<em>T. gondii</em>, and its order, family and genus)</p></li>
-<li><p>1 entry of <em>Candida</em> (<em>C. krusei</em>), that is not (yet) in the Catalogue of Life</p></li>
-<li><p>1 entry of <em>Blastocystis</em> (<em>B. hominis</em>), although it officially does not exist (Noel <em>et al.</em> 2005, PMID 15634993)</p></li>
-<li><p>1 entry of <em>Moraxella</em> (<em>M. catarrhalis</em>), which was formally named <em>Branhamella catarrhalis</em> (Catlin, 1970) though this change was never accepted within the field of clinical microbiology</p></li>
-<li><p>5 other 'undefined' entries (unknown, unknown Gram negatives, unknown Gram positives, unknown yeast and unknown fungus)</p></li>
-<li><p>6 families under the Enterobacterales order, according to Adeolu <em>et al.</em> (2016, PMID 27620848), that are not (yet) in the Catalogue of Life</p></li>
-</ul></div>
-
-<div class="section">
-<h3 id="direct-download">Direct download<a class="anchor" aria-label="anchor" href="#direct-download"></a></h3>
-
-
-<p>This data set is available as 'flat file' for use even without <span style="R">R</span> - you can find the file here: <a href="https://github.com/msberends/AMR/raw/main/data-raw/microorganisms.txt" class="external-link">https://github.com/msberends/AMR/raw/main/data-raw/microorganisms.txt</a>.</p>
-<p>The file in <span style="R">R</span> format (with preserved data structure) can be found here: <a href="https://github.com/msberends/AMR/raw/main/data/microorganisms.rda" class="external-link">https://github.com/msberends/AMR/raw/main/data/microorganisms.rda</a>.</p>
-</div>
-
- </div>
- <div id="about-the-records-from-lpsn-see-source-">
- <h2>About the Records from LPSN (see <em>Source</em>)</h2>
-
-
-<p>The List of Prokaryotic names with Standing in Nomenclature (LPSN) provides comprehensive information on the nomenclature of prokaryotes. LPSN is a free to use service founded by Jean P. Euzeby in 1997 and later on maintained by Aidan C. Parte.</p>
-<p>As of February 2020, the regularly augmented LPSN database at DSMZ is the basis of the new LPSN service. The new database was implemented for the Type-Strain Genome Server and augmented in 2018 to store all kinds of nomenclatural information. Data from the previous version of LPSN and from the Prokaryotic Nomenclature Up-to-date (PNU) service were imported into the new system. PNU had been established in 1993 as a service of the Leibniz Institute DSMZ, and was curated by Norbert Weiss, Manfred Kracht and Dorothea Gleim.</p>
- </div>
- <div id="catalogue-of-life">
- <h2>Catalogue of Life</h2>
-
-
-<p><img src="figures/logo_col.png" height="40" style='margin-bottom:"5"'><br>
-This package contains the complete taxonomic tree of almost all microorganisms (~71,000 species) from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a>). The CoL is the most comprehensive and authoritative global index of species currently available. Nonetheless, we supplemented the CoL data with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de" class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/CatalogueOfLife/general" class="external-link">CoL+ project</a> is finished, which we await.</p>
-<p><a href="catalogue_of_life.html">Click here</a> for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with <code><a href="catalogue_of_life_version.html">catalogue_of_life_version()</a></code>.</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="as.mo.html">as.mo()</a></code>, <code><a href="mo_property.html">mo_property()</a></code>, <a href="microorganisms.codes.html">microorganisms.codes</a>, <a href="intrinsic_resistant.html">intrinsic_resistant</a></p></div>
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- <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p>
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- <h1>Data Set with Previously Accepted Taxonomic Names</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>microorganisms.old.Rd</code></div>
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-
- <div class="ref-description">
- <p>A data set containing old (previously valid or accepted) taxonomic names according to the Catalogue of Life. This data set is used internally by <code><a href="as.mo.html">as.mo()</a></code>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">microorganisms.old</span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 14,338 observations and 4 variables:</p><ul><li><p><code>fullname</code><br> Old full taxonomic name of the microorganism</p></li>
-<li><p><code>fullname_new</code><br> New full taxonomic name of the microorganism</p></li>
-<li><p><code>ref</code><br> Author(s) and year of concerning scientific publication</p></li>
-<li><p><code>prevalence</code><br> Prevalence of the microorganism, see <code><a href="as.mo.html">as.mo()</a></code></p></li>
-</ul></div>
- <div id="source">
- <h2>Source</h2>
- <p>Catalogue of Life: Annual Checklist (public online taxonomic database), <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a> (check included annual version with <code><a href="catalogue_of_life_version.html">catalogue_of_life_version()</a></code>).</p>
-<p>Parte, A.C. (2018). LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; doi: <a href="https://doi.org/10.1099/ijsem.0.002786" class="external-link">10.1099/ijsem.0.002786</a></p>
- </div>
- <div id="catalogue-of-life">
- <h2>Catalogue of Life</h2>
-
-
-<p><img src="figures/logo_col.png" height="40" style='margin-bottom:"5"'><br>
-This package contains the complete taxonomic tree of almost all microorganisms (~71,000 species) from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a>). The CoL is the most comprehensive and authoritative global index of species currently available. Nonetheless, we supplemented the CoL data with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de" class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/CatalogueOfLife/general" class="external-link">CoL+ project</a> is finished, which we await.</p>
-<p><a href="catalogue_of_life.html">Click here</a> for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with <code><a href="catalogue_of_life_version.html">catalogue_of_life_version()</a></code>.</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
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-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
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- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="as.mo.html">as.mo()</a></code> <code><a href="mo_property.html">mo_property()</a></code> <a href="microorganisms.html">microorganisms</a></p></div>
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- <h1>Calculate the Matching Score for Microorganisms</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mo_matching_score.R" class="external-link"><code>R/mo_matching_score.R</code></a></small>
- <div class="hidden name"><code>mo_matching_score.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>This algorithm is used by <code><a href="as.mo.html">as.mo()</a></code> and all the <code><a href="mo_property.html">mo_*</a></code> functions to determine the most probable match of taxonomic records based on user input.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">mo_matching_score</span><span class="op">(</span><span class="va">x</span>, <span class="va">n</span><span class="op">)</span></span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>Any user input value(s)</p></dd>
-
-
-<dt>n</dt>
-<dd><p>A full taxonomic name, that exists in <code><a href="microorganisms.html">microorganisms$fullname</a></code></p></dd>
-
-</dl></div>
- <div id="matching-score-for-microorganisms">
- <h2>Matching Score for Microorganisms</h2>
-
-
-<p>With ambiguous user input in <code><a href="as.mo.html">as.mo()</a></code> and all the <code><a href="mo_property.html">mo_*</a></code> functions, the returned results are chosen based on their matching score using <code>mo_matching_score()</code>. This matching score \(m\), is calculated as:</p>
-<p><img src="figures/mo_matching_score.png" width="300" alt="mo matching score"></p>
-<p>where:</p><ul><li><p><i>x</i> is the user input;</p></li>
-<li><p><i>n</i> is a taxonomic name (genus, species, and subspecies);</p></li>
-<li><p><i>l<sub>n</sub></i> is the length of <i>n</i>;</p></li>
-<li><p><i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance" class="external-link">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;</p></li>
-<li><p><i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;</p></li>
-<li><p><i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
-</ul><p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>, <em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
-<p>All characters in \(x\) and \(n\) are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.</p>
-<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.079\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
-<p>Since <code>AMR</code> version 1.8.1, common microorganism abbreviations are ignored in determining the matching score. These abbreviations are currently: AIEC, ATEC, BORSA, CRSM, DAEC, EAEC, EHEC, EIEC, EPEC, ETEC, GISA, MRPA, MRSA, MRSE, MSSA, MSSE, NMEC, PISP, PRSP, STEC, UPEC, VISA, VISP, VRE, VRSA and VRSP.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="author">
- <h2>Author</h2>
- <p>Dr Matthijs Berends</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span></span>
-<span><span class="fu"><a href="as.mo.html">mo_uncertainties</a></span><span class="op">(</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_matching_score</span><span class="op">(</span>x <span class="op">=</span> <span class="st">"E. coli"</span>,</span>
-<span> n <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Escherichia coli"</span>, <span class="st">"Entamoeba coli"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
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diff --git a/docs/reference/mo_property.html b/docs/reference/mo_property.html
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- <h1>Get Properties of a Microorganism</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mo_property.R" class="external-link"><code>R/mo_property.R</code></a></small>
- <div class="hidden name"><code>mo_property.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Use these functions to return a specific property of a microorganism based on the latest accepted taxonomy. All input values will be evaluated internally with <code><a href="as.mo.html">as.mo()</a></code>, which makes it possible to use microbial abbreviations, codes and names as input. See <em>Examples</em>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">mo_name</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_fullname</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_shortname</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_subspecies</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_species</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_genus</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_family</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_order</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_class</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_phylum</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_kingdom</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_domain</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_type</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_gramstain</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_is_gram_negative</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_is_gram_positive</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_is_yeast</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_is_intrinsic_resistant</span><span class="op">(</span><span class="va">x</span>, <span class="va">ab</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_snomed</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_ref</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_authors</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_year</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_lpsn</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_rank</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_taxonomy</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_synonyms</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_info</span><span class="op">(</span><span class="va">x</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_url</span><span class="op">(</span><span class="va">x</span>, open <span class="op">=</span> <span class="cn">FALSE</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">mo_property</span><span class="op">(</span><span class="va">x</span>, property <span class="op">=</span> <span class="st">"fullname"</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>any <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vector) that can be coerced to a valid microorganism code with <code><a href="as.mo.html">as.mo()</a></code>. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, see <em>Examples</em>.</p></dd>
-
-
-<dt>language</dt>
-<dd><p>language of the returned text, defaults to system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can be overwritten by setting the option <code>AMR_locale</code>, e.g. <code>options(AMR_locale = "de")</code>, see <a href="translate.html">translate</a>. Also used to translate text like "no growth". Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
-
-
-<dt>...</dt>
-<dd><p>other arguments passed on to <code><a href="as.mo.html">as.mo()</a></code>, such as 'allow_uncertain' and 'ignore_pattern'</p></dd>
-
-
-<dt>ab</dt>
-<dd><p>any (vector of) text that can be coerced to a valid antibiotic code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
-
-
-<dt>open</dt>
-<dd><p>browse the URL using <code><a href="https://rdrr.io/r/utils/browseURL.html" class="external-link">browseURL()</a></code></p></dd>
-
-
-<dt>property</dt>
-<dd><p>one of the column names of the <a href="microorganisms.html">microorganisms</a> data set: "mo", "fullname", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "species_id", "source", "prevalence" or "snomed", or must be <code>"shortname"</code></p></dd>
-
-</dl></div>
- <div id="value">
- <h2>Value</h2>
-
-
-<ul><li><p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> in case of <code>mo_year()</code></p></li>
-<li><p>A <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a> in case of <code>mo_taxonomy()</code> and <code>mo_info()</code></p></li>
-<li><p>A named <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> in case of <code>mo_url()</code></p></li>
-<li><p>A <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> in case of <code>mo_snomed()</code></p></li>
-<li><p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> in all other cases</p></li>
-</ul></div>
- <div id="details">
- <h2>Details</h2>
- <p>All functions will return the most recently known taxonomic property according to the Catalogue of Life, except for <code>mo_ref()</code>, <code>mo_authors()</code> and <code>mo_year()</code>. Please refer to this example, knowing that <em>Escherichia blattae</em> was renamed to <em>Shimwellia blattae</em> in 2010:</p><ul><li><p><code>mo_name("Escherichia blattae")</code> will return <code>"Shimwellia blattae"</code> (with a message about the renaming)</p></li>
-<li><p><code>mo_ref("Escherichia blattae")</code> will return <code>"Burgess et al., 1973"</code> (with a message about the renaming)</p></li>
-<li><p><code>mo_ref("Shimwellia blattae")</code> will return <code>"Priest et al., 2010"</code> (without a message)</p></li>
-</ul><p>The short name - <code>mo_shortname()</code> - almost always returns the first character of the genus and the full species, like <code>"E. coli"</code>. Exceptions are abbreviations of staphylococci (such as <em>"CoNS"</em>, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as <em>"GBS"</em>, Group B Streptococci). Please bear in mind that e.g. <em>E. coli</em> could mean <em>Escherichia coli</em> (kingdom of Bacteria) as well as <em>Entamoeba coli</em> (kingdom of Protozoa). Returning to the full name will be done using <code><a href="as.mo.html">as.mo()</a></code> internally, giving priority to bacteria and human pathogens, i.e. <code>"E. coli"</code> will be considered <em>Escherichia coli</em>. In other words, <code>mo_fullname(mo_shortname("Entamoeba coli"))</code> returns <code>"Escherichia coli"</code>.</p>
-<p>Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions <code>mo_kingdom()</code> and <code>mo_domain()</code> return the exact same results.</p>
-<p>The Gram stain - <code>mo_gramstain()</code> - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, <a href="https://pubmed.ncbi.nlm.nih.gov/11837318" class="external-link">PMID 11837318</a>), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive, except for members of the class Negativicutes which are Gram-negative. Members of other bacterial phyla are all considered Gram-negative. Species outside the kingdom of Bacteria will return a value <code>NA</code>. Functions <code>mo_is_gram_negative()</code> and <code>mo_is_gram_positive()</code> always return <code>TRUE</code> or <code>FALSE</code> (except when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>), thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p>
-<p>Determination of yeasts - <code>mo_is_yeast()</code> - will be based on the taxonomic kingdom and class. <em>Budding yeasts</em> are fungi of the phylum Ascomycetes, class Saccharomycetes (also called Hemiascomycetes). <em>True yeasts</em> are aggregated into the underlying order Saccharomycetales. Thus, for all microorganisms that are fungi and member of the taxonomic class Saccharomycetes, the function will return <code>TRUE</code>. It returns <code>FALSE</code> otherwise (except when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>).</p>
-<p>Intrinsic resistance - <code>mo_is_intrinsic_resistant()</code> - will be determined based on the <a href="intrinsic_resistant.html">intrinsic_resistant</a> data set, which is based on <a href="https://www.eucast.org/expert_rules_and_expected_phenotypes/" class="external-link">'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3</a> (2021). The <code>mo_is_intrinsic_resistant()</code> functions can be vectorised over arguments <code>x</code> (input for microorganisms) and over <code>ab</code> (input for antibiotics).</p>
-<p>All output <a href="translate.html">will be translated</a> where possible.</p>
-<p>The function <code>mo_url()</code> will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.</p>
-<p>SNOMED codes - <code>mo_snomed()</code> - are from the US Edition of SNOMED CT from 1 September 2020. See <em>Source</em> and the <a href="microorganisms.html">microorganisms</a> data set for more info.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="matching-score-for-microorganisms">
- <h2>Matching Score for Microorganisms</h2>
-
-
-<p>With ambiguous user input in <code><a href="as.mo.html">as.mo()</a></code> and all the <code>mo_*</code> functions, the returned results are chosen based on their matching score using <code><a href="mo_matching_score.html">mo_matching_score()</a></code>. This matching score \(m\), is calculated as:</p>
-<p><img src="figures/mo_matching_score.png" width="300" alt="mo matching score"></p>
-<p>where:</p><ul><li><p><i>x</i> is the user input;</p></li>
-<li><p><i>n</i> is a taxonomic name (genus, species, and subspecies);</p></li>
-<li><p><i>l<sub>n</sub></i> is the length of <i>n</i>;</p></li>
-<li><p><i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance" class="external-link">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;</p></li>
-<li><p><i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;</p></li>
-<li><p><i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
-</ul><p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>, <em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
-<p>All characters in \(x\) and \(n\) are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.</p>
-<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.079\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
-<p>Since <code>AMR</code> version 1.8.1, common microorganism abbreviations are ignored in determining the matching score. These abbreviations are currently: AIEC, ATEC, BORSA, CRSM, DAEC, EAEC, EHEC, EIEC, EPEC, ETEC, GISA, MRPA, MRSA, MRSE, MSSA, MSSE, NMEC, PISP, PRSP, STEC, UPEC, VISA, VISP, VRE, VRSA and VRSP.</p>
- </div>
- <div id="catalogue-of-life">
- <h2>Catalogue of Life</h2>
-
-
-<p><img src="figures/logo_col.png" height="40" style='margin-bottom:"5"'><br>
-This package contains the complete taxonomic tree of almost all microorganisms (~71,000 species) from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a>). The CoL is the most comprehensive and authoritative global index of species currently available. Nonetheless, we supplemented the CoL data with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de" class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/CatalogueOfLife/general" class="external-link">CoL+ project</a> is finished, which we await.</p>
-<p><a href="catalogue_of_life.html">Click here</a> for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with <code><a href="catalogue_of_life_version.html">catalogue_of_life_version()</a></code>.</p>
- </div>
- <div id="source">
- <h2>Source</h2>
-
-
-<ol><li><p>Becker K <em>et al.</em> <strong>Coagulase-Negative Staphylococci</strong>. 2014. Clin Microbiol Rev. 27(4): 870-926; <a href="https://doi.org/10.1128/CMR.00109-13" class="external-link">doi:10.1128/CMR.00109-13</a></p></li>
-<li><p>Becker K <em>et al.</em> <strong>Implications of identifying the recently defined members of the <em>S. aureus</em> complex, <em>S. argenteus</em> and <em>S. schweitzeri</em>: A position paper of members of the ESCMID Study Group for staphylococci and Staphylococcal Diseases (ESGS).</strong> 2019. Clin Microbiol Infect; <a href="https://doi.org/10.1016/j.cmi.2019.02.028" class="external-link">doi:10.1016/j.cmi.2019.02.028</a></p></li>
-<li><p>Becker K <em>et al.</em> <strong>Emergence of coagulase-negative staphylococci</strong> 2020. Expert Rev Anti Infect Ther. 18(4):349-366; <a href="https://doi.org/10.1080/14787210.2020.1730813" class="external-link">doi:10.1080/14787210.2020.1730813</a></p></li>
-<li><p>Lancefield RC <strong>A serological differentiation of human and other groups of hemolytic streptococci</strong>. 1933. J Exp Med. 57(4): 571-95; <a href="https://doi.org/10.1084/jem.57.4.571" class="external-link">doi:10.1084/jem.57.4.571</a></p></li>
-<li><p>Catalogue of Life: 2019 Annual Checklist, <a href="http://www.catalogueoflife.org" class="external-link">http://www.catalogueoflife.org</a></p></li>
-<li><p>List of Prokaryotic names with Standing in Nomenclature (5 October 2021), <a href="https://doi.org/10.1099/ijsem.0.004332" class="external-link">doi:10.1099/ijsem.0.004332</a></p></li>
-<li><p>US Edition of SNOMED CT from 1 September 2020, retrieved from the Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS), OID 2.16.840.1.114222.4.11.1009, version 12; url: <a href="https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009" class="external-link">https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009</a></p></li>
-</ol></div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p>Data set <a href="microorganisms.html">microorganisms</a></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># taxonomic tree -----------------------------------------------------------</span></span>
-<span><span class="fu">mo_kingdom</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Bacteria"</span></span>
-<span><span class="fu">mo_phylum</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Proteobacteria"</span></span>
-<span><span class="fu">mo_class</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Gammaproteobacteria"</span></span>
-<span><span class="fu">mo_order</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Enterobacterales"</span></span>
-<span><span class="fu">mo_family</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Enterobacteriaceae"</span></span>
-<span><span class="fu">mo_genus</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Escherichia"</span></span>
-<span><span class="fu">mo_species</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "coli"</span></span>
-<span><span class="fu">mo_subspecies</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># ""</span></span>
-<span></span>
-<span><span class="co"># colloquial properties ----------------------------------------------------</span></span>
-<span><span class="fu">mo_name</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Escherichia coli"</span></span>
-<span><span class="fu">mo_fullname</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Escherichia coli" - same as mo_name()</span></span>
-<span><span class="fu">mo_shortname</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "E. coli"</span></span>
-<span></span>
-<span><span class="co"># other properties ---------------------------------------------------------</span></span>
-<span><span class="fu">mo_gramstain</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Gram-negative"</span></span>
-<span><span class="fu">mo_snomed</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># 112283007, 116395006, ... (SNOMED codes)</span></span>
-<span><span class="fu">mo_type</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Bacteria" (equal to kingdom, but may be translated)</span></span>
-<span><span class="fu">mo_rank</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "species"</span></span>
-<span><span class="fu">mo_url</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># get the direct url to the online database entry</span></span>
-<span><span class="fu">mo_synonyms</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># get previously accepted taxonomic names</span></span>
-<span></span>
-<span><span class="co"># scientific reference -----------------------------------------------------</span></span>
-<span><span class="fu">mo_ref</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Castellani et al., 1919"</span></span>
-<span><span class="fu">mo_authors</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Castellani et al."</span></span>
-<span><span class="fu">mo_year</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># 1919</span></span>
-<span><span class="fu">mo_lpsn</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># 776057 (LPSN record ID)</span></span>
-<span></span>
-<span><span class="co"># abbreviations known in the field -----------------------------------------</span></span>
-<span><span class="fu">mo_genus</span><span class="op">(</span><span class="st">"MRSA"</span><span class="op">)</span> <span class="co"># "Staphylococcus"</span></span>
-<span><span class="fu">mo_species</span><span class="op">(</span><span class="st">"MRSA"</span><span class="op">)</span> <span class="co"># "aureus"</span></span>
-<span><span class="fu">mo_shortname</span><span class="op">(</span><span class="st">"VISA"</span><span class="op">)</span> <span class="co"># "S. aureus"</span></span>
-<span><span class="fu">mo_gramstain</span><span class="op">(</span><span class="st">"VISA"</span><span class="op">)</span> <span class="co"># "Gram-positive"</span></span>
-<span></span>
-<span><span class="fu">mo_genus</span><span class="op">(</span><span class="st">"EHEC"</span><span class="op">)</span> <span class="co"># "Escherichia"</span></span>
-<span><span class="fu">mo_species</span><span class="op">(</span><span class="st">"EHEC"</span><span class="op">)</span> <span class="co"># "coli"</span></span>
-<span></span>
-<span><span class="co"># known subspecies ---------------------------------------------------------</span></span>
-<span><span class="fu">mo_name</span><span class="op">(</span><span class="st">"doylei"</span><span class="op">)</span> <span class="co"># "Campylobacter jejuni doylei"</span></span>
-<span><span class="fu">mo_genus</span><span class="op">(</span><span class="st">"doylei"</span><span class="op">)</span> <span class="co"># "Campylobacter"</span></span>
-<span><span class="fu">mo_species</span><span class="op">(</span><span class="st">"doylei"</span><span class="op">)</span> <span class="co"># "jejuni"</span></span>
-<span><span class="fu">mo_subspecies</span><span class="op">(</span><span class="st">"doylei"</span><span class="op">)</span> <span class="co"># "doylei"</span></span>
-<span></span>
-<span><span class="fu">mo_fullname</span><span class="op">(</span><span class="st">"K. pneu rh"</span><span class="op">)</span> <span class="co"># "Klebsiella pneumoniae rhinoscleromatis"</span></span>
-<span><span class="fu">mo_shortname</span><span class="op">(</span><span class="st">"K. pneu rh"</span><span class="op">)</span> <span class="co"># "K. pneumoniae"</span></span>
-<span></span>
-<span><span class="co"># \donttest{</span></span>
-<span><span class="co"># Becker classification, see ?as.mo ----------------------------------------</span></span>
-<span><span class="fu">mo_fullname</span><span class="op">(</span><span class="st">"S. epi"</span><span class="op">)</span> <span class="co"># "Staphylococcus epidermidis"</span></span>
-<span><span class="fu">mo_fullname</span><span class="op">(</span><span class="st">"S. epi"</span>, Becker <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="co"># "Coagulase-negative Staphylococcus (CoNS)"</span></span>
-<span><span class="fu">mo_shortname</span><span class="op">(</span><span class="st">"S. epi"</span><span class="op">)</span> <span class="co"># "S. epidermidis"</span></span>
-<span><span class="fu">mo_shortname</span><span class="op">(</span><span class="st">"S. epi"</span>, Becker <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="co"># "CoNS"</span></span>
-<span></span>
-<span><span class="co"># Lancefield classification, see ?as.mo ------------------------------------</span></span>
-<span><span class="fu">mo_fullname</span><span class="op">(</span><span class="st">"S. pyo"</span><span class="op">)</span> <span class="co"># "Streptococcus pyogenes"</span></span>
-<span><span class="fu">mo_fullname</span><span class="op">(</span><span class="st">"S. pyo"</span>, Lancefield <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="co"># "Streptococcus group A"</span></span>
-<span><span class="fu">mo_shortname</span><span class="op">(</span><span class="st">"S. pyo"</span><span class="op">)</span> <span class="co"># "S. pyogenes"</span></span>
-<span><span class="fu">mo_shortname</span><span class="op">(</span><span class="st">"S. pyo"</span>, Lancefield <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="co"># "GAS" (='Group A Streptococci')</span></span>
-<span></span>
-<span></span>
-<span><span class="co"># language support --------------------------------------------------------</span></span>
-<span><span class="fu">mo_gramstain</span><span class="op">(</span><span class="st">"E. coli"</span>, language <span class="op">=</span> <span class="st">"de"</span><span class="op">)</span> <span class="co"># "Gramnegativ"</span></span>
-<span><span class="fu">mo_gramstain</span><span class="op">(</span><span class="st">"E. coli"</span>, language <span class="op">=</span> <span class="st">"nl"</span><span class="op">)</span> <span class="co"># "Gram-negatief"</span></span>
-<span><span class="fu">mo_gramstain</span><span class="op">(</span><span class="st">"E. coli"</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span> <span class="co"># "Gram negativo"</span></span>
-<span></span>
-<span><span class="co"># mo_type is equal to mo_kingdom, but mo_kingdom will remain official</span></span>
-<span><span class="fu">mo_kingdom</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Bacteria" on a German system</span></span>
-<span><span class="fu">mo_type</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Bakterien" on a German system</span></span>
-<span><span class="fu">mo_type</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span> <span class="co"># "Bacteria" on an English system</span></span>
-<span></span>
-<span><span class="fu">mo_fullname</span><span class="op">(</span><span class="st">"S. pyogenes"</span>,</span>
-<span> Lancefield <span class="op">=</span> <span class="cn">TRUE</span>,</span>
-<span> language <span class="op">=</span> <span class="st">"de"</span><span class="op">)</span> <span class="co"># "Streptococcus Gruppe A"</span></span>
-<span><span class="fu">mo_fullname</span><span class="op">(</span><span class="st">"S. pyogenes"</span>,</span>
-<span> Lancefield <span class="op">=</span> <span class="cn">TRUE</span>,</span>
-<span> language <span class="op">=</span> <span class="st">"nl"</span><span class="op">)</span> <span class="co"># "Streptococcus groep A"</span></span>
-<span></span>
-<span></span>
-<span><span class="co"># other --------------------------------------------------------------------</span></span>
-<span></span>
-<span><span class="fu">mo_is_yeast</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Candida"</span>, <span class="st">"E. coli"</span><span class="op">)</span><span class="op">)</span> <span class="co"># TRUE, FALSE</span></span>
-<span></span>
-<span><span class="co"># gram stains and intrinsic resistance can also be used as a filter in dplyr verbs</span></span>
-<span><span class="co"># \donttest{</span></span>
-<span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span>
-<span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu">mo_is_gram_positive</span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
-<span> </span>
-<span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu">mo_is_intrinsic_resistant</span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"vanco"</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="op">}</span></span>
-<span></span>
-<span></span>
-<span><span class="co"># get a list with the complete taxonomy (from kingdom to subspecies)</span></span>
-<span><span class="fu">mo_taxonomy</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span></span>
-<span><span class="co"># get a list with the taxonomy, the authors, Gram-stain,</span></span>
-<span><span class="co"># SNOMED codes, and URL to the online database</span></span>
-<span><span class="fu">mo_info</span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span></span>
-<span><span class="co"># }</span></span>
-<span><span class="co"># }</span></span></code></pre></div>
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-This is the fastest way to have your organisation (or analysis) specific codes picked up and translated by this package, since you don't have to bother about it again after setting it up once."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@univgroningen"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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- <h1>User-Defined Reference Data Set for Microorganisms</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mo_source.R" class="external-link"><code>R/mo_source.R</code></a></small>
- <div class="hidden name"><code>mo_source.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>These functions can be used to predefine your own reference to be used in <code><a href="as.mo.html">as.mo()</a></code> and consequently all <code><a href="mo_property.html">mo_*</a></code> functions (such as <code><a href="mo_property.html">mo_genus()</a></code> and <code><a href="mo_property.html">mo_gramstain()</a></code>).</p>
-<p>This is <strong>the fastest way</strong> to have your organisation (or analysis) specific codes picked up and translated by this package, since you don't have to bother about it again after setting it up once.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">set_mo_source</span><span class="op">(</span>
- <span class="va">path</span>,
- destination <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"AMR_mo_source"</span>, <span class="st">"~/mo_source.rds"</span><span class="op">)</span>
-<span class="op">)</span>
-
-<span class="fu">get_mo_source</span><span class="op">(</span>destination <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"AMR_mo_source"</span>, <span class="st">"~/mo_source.rds"</span><span class="op">)</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>path</dt>
-<dd><p>location of your reference file, this can be any text file (comma-, tab- or pipe-separated) or an Excel file (see <em>Details</em>). Can also be <code>""</code>, <code>NULL</code> or <code>FALSE</code> to delete the reference file.</p></dd>
-<dt>destination</dt>
-<dd><p>destination of the compressed data file, default to the user's home directory.</p></dd>
-</dl></div>
- <div id="details">
- <h2>Details</h2>
- <p>The reference file can be a text file separated with commas (CSV) or tabs or pipes, an Excel file (either 'xls' or 'xlsx' format) or an <span style="R">R</span> object file (extension '.rds'). To use an Excel file, you will need to have the <code>readxl</code> package installed.</p>
-<p><code>set_mo_source()</code> will check the file for validity: it must be a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>, must have a column named <code>"mo"</code> which contains values from <code><a href="microorganisms.html">microorganisms$mo</a></code> or <code><a href="microorganisms.html">microorganisms$fullname</a></code> and must have a reference column with your own defined values. If all tests pass, <code>set_mo_source()</code> will read the file into <span style="R">R</span> and will ask to export it to <code>"~/mo_source.rds"</code>. The CRAN policy disallows packages to write to the file system, although '<em>exceptions may be allowed in interactive sessions if the package obtains confirmation from the user</em>'. For this reason, this function only works in interactive sessions so that the user can <strong>specifically confirm and allow</strong> that this file will be created. The destination of this file can be set with the <code>destination</code> argument and defaults to the user's home directory. It can also be set as an <span style="R">R</span> option, using <code>options(AMR_mo_source = "my/location/file.rds")</code>.</p>
-<p>The created compressed data file <code>"mo_source.rds"</code> will be used at default for MO determination (function <code><a href="as.mo.html">as.mo()</a></code> and consequently all <code>mo_*</code> functions like <code><a href="mo_property.html">mo_genus()</a></code> and <code><a href="mo_property.html">mo_gramstain()</a></code>). The location and timestamp of the original file will be saved as an <a href="https://rdrr.io/r/base/attributes.html" class="external-link">attribute</a> to the compressed data file.</p>
-<p>The function <code>get_mo_source()</code> will return the data set by reading <code>"mo_source.rds"</code> with <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">readRDS()</a></code>. If the original file has changed (by checking the location and timestamp of the original file), it will call <code>set_mo_source()</code> to update the data file automatically if used in an interactive session.</p>
-<p>Reading an Excel file (<code>.xlsx</code>) with only one row has a size of 8-9 kB. The compressed file created with <code>set_mo_source()</code> will then have a size of 0.1 kB and can be read by <code>get_mo_source()</code> in only a couple of microseconds (millionths of a second).</p>
- </div>
- <div id="how-to-setup">
- <h2>How to Setup</h2>
-
-
-
-<p>Imagine this data on a sheet of an Excel file. The first column contains the organisation specific codes, the second column contains valid taxonomic names:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>We save it as <code>"home/me/ourcodes.xlsx"</code>. Now we have to set it as a source:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>It has now created a file <code>"~/mo_source.rds"</code> with the contents of our Excel file. Only the first column with foreign values and the 'mo' column will be kept when creating the RDS file.</p>
-<p>And now we can use it in our functions:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>If we edit the Excel file by, let's say, adding row 4 like this:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>...any new usage of an MO function in this package will update your data file:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>To delete the reference data file, just use <code>""</code>, <code>NULL</code> or <code>FALSE</code> as input for <code>set_mo_source()</code>:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>If the original file (in the previous case an Excel file) is moved or deleted, the <code>mo_source.rds</code> file will be removed upon the next use of <code><a href="as.mo.html">as.mo()</a></code> or any <code><a href="mo_property.html">mo_*</a></code> function.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
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- <h1>Principal Component Analysis (for AMR)</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/pca.R" class="external-link"><code>R/pca.R</code></a></small>
- <div class="hidden name"><code>pca.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">pca</span><span class="op">(</span>
- <span class="va">x</span>,
- <span class="va">...</span>,
- retx <span class="op">=</span> <span class="cn">TRUE</span>,
- center <span class="op">=</span> <span class="cn">TRUE</span>,
- scale. <span class="op">=</span> <span class="cn">TRUE</span>,
- tol <span class="op">=</span> <span class="cn">NULL</span>,
- rank. <span class="op">=</span> <span class="cn">NULL</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> columns</p></dd>
-<dt>...</dt>
-<dd><p>columns of <code>x</code> to be selected for PCA, can be unquoted since it supports quasiquotation.</p></dd>
-<dt>retx</dt>
-<dd><p>a logical value indicating whether the rotated variables
- should be returned.</p></dd>
-<dt>center</dt>
-<dd><p>a logical value indicating whether the variables
- should be shifted to be zero centered. Alternately, a vector of
- length equal the number of columns of <code>x</code> can be supplied.
- The value is passed to <code>scale</code>.</p></dd>
-<dt>scale.</dt>
-<dd><p>a logical value indicating whether the variables should
- be scaled to have unit variance before the analysis takes
- place. The default is <code>FALSE</code> for consistency with S, but
- in general scaling is advisable. Alternatively, a vector of length
- equal the number of columns of <code>x</code> can be supplied. The
- value is passed to <code><a href="https://rdrr.io/r/base/scale.html" class="external-link">scale</a></code>.</p></dd>
-<dt>tol</dt>
-<dd><p>a value indicating the magnitude below which components
- should be omitted. (Components are omitted if their
- standard deviations are less than or equal to <code>tol</code> times the
- standard deviation of the first component.) With the default null
- setting, no components are omitted (unless <code>rank.</code> is specified
- less than <code>min(dim(x))</code>.). Other settings for tol could be
- <code>tol = 0</code> or <code>tol = sqrt(.Machine$double.eps)</code>, which
- would omit essentially constant components.</p></dd>
-<dt>rank.</dt>
-<dd><p>optionally, a number specifying the maximal rank, i.e.,
- maximal number of principal components to be used. Can be set as
- alternative or in addition to <code>tol</code>, useful notably when the
- desired rank is considerably smaller than the dimensions of the matrix.</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>An object of classes pca and <a href="https://rdrr.io/r/stats/prcomp.html" class="external-link">prcomp</a></p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>The <code>pca()</code> function takes a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> as input and performs the actual PCA with the <span style="R">R</span> function <code><a href="https://rdrr.io/r/stats/prcomp.html" class="external-link">prcomp()</a></code>.</p>
-<p>The result of the <code>pca()</code> function is a <a href="https://rdrr.io/r/stats/prcomp.html" class="external-link">prcomp</a> object, with an additional attribute <code>non_numeric_cols</code> which is a vector with the column names of all columns that do not contain <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> values. These are probably the groups and labels, and will be used by <code><a href="ggplot_pca.html">ggplot_pca()</a></code>.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># `example_isolates` is a data set available in the AMR package.</span>
-<span class="co"># See ?example_isolates.</span>
-
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="co"># calculate the resistance per group first </span>
- <span class="va">resistance_data</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>order <span class="op">=</span> <span class="fu"><a href="mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, <span class="co"># group on anything, like order</span>
- genus <span class="op">=</span> <span class="fu"><a href="mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="co"># and genus as we do here;</span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html" class="external-link">summarise_if</a></span><span class="op">(</span><span class="va">is.rsi</span>, <span class="va">resistance</span><span class="op">)</span> <span class="co"># then get resistance of all drugs</span>
-
- <span class="co"># now conduct PCA for certain antimicrobial agents</span>
- <span class="va">pca_result</span> <span class="op"><-</span> <span class="va">resistance_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">pca</span><span class="op">(</span><span class="va">AMC</span>, <span class="va">CXM</span>, <span class="va">CTX</span>, <span class="va">CAZ</span>, <span class="va">GEN</span>, <span class="va">TOB</span>, <span class="va">TMP</span>, <span class="va">SXT</span><span class="op">)</span>
-
- <span class="va">pca_result</span>
- <span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span>
- <span class="fu"><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span>
- <span class="fu"><a href="ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span> <span class="co"># a new and convenient plot function</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
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- <h1>Plotting for Classes <code>rsi</code>, <code>mic</code> and <code>disk</code></h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
- <div class="hidden name"><code>plot.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Functions to plot classes <code>rsi</code>, <code>mic</code> and <code>disk</code>, with support for base <span style="R">R</span> and <code>ggplot2</code>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># S3 method for mic</span>
-<span class="fu">plot</span><span class="op">(</span>
- <span class="va">x</span>,
- mo <span class="op">=</span> <span class="cn">NULL</span>,
- ab <span class="op">=</span> <span class="cn">NULL</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span>,
- main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span>,
- ylab <span class="op">=</span> <span class="st">"Frequency"</span>,
- xlab <span class="op">=</span> <span class="st">"Minimum Inhibitory Concentration (mg/L)"</span>,
- colours_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"#ED553B"</span>, <span class="st">"#3CAEA3"</span>, <span class="st">"#F6D55C"</span><span class="op">)</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- expand <span class="op">=</span> <span class="cn">TRUE</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for mic</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span>
- <span class="va">object</span>,
- mo <span class="op">=</span> <span class="cn">NULL</span>,
- ab <span class="op">=</span> <span class="cn">NULL</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span>,
- title <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"MIC values of"</span>, <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">object</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>,
- ylab <span class="op">=</span> <span class="st">"Frequency"</span>,
- xlab <span class="op">=</span> <span class="st">"Minimum Inhibitory Concentration (mg/L)"</span>,
- colours_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"#ED553B"</span>, <span class="st">"#3CAEA3"</span>, <span class="st">"#F6D55C"</span><span class="op">)</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- expand <span class="op">=</span> <span class="cn">TRUE</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for mic</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/fortify.html" class="external-link">fortify</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="co"># S3 method for disk</span>
-<span class="fu">plot</span><span class="op">(</span>
- <span class="va">x</span>,
- main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span>,
- ylab <span class="op">=</span> <span class="st">"Frequency"</span>,
- xlab <span class="op">=</span> <span class="st">"Disk diffusion diameter (mm)"</span>,
- mo <span class="op">=</span> <span class="cn">NULL</span>,
- ab <span class="op">=</span> <span class="cn">NULL</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span>,
- colours_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"#ED553B"</span>, <span class="st">"#3CAEA3"</span>, <span class="st">"#F6D55C"</span><span class="op">)</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- expand <span class="op">=</span> <span class="cn">TRUE</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for disk</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span>
- <span class="va">object</span>,
- mo <span class="op">=</span> <span class="cn">NULL</span>,
- ab <span class="op">=</span> <span class="cn">NULL</span>,
- title <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Disk zones of"</span>, <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">object</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>,
- ylab <span class="op">=</span> <span class="st">"Frequency"</span>,
- xlab <span class="op">=</span> <span class="st">"Disk diffusion diameter (mm)"</span>,
- guideline <span class="op">=</span> <span class="st">"EUCAST"</span>,
- colours_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"#ED553B"</span>, <span class="st">"#3CAEA3"</span>, <span class="st">"#F6D55C"</span><span class="op">)</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- expand <span class="op">=</span> <span class="cn">TRUE</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for disk</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/fortify.html" class="external-link">fortify</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="co"># S3 method for rsi</span>
-<span class="fu">plot</span><span class="op">(</span>
- <span class="va">x</span>,
- ylab <span class="op">=</span> <span class="st">"Percentage"</span>,
- xlab <span class="op">=</span> <span class="st">"Antimicrobial Interpretation"</span>,
- main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for rsi</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span>
- <span class="va">object</span>,
- title <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Resistance Overview of"</span>, <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">object</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>,
- xlab <span class="op">=</span> <span class="st">"Antimicrobial Interpretation"</span>,
- ylab <span class="op">=</span> <span class="st">"Frequency"</span>,
- colours_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"#ED553B"</span>, <span class="st">"#3CAEA3"</span>, <span class="st">"#F6D55C"</span><span class="op">)</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for rsi</span>
-<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/fortify.html" class="external-link">fortify</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x, object</dt>
-<dd><p>values created with <code><a href="as.mic.html">as.mic()</a></code>, <code><a href="as.disk.html">as.disk()</a></code> or <code><a href="as.rsi.html">as.rsi()</a></code> (or their <code>random_*</code> variants, such as <code><a href="random.html">random_mic()</a></code>)</p></dd>
-<dt>mo</dt>
-<dd><p>any (vector of) text that can be coerced to a valid microorganism code with <code><a href="as.mo.html">as.mo()</a></code></p></dd>
-<dt>ab</dt>
-<dd><p>any (vector of) text that can be coerced to a valid antimicrobial code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
-<dt>guideline</dt>
-<dd><p>interpretation guideline to use, defaults to the latest included EUCAST guideline, see <em>Details</em></p></dd>
-<dt>main, title</dt>
-<dd><p>title of the plot</p></dd>
-<dt>xlab, ylab</dt>
-<dd><p>axis title</p></dd>
-<dt>colours_RSI</dt>
-<dd><p>colours to use for filling in the bars, must be a vector of three values (in the order R, S and I). The default colours are colour-blind friendly.</p></dd>
-<dt>language</dt>
-<dd><p>language to be used to translate 'Susceptible', 'Increased exposure'/'Intermediate' and 'Resistant', defaults to system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can be overwritten by setting the option <code>AMR_locale</code>, e.g. <code>options(AMR_locale = "de")</code>, see <a href="translate.html">translate</a>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
-<dt>expand</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.</p></dd>
-<dt>...</dt>
-<dd><p>arguments passed on to methods</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>The <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot()</a></code> functions return a <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></code> model that is extendible with any <code>ggplot2</code> function.
-The <code><a href="https://ggplot2.tidyverse.org/reference/fortify.html" class="external-link">fortify()</a></code> functions return a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> as an extension for usage in the <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot2::ggplot()</a></code> function.</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>The interpretation of "I" will be named "Increased exposure" for all EUCAST guidelines since 2019, and will be named "Intermediate" in all other cases.</p>
-<p>For interpreting MIC values as well as disk diffusion diameters, supported guidelines to be used as input for the <code>guideline</code> argument are: "EUCAST 2022", "EUCAST 2021", "EUCAST 2020", "EUCAST 2019", "EUCAST 2018", "EUCAST 2017", "EUCAST 2016", "EUCAST 2015", "EUCAST 2014", "EUCAST 2013", "EUCAST 2012", "EUCAST 2011", "CLSI 2022", "CLSI 2021", "CLSI 2020", "CLSI 2019", "CLSI 2018", "CLSI 2017", "CLSI 2016", "CLSI 2015", "CLSI 2014", "CLSI 2013", "CLSI 2012" and "CLSI 2011".</p>
-<p>Simply using <code>"CLSI"</code> or <code>"EUCAST"</code> as input will automatically select the latest version of that guideline.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
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-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">some_mic_values</span> <span class="op"><-</span> <span class="fu"><a href="random.html">random_mic</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
-<span class="va">some_disk_values</span> <span class="op"><-</span> <span class="fu"><a href="random.html">random_disk</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">100</span>, mo <span class="op">=</span> <span class="st">"Escherichia coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span>
-<span class="va">some_rsi_values</span> <span class="op"><-</span> <span class="fu"><a href="random.html">random_rsi</a></span><span class="op">(</span><span class="fl">50</span>, prob_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.30</span>, <span class="fl">0.55</span>, <span class="fl">0.05</span><span class="op">)</span><span class="op">)</span>
-
-<span class="fu">plot</span><span class="op">(</span><span class="va">some_mic_values</span><span class="op">)</span>
-<span class="fu">plot</span><span class="op">(</span><span class="va">some_disk_values</span><span class="op">)</span>
-<span class="fu">plot</span><span class="op">(</span><span class="va">some_rsi_values</span><span class="op">)</span>
-
-<span class="co"># when providing the microorganism and antibiotic, colours will show interpretations:</span>
-<span class="fu">plot</span><span class="op">(</span><span class="va">some_mic_values</span>, mo <span class="op">=</span> <span class="st">"S. aureus"</span>, ab <span class="op">=</span> <span class="st">"ampicillin"</span><span class="op">)</span>
-<span class="fu">plot</span><span class="op">(</span><span class="va">some_disk_values</span>, mo <span class="op">=</span> <span class="st">"Escherichia coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span>
-
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://ggplot2.tidyverse.org" class="external-link">"ggplot2"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">some_mic_values</span><span class="op">)</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">some_disk_values</span>, mo <span class="op">=</span> <span class="st">"Escherichia coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">some_rsi_values</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
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- <h1>Calculate Microbial Resistance</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/proportion.R" class="external-link"><code>R/proportion.R</code></a>, <a href="https://github.com/msberends/AMR/blob/HEAD/R/rsi_df.R" class="external-link"><code>R/rsi_df.R</code></a></small>
- <div class="hidden name"><code>proportion.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code> from the <code>dplyr</code> package and also support grouped variables, see <em>Examples</em>.</p>
-<p><code>resistance()</code> should be used to calculate resistance, <code>susceptibility()</code> should be used to calculate susceptibility.<br></p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">resistance</span><span class="op">(</span><span class="va">...</span>, minimum <span class="op">=</span> <span class="fl">30</span>, as_percent <span class="op">=</span> <span class="cn">FALSE</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">susceptibility</span><span class="op">(</span><span class="va">...</span>, minimum <span class="op">=</span> <span class="fl">30</span>, as_percent <span class="op">=</span> <span class="cn">FALSE</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">proportion_R</span><span class="op">(</span><span class="va">...</span>, minimum <span class="op">=</span> <span class="fl">30</span>, as_percent <span class="op">=</span> <span class="cn">FALSE</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">proportion_IR</span><span class="op">(</span><span class="va">...</span>, minimum <span class="op">=</span> <span class="fl">30</span>, as_percent <span class="op">=</span> <span class="cn">FALSE</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">proportion_I</span><span class="op">(</span><span class="va">...</span>, minimum <span class="op">=</span> <span class="fl">30</span>, as_percent <span class="op">=</span> <span class="cn">FALSE</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">proportion_SI</span><span class="op">(</span><span class="va">...</span>, minimum <span class="op">=</span> <span class="fl">30</span>, as_percent <span class="op">=</span> <span class="cn">FALSE</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">proportion_S</span><span class="op">(</span><span class="va">...</span>, minimum <span class="op">=</span> <span class="fl">30</span>, as_percent <span class="op">=</span> <span class="cn">FALSE</span>, only_all_tested <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="fu">proportion_df</span><span class="op">(</span>
- <span class="va">data</span>,
- translate_ab <span class="op">=</span> <span class="st">"name"</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- minimum <span class="op">=</span> <span class="fl">30</span>,
- as_percent <span class="op">=</span> <span class="cn">FALSE</span>,
- combine_SI <span class="op">=</span> <span class="cn">TRUE</span>,
- combine_IR <span class="op">=</span> <span class="cn">FALSE</span>
-<span class="op">)</span>
-
-<span class="fu">rsi_df</span><span class="op">(</span>
- <span class="va">data</span>,
- translate_ab <span class="op">=</span> <span class="st">"name"</span>,
- language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,
- minimum <span class="op">=</span> <span class="fl">30</span>,
- as_percent <span class="op">=</span> <span class="cn">FALSE</span>,
- combine_SI <span class="op">=</span> <span class="cn">TRUE</span>,
- combine_IR <span class="op">=</span> <span class="cn">FALSE</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="source">
- <h2>Source</h2>
- <p><strong>M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition</strong>, 2014, <em>Clinical and Laboratory Standards Institute (CLSI)</em>. <a href="https://clsi.org/standards/products/microbiology/documents/m39/" class="external-link">https://clsi.org/standards/products/microbiology/documents/m39/</a>.</p>
- </div>
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>...</dt>
-<dd><p>one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with <code><a href="as.rsi.html">as.rsi()</a></code> if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See <em>Examples</em>.</p></dd>
-<dt>minimum</dt>
-<dd><p>the minimum allowed number of available (tested) isolates. Any isolate count lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see <em>Source</em>.</p></dd>
-<dt>as_percent</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the output must be returned as a hundred fold with % sign (a character). A value of <code>0.123456</code> will then be returned as <code>"12.3%"</code>.</p></dd>
-<dt>only_all_tested</dt>
-<dd><p>(for combination therapies, i.e. using more than one variable for <code>...</code>): a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that isolates must be tested for all antibiotics, see section <em>Combination Therapy</em> below</p></dd>
-<dt>data</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing columns with class <code><a href="as.rsi.html">rsi</a></code> (see <code><a href="as.rsi.html">as.rsi()</a></code>)</p></dd>
-<dt>translate_ab</dt>
-<dd><p>a column name of the <a href="antibiotics.html">antibiotics</a> data set to translate the antibiotic abbreviations to, using <code><a href="ab_property.html">ab_property()</a></code></p></dd>
-<dt>language</dt>
-<dd><p>language of the returned text, defaults to system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with <code>getOption("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
-<dt>combine_SI</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument <code>combine_IR</code>, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is <code>TRUE</code>.</p></dd>
-<dt>combine_IR</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see argument <code>combine_SI</code>.</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>A <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> or, when <code>as_percent = TRUE</code>, a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>.</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>The function <code>resistance()</code> is equal to the function <code>proportion_R()</code>. The function <code>susceptibility()</code> is equal to the function <code>proportion_SI()</code>.</p>
-<p><strong>Remember that you should filter your data to let it contain only first isolates!</strong> This is needed to exclude duplicates and to reduce selection bias. Use <code><a href="first_isolate.html">first_isolate()</a></code> to determine them in your data set.</p>
-<p>These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the <code><a href="count.html">count()</a></code> functions to count isolates. The function <code>susceptibility()</code> is essentially equal to <code>count_susceptible() / count_all()</code>. <em>Low counts can influence the outcome - the <code>proportion</code> functions may camouflage this, since they only return the proportion (albeit being dependent on the <code>minimum</code> argument).</em></p>
-<p>The function <code>proportion_df()</code> takes any variable from <code>data</code> that has an <code><a href="as.rsi.html">rsi</a></code> class (created with <code><a href="as.rsi.html">as.rsi()</a></code>) and calculates the proportions R, I and S. It also supports grouped variables. The function <code>rsi_df()</code> works exactly like <code>proportion_df()</code>, but adds the number of isolates.</p>
- </div>
- <div id="combination-therapy">
- <h2>Combination Therapy</h2>
-
-
-<p>When using more than one variable for <code>...</code> (= combination therapy), use <code>only_all_tested</code> to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Drug A and Drug B, about how <code>susceptibility()</code> works to calculate the %SI:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>Please note that, in combination therapies, for <code>only_all_tested = TRUE</code> applies that:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>and that, in combination therapies, for <code>only_all_tested = FALSE</code> applies that:</p>
-<p></p><div class="sourceCode"><pre><code></code></pre><p></p></div>
-<p>Using <code>only_all_tested</code> has no impact when only using one antibiotic as input.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="interpretation-of-r-and-s-i">
- <h2>Interpretation of R and S/I</h2>
-
-
-<p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (<a href="https://www.eucast.org/newsiandr/" class="external-link">https://www.eucast.org/newsiandr/</a>).</p><ul><li><p><strong>R = Resistant</strong><br>
-A microorganism is categorised as <em>Resistant</em> when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p></li>
-<li><p><strong>S = Susceptible</strong><br>
-A microorganism is categorised as <em>Susceptible, standard dosing regimen</em>, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
-<li><p><strong>I = Susceptible, Increased exposure</strong><br>
-A microorganism is categorised as <em>Susceptible, Increased exposure</em> when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.</p></li>
-</ul><p>This AMR package honours this (new) insight. Use <code>susceptibility()</code> (equal to <code>proportion_SI()</code>) to determine antimicrobial susceptibility and <code><a href="count.html">count_susceptible()</a></code> (equal to <code><a href="count.html">count_SI()</a></code>) to count susceptible isolates.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="count.html">count()</a></code> to count resistant and susceptible isolates.</p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># example_isolates is a data set available in the AMR package.</span>
-<span class="op">?</span><span class="va">example_isolates</span>
-
-<span class="fu">resistance</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span> <span class="co"># determines %R</span>
-<span class="fu">susceptibility</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span> <span class="co"># determines %S+I</span>
-
-<span class="co"># be more specific</span>
-<span class="fu">proportion_S</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu">proportion_SI</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu">proportion_I</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu">proportion_IR</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-<span class="fu">proportion_R</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">AMX</span><span class="op">)</span>
-
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>r <span class="op">=</span> <span class="fu">resistance</span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span>,
- n <span class="op">=</span> <span class="fu"><a href="count.html">n_rsi</a></span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span><span class="op">)</span> <span class="co"># n_rsi works like n_distinct in dplyr, see ?n_rsi</span>
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>R <span class="op">=</span> <span class="fu">resistance</span><span class="op">(</span><span class="va">CIP</span>, as_percent <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,
- SI <span class="op">=</span> <span class="fu">susceptibility</span><span class="op">(</span><span class="va">CIP</span>, as_percent <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,
- n1 <span class="op">=</span> <span class="fu"><a href="count.html">count_all</a></span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span>, <span class="co"># the actual total; sum of all three</span>
- n2 <span class="op">=</span> <span class="fu"><a href="count.html">n_rsi</a></span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span>, <span class="co"># same - analogous to n_distinct</span>
- total <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/context.html" class="external-link">n</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co"># NOT the number of tested isolates!</span>
-
- <span class="co"># Calculate co-resistance between amoxicillin/clav acid and gentamicin,</span>
- <span class="co"># so we can see that combination therapy does a lot more than mono therapy:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">susceptibility</span><span class="op">(</span><span class="va">AMC</span><span class="op">)</span> <span class="co"># %SI = 76.3%</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="count.html">count_all</a></span><span class="op">(</span><span class="va">AMC</span><span class="op">)</span> <span class="co"># n = 1879</span>
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">susceptibility</span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span> <span class="co"># %SI = 75.4%</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="count.html">count_all</a></span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span> <span class="co"># n = 1855</span>
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu">susceptibility</span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span><span class="op">)</span> <span class="co"># %SI = 94.1%</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> <span class="fu"><a href="count.html">count_all</a></span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span><span class="op">)</span> <span class="co"># n = 1939</span>
-
-
- <span class="co"># See Details on how `only_all_tested` works. Example:</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>numerator <span class="op">=</span> <span class="fu"><a href="count.html">count_susceptible</a></span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span><span class="op">)</span>,
- denominator <span class="op">=</span> <span class="fu"><a href="count.html">count_all</a></span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span><span class="op">)</span>,
- proportion <span class="op">=</span> <span class="fu">susceptibility</span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span><span class="op">)</span><span class="op">)</span>
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>numerator <span class="op">=</span> <span class="fu"><a href="count.html">count_susceptible</a></span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span>, only_all_tested <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,
- denominator <span class="op">=</span> <span class="fu"><a href="count.html">count_all</a></span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span>, only_all_tested <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,
- proportion <span class="op">=</span> <span class="fu">susceptibility</span><span class="op">(</span><span class="va">AMC</span>, <span class="va">GEN</span>, only_all_tested <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span>
-
-
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>cipro_p <span class="op">=</span> <span class="fu">susceptibility</span><span class="op">(</span><span class="va">CIP</span>, as_percent <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,
- cipro_n <span class="op">=</span> <span class="fu"><a href="count.html">count_all</a></span><span class="op">(</span><span class="va">CIP</span><span class="op">)</span>,
- genta_p <span class="op">=</span> <span class="fu">susceptibility</span><span class="op">(</span><span class="va">GEN</span>, as_percent <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,
- genta_n <span class="op">=</span> <span class="fu"><a href="count.html">count_all</a></span><span class="op">(</span><span class="va">GEN</span><span class="op">)</span>,
- combination_p <span class="op">=</span> <span class="fu">susceptibility</span><span class="op">(</span><span class="va">CIP</span>, <span class="va">GEN</span>, as_percent <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,
- combination_n <span class="op">=</span> <span class="fu"><a href="count.html">count_all</a></span><span class="op">(</span><span class="va">CIP</span>, <span class="va">GEN</span><span class="op">)</span><span class="op">)</span>
-
- <span class="co"># Get proportions S/I/R immediately of all rsi columns</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">proportion_df</span><span class="op">(</span>translate <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
- <span class="co"># It also supports grouping variables</span>
- <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">hospital_id</span>, <span class="va">AMX</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">proportion_df</span><span class="op">(</span>translate <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
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- <span class="fa fa-dice"></span>
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- Predict antimicrobial resistance
- </a>
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- <li>
- <a href="../articles/datasets.html">
- <span class="fa fa-database"></span>
-
- Data sets for download / own use
- </a>
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- <li>
- <a href="../articles/PCA.html">
- <span class="fa fa-compress"></span>
-
- Conduct principal component analysis for AMR
- </a>
- </li>
- <li>
- <a href="../articles/MDR.html">
- <span class="fa fa-skull-crossbones"></span>
-
- Determine multi-drug resistance (MDR)
- </a>
- </li>
- <li>
- <a href="../articles/WHONET.html">
- <span class="fa fa-globe-americas"></span>
-
- Work with WHONET data
- </a>
- </li>
- <li>
- <a href="../articles/SPSS.html">
- <span class="fa fa-file-upload"></span>
-
- Import data from SPSS/SAS/Stata
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- <a href="../articles/EUCAST.html">
- <span class="fa fa-exchange-alt"></span>
-
- Apply EUCAST rules
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- <div class="col-md-9 contents">
- <div class="page-header">
- <h1>Random MIC Values/Disk Zones/RSI Generation</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/random.R" class="external-link"><code>R/random.R</code></a></small>
- <div class="hidden name"><code>random.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>These functions can be used for generating random MIC values and disk diffusion diameters, for AMR data analysis practice. By providing a microorganism and antimicrobial agent, the generated results will reflect reality as much as possible.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">random_mic</span><span class="op">(</span>size <span class="op">=</span> <span class="cn">NULL</span>, mo <span class="op">=</span> <span class="cn">NULL</span>, ab <span class="op">=</span> <span class="cn">NULL</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">random_disk</span><span class="op">(</span>size <span class="op">=</span> <span class="cn">NULL</span>, mo <span class="op">=</span> <span class="cn">NULL</span>, ab <span class="op">=</span> <span class="cn">NULL</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">random_rsi</span><span class="op">(</span>size <span class="op">=</span> <span class="cn">NULL</span>, prob_RSI <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.33</span>, <span class="fl">0.33</span>, <span class="fl">0.33</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>size</dt>
-<dd><p>desired size of the returned vector. If used in a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> call or <code>dplyr</code> verb, will get the current (group) size if left blank.</p></dd>
-<dt>mo</dt>
-<dd><p>any <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> that can be coerced to a valid microorganism code with <code><a href="as.mo.html">as.mo()</a></code></p></dd>
-<dt>ab</dt>
-<dd><p>any <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> that can be coerced to a valid antimicrobial agent code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
-<dt>...</dt>
-<dd><p>ignored, only in place to allow future extensions</p></dd>
-<dt>prob_RSI</dt>
-<dd><p>a vector of length 3: the probabilities for "R" (1st value), "S" (2nd value) and "I" (3rd value)</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>class <code><mic></code> for <code>random_mic()</code> (see <code><a href="as.mic.html">as.mic()</a></code>) and class <code><disk></code> for <code>random_disk()</code> (see <code><a href="as.disk.html">as.disk()</a></code>)</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>The base <span style="R">R</span> function <code><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample()</a></code> is used for generating values.</p>
-<p>Generated values are based on the EUCAST 2022 guideline as implemented in the <a href="rsi_translation.html">rsi_translation</a> data set. To create specific generated values per bug or drug, set the <code>mo</code> and/or <code>ab</code> argument.</p>
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">random_mic</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span>
-<span class="fu">random_disk</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span>
-<span class="fu">random_rsi</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span>
-
-<span class="co"># \donttest{</span>
-<span class="co"># make the random generation more realistic by setting a bug and/or drug:</span>
-<span class="fu">random_mic</span><span class="op">(</span><span class="fl">100</span>, <span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span> <span class="co"># range 0.0625-64</span>
-<span class="fu">random_mic</span><span class="op">(</span><span class="fl">100</span>, <span class="st">"Klebsiella pneumoniae"</span>, <span class="st">"meropenem"</span><span class="op">)</span> <span class="co"># range 0.0625-16</span>
-<span class="fu">random_mic</span><span class="op">(</span><span class="fl">100</span>, <span class="st">"Streptococcus pneumoniae"</span>, <span class="st">"meropenem"</span><span class="op">)</span> <span class="co"># range 0.0625-4</span>
-
-<span class="fu">random_disk</span><span class="op">(</span><span class="fl">100</span>, <span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span> <span class="co"># range 8-50</span>
-<span class="fu">random_disk</span><span class="op">(</span><span class="fl">100</span>, <span class="st">"Klebsiella pneumoniae"</span>, <span class="st">"ampicillin"</span><span class="op">)</span> <span class="co"># range 11-17</span>
-<span class="fu">random_disk</span><span class="op">(</span><span class="fl">100</span>, <span class="st">"Streptococcus pneumoniae"</span>, <span class="st">"ampicillin"</span><span class="op">)</span> <span class="co"># range 12-27</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/resistance_predict.html b/docs/reference/resistance_predict.html
deleted file mode 100644
index 3f5cd32bb..000000000
--- a/docs/reference/resistance_predict.html
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- <h1>Predict Antimicrobial Resistance</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/resistance_predict.R" class="external-link"><code>R/resistance_predict.R</code></a></small>
- <div class="hidden name"><code>resistance_predict.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns <code>se_min</code> and <code>se_max</code>. See <em>Examples</em> for a real live example.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">resistance_predict</span><span class="op">(</span>
- <span class="va">x</span>,
- <span class="va">col_ab</span>,
- col_date <span class="op">=</span> <span class="cn">NULL</span>,
- year_min <span class="op">=</span> <span class="cn">NULL</span>,
- year_max <span class="op">=</span> <span class="cn">NULL</span>,
- year_every <span class="op">=</span> <span class="fl">1</span>,
- minimum <span class="op">=</span> <span class="fl">30</span>,
- model <span class="op">=</span> <span class="cn">NULL</span>,
- I_as_S <span class="op">=</span> <span class="cn">TRUE</span>,
- preserve_measurements <span class="op">=</span> <span class="cn">TRUE</span>,
- info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="fu">rsi_predict</span><span class="op">(</span>
- <span class="va">x</span>,
- <span class="va">col_ab</span>,
- col_date <span class="op">=</span> <span class="cn">NULL</span>,
- year_min <span class="op">=</span> <span class="cn">NULL</span>,
- year_max <span class="op">=</span> <span class="cn">NULL</span>,
- year_every <span class="op">=</span> <span class="fl">1</span>,
- minimum <span class="op">=</span> <span class="fl">30</span>,
- model <span class="op">=</span> <span class="cn">NULL</span>,
- I_as_S <span class="op">=</span> <span class="cn">TRUE</span>,
- preserve_measurements <span class="op">=</span> <span class="cn">TRUE</span>,
- info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for resistance_predict</span>
-<span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">x</span>, main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Resistance Prediction of"</span>, <span class="va">x_name</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span>
-
-<span class="fu">ggplot_rsi_predict</span><span class="op">(</span>
- <span class="va">x</span>,
- main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Resistance Prediction of"</span>, <span class="va">x_name</span><span class="op">)</span>,
- ribbon <span class="op">=</span> <span class="cn">TRUE</span>,
- <span class="va">...</span>
-<span class="op">)</span>
-
-<span class="co"># S3 method for resistance_predict</span>
-<span class="fu">autoplot</span><span class="op">(</span>
- <span class="va">object</span>,
- main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Resistance Prediction of"</span>, <span class="va">x_name</span><span class="op">)</span>,
- ribbon <span class="op">=</span> <span class="cn">TRUE</span>,
- <span class="va">...</span>
-<span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing isolates. Can be left blank for automatic determination, see <em>Examples</em>.</p></dd>
-<dt>col_ab</dt>
-<dd><p>column name of <code>x</code> containing antimicrobial interpretations (<code>"R"</code>, <code>"I"</code> and <code>"S"</code>)</p></dd>
-<dt>col_date</dt>
-<dd><p>column name of the date, will be used to calculate years if this column doesn't consist of years already, defaults to the first column of with a date class</p></dd>
-<dt>year_min</dt>
-<dd><p>lowest year to use in the prediction model, dafaults to the lowest year in <code>col_date</code></p></dd>
-<dt>year_max</dt>
-<dd><p>highest year to use in the prediction model, defaults to 10 years after today</p></dd>
-<dt>year_every</dt>
-<dd><p>unit of sequence between lowest year found in the data and <code>year_max</code></p></dd>
-<dt>minimum</dt>
-<dd><p>minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.</p></dd>
-<dt>model</dt>
-<dd><p>the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using <code>glm(..., family = binomial)</code>, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See <em>Details</em> for all valid options.</p></dd>
-<dt>I_as_S</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether values <code>"I"</code> should be treated as <code>"S"</code> (will otherwise be treated as <code>"R"</code>). The default, <code>TRUE</code>, follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section <em>Interpretation of S, I and R</em> below.</p></dd>
-<dt>preserve_measurements</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be <code>NA</code>.</p></dd>
-<dt>info</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether textual analysis should be printed with the name and <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code> of the statistical model.</p></dd>
-<dt>...</dt>
-<dd><p>arguments passed on to functions</p></dd>
-<dt>main</dt>
-<dd><p>title of the plot</p></dd>
-<dt>ribbon</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a ribbon should be shown (default) or error bars</p></dd>
-<dt>object</dt>
-<dd><p>model data to be plotted</p></dd>
-</dl></div>
- <div id="value">
- <h2>Value</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with extra class <code>resistance_predict</code> with columns:</p><ul><li><p><code>year</code></p></li>
-<li><p><code>value</code>, the same as <code>estimated</code> when <code>preserve_measurements = FALSE</code>, and a combination of <code>observed</code> and <code>estimated</code> otherwise</p></li>
-<li><p><code>se_min</code>, the lower bound of the standard error with a minimum of <code>0</code> (so the standard error will never go below 0%)</p></li>
-<li><p><code>se_max</code> the upper bound of the standard error with a maximum of <code>1</code> (so the standard error will never go above 100%)</p></li>
-<li><p><code>observations</code>, the total number of available observations in that year, i.e. \(S + I + R\)</p></li>
-<li><p><code>observed</code>, the original observed resistant percentages</p></li>
-<li><p><code>estimated</code>, the estimated resistant percentages, calculated by the model</p></li>
-</ul><p>Furthermore, the model itself is available as an attribute: <code>attributes(x)$model</code>, see <em>Examples</em>.</p>
- </div>
- <div id="details">
- <h2>Details</h2>
- <p>Valid options for the statistical model (argument <code>model</code>) are:</p><ul><li><p><code>"binomial"</code> or <code>"binom"</code> or <code>"logit"</code>: a generalised linear regression model with binomial distribution</p></li>
-<li><p><code>"loglin"</code> or <code>"poisson"</code>: a generalised log-linear regression model with poisson distribution</p></li>
-<li><p><code>"lin"</code> or <code>"linear"</code>: a linear regression model</p></li>
-</ul></div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="interpretation-of-r-and-s-i">
- <h2>Interpretation of R and S/I</h2>
-
-
-<p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (<a href="https://www.eucast.org/newsiandr/" class="external-link">https://www.eucast.org/newsiandr/</a>).</p><ul><li><p><strong>R = Resistant</strong><br>
-A microorganism is categorised as <em>Resistant</em> when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p></li>
-<li><p><strong>S = Susceptible</strong><br>
-A microorganism is categorised as <em>Susceptible, standard dosing regimen</em>, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
-<li><p><strong>I = Susceptible, Increased exposure</strong><br>
-A microorganism is categorised as <em>Susceptible, Increased exposure</em> when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.</p></li>
-</ul><p>This AMR package honours this (new) insight. Use <code><a href="proportion.html">susceptibility()</a></code> (equal to <code><a href="proportion.html">proportion_SI()</a></code>) to determine antimicrobial susceptibility and <code><a href="count.html">count_susceptible()</a></code> (equal to <code><a href="count.html">count_SI()</a></code>) to count susceptible isolates.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p>The <code><a href="proportion.html">proportion()</a></code> functions to calculate resistance</p>
-<p>Models: <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm()</a></code> <code><a href="https://rdrr.io/r/stats/glm.html" class="external-link">glm()</a></code></p></div>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">x</span> <span class="op"><-</span> <span class="fu">resistance_predict</span><span class="op">(</span><span class="va">example_isolates</span>,
- col_ab <span class="op">=</span> <span class="st">"AMX"</span>,
- year_min <span class="op">=</span> <span class="fl">2010</span>,
- model <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span>
-<span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-<span class="co"># \donttest{</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://ggplot2.tidyverse.org" class="external-link">"ggplot2"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="fu">ggplot_rsi_predict</span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-<span class="op">}</span>
-
-<span class="co"># using dplyr:</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
- <span class="va">x</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Staphylococcus"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">resistance_predict</span><span class="op">(</span><span class="st">"PEN"</span>, model <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span>
- <span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
-
- <span class="co"># get the model from the object</span>
- <span class="va">mymodel</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html" class="external-link">attributes</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">$</span><span class="va">model</span>
- <span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">mymodel</span><span class="op">)</span>
-<span class="op">}</span>
-
-<span class="co"># create nice plots with ggplot2 yourself</span>
-<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span> <span class="op">&</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://ggplot2.tidyverse.org" class="external-link">"ggplot2"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
-
- <span class="va">data</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">mo</span> <span class="op">==</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
- <span class="fu">resistance_predict</span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"AMX"</span>,
- col_date <span class="op">=</span> <span class="st">"date"</span>,
- model <span class="op">=</span> <span class="st">"binomial"</span>,
- info <span class="op">=</span> <span class="cn">FALSE</span>,
- minimum <span class="op">=</span> <span class="fl">15</span><span class="op">)</span>
-
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span>
-
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">data</span>,
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">year</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html" class="external-link">geom_col</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>y <span class="op">=</span> <span class="va">value</span><span class="op">)</span>,
- fill <span class="op">=</span> <span class="st">"grey75"</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_linerange.html" class="external-link">geom_errorbar</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>ymin <span class="op">=</span> <span class="va">se_min</span>,
- ymax <span class="op">=</span> <span class="va">se_max</span><span class="op">)</span>,
- colour <span class="op">=</span> <span class="st">"grey50"</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_continuous.html" class="external-link">scale_y_continuous</a></span><span class="op">(</span>limits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span><span class="op">)</span>,
- breaks <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">0.1</span><span class="op">)</span>,
- labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">100</span>, <span class="fl">10</span><span class="op">)</span>, <span class="st">"%"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/expression.html" class="external-link">expression</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Forecast of Amoxicillin Resistance in "</span>,
- <span class="fu"><a href="https://rdrr.io/r/grDevices/plotmath.html" class="external-link">italic</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>,
- y <span class="op">=</span> <span class="st">"%R"</span>,
- x <span class="op">=</span> <span class="st">"Year"</span><span class="op">)</span> <span class="op">+</span>
- <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span>base_size <span class="op">=</span> <span class="fl">13</span><span class="op">)</span>
-<span class="op">}</span>
-<span class="co"># }</span>
-</code></pre></div>
- </div>
- </div>
- <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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- <h1>Data Set for R/SI Interpretation</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
- <div class="hidden name"><code>rsi_translation.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (2011-2022) and CLSI (2011-2022). Use <code><a href="as.rsi.html">as.rsi()</a></code> to transform MICs or disks measurements to R/SI values.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">rsi_translation</span></span></code></pre></div>
- </div>
-
- <div id="format">
- <h2>Format</h2>
- <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with 20,369 observations and 11 variables:</p><ul><li><p><code>guideline</code><br> Name of the guideline</p></li>
-<li><p><code>method</code><br> Either "DISK" or "MIC"</p></li>
-<li><p><code>site</code><br> Body site, e.g. "Oral" or "Respiratory"</p></li>
-<li><p><code>mo</code><br> Microbial ID, see <code><a href="as.mo.html">as.mo()</a></code></p></li>
-<li><p><code>rank_index</code><br> Taxonomic rank index of <code>mo</code> from 1 (subspecies/infraspecies) to 5 (unknown microorganism)</p></li>
-<li><p><code>ab</code><br> Antibiotic ID, see <code><a href="as.ab.html">as.ab()</a></code></p></li>
-<li><p><code>ref_tbl</code><br> Info about where the guideline rule can be found</p></li>
-<li><p><code>disk_dose</code><br> Dose of the used disk diffusion method</p></li>
-<li><p><code>breakpoint_S</code><br> Lowest MIC value or highest number of millimetres that leads to "S"</p></li>
-<li><p><code>breakpoint_R</code><br> Highest MIC value or lowest number of millimetres that leads to "R"</p></li>
-<li><p><code>uti</code><br> A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> value (<code>TRUE</code>/<code>FALSE</code>) to indicate whether the rule applies to a urinary tract infection (UTI)</p></li>
-</ul></div>
- <div id="details">
- <h2>Details</h2>
- <p>Overview of the data set:</p>
-<p></p><div class="sourceCode r"><pre><code><span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">rsi_translation</span><span class="op">)</span></span>
-<span><span class="co">#> guideline method site mo rank_index ab ref_tbl disk_dose</span></span>
-<span><span class="co">#> 1 EUCAST 2022 MIC <NA> F_ASPRG_MGTS 2 AMB Aspergillus <NA></span></span>
-<span><span class="co">#> 2 EUCAST 2022 MIC <NA> F_ASPRG_NIGR 2 AMB Aspergillus <NA></span></span>
-<span><span class="co">#> 3 EUCAST 2022 MIC <NA> F_CANDD 3 AMB Candida <NA></span></span>
-<span><span class="co">#> 4 EUCAST 2022 MIC <NA> F_CANDD_ALBC 2 AMB Candida <NA></span></span>
-<span><span class="co">#> 5 EUCAST 2022 MIC <NA> F_CANDD_DBLN 2 AMB Candida <NA></span></span>
-<span><span class="co">#> 6 EUCAST 2022 MIC <NA> F_CANDD_KRUS 2 AMB Candida <NA></span></span>
-<span><span class="co">#> breakpoint_S breakpoint_R uti</span></span>
-<span><span class="co">#> 1 1 1 FALSE</span></span>
-<span><span class="co">#> 2 1 1 FALSE</span></span>
-<span><span class="co">#> 3 1 1 FALSE</span></span>
-<span><span class="co">#> 4 1 1 FALSE</span></span>
-<span><span class="co">#> 5 1 1 FALSE</span></span>
-<span><span class="co">#> 6 1 1 FALSE</span></span></code></pre><p></p></div>
-<p>The repository of this <code>AMR</code> package contains a file comprising this exact data set: <a href="https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt" class="external-link">https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt</a>. This file <strong>allows for machine reading EUCAST and CLSI guidelines</strong>, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically and the <code>mo</code> and <code>ab</code> columns have been transformed to contain the full official names instead of codes.</p>
- </div>
- <div id="reference-data-publicly-available">
- <h2>Reference Data Publicly Available</h2>
-
-
-<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
- <div id="see-also">
- <h2>See also</h2>
- <div class="dont-index"><p><a href="intrinsic_resistant.html">intrinsic_resistant</a></p></div>
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-When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@univgroningen"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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- <h1>Skewness of the Sample</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/skewness.R" class="external-link"><code>R/skewness.R</code></a></small>
- <div class="hidden name"><code>skewness.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.</p>
-<p>When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="co"># S3 method for default</span>
-<span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="co"># S3 method for matrix</span>
-<span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
-
-<span class="co"># S3 method for data.frame</span>
-<span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="arguments">
- <h2>Arguments</h2>
- <dl><dt>x</dt>
-<dd><p>a vector of values, a <a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a> or a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p></dd>
-<dt>na.rm</dt>
-<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> value indicating whether <code>NA</code> values should be stripped before the computation proceeds</p></dd>
-</dl></div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
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- <h2>See also</h2>
- <div class="dont-index"><p><code><a href="kurtosis.html">kurtosis()</a></code></p></div>
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- <h1>Translate Strings from AMR Package</h1>
- <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/translate.R" class="external-link"><code>R/translate.R</code></a></small>
- <div class="hidden name"><code>translate.Rd</code></div>
- </div>
-
- <div class="ref-description">
- <p>For language-dependent output of AMR functions, like <code><a href="mo_property.html">mo_name()</a></code>, <code><a href="mo_property.html">mo_gramstain()</a></code>, <code><a href="mo_property.html">mo_type()</a></code> and <code><a href="ab_property.html">ab_name()</a></code>.</p>
- </div>
-
- <div id="ref-usage">
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">get_AMR_locale</span><span class="op">(</span><span class="op">)</span></code></pre></div>
- </div>
-
- <div id="details">
- <h2>Details</h2>
- <p>Strings will be translated to foreign languages if they are defined in a local translation file. Additions to this file can be suggested at our repository. The file can be found here: <a href="https://github.com/msberends/AMR/blob/main/data-raw/translations.tsv" class="external-link">https://github.com/msberends/AMR/blob/main/data-raw/translations.tsv</a>. This file will be read by all functions where a translated output can be desired, like all <code><a href="mo_property.html">mo_*</a></code> functions (such as <code><a href="mo_property.html">mo_name()</a></code>, <code><a href="mo_property.html">mo_gramstain()</a></code>, <code><a href="mo_property.html">mo_type()</a></code>, etc.) and <code><a href="ab_property.html">ab_*</a></code> functions (such as <code><a href="ab_property.html">ab_name()</a></code>, <code><a href="ab_property.html">ab_group()</a></code>, etc.).</p>
-<p>Currently supported languages are: Danish, Dutch, English, French, German, Italian, Portuguese, Russian, Spanish and Swedish. All these languages have translations available for all antimicrobial agents and colloquial microorganism names.</p>
-<p>Please suggest your own translations <a href="https://github.com/msberends/AMR/issues/new?title=Translations" class="external-link">by creating a new issue on our repository</a>.</p><div class="section">
-<h3 id="changing-the-default-language">Changing the Default Language<a class="anchor" aria-label="anchor" href="#changing-the-default-language"></a></h3>
-
-
-<p>The system language will be used at default (as returned by <code>Sys.getenv("LANG")</code> or, if <code>LANG</code> is not set, <code><a href="https://rdrr.io/r/base/locales.html" class="external-link">Sys.getlocale()</a></code>), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:</p><ol><li><p>Setting the R option <code>AMR_locale</code>, e.g. by running <code>options(AMR_locale = "de")</code></p></li>
-<li><p>Setting the system variable <code>LANGUAGE</code> or <code>LANG</code>, e.g. by adding <code>LANGUAGE="de_DE.utf8"</code> to your <code>.Renviron</code> file in your home directory</p></li>
-</ol><p>Thus, if the R option <code>AMR_locale</code> is set, the system variables <code>LANGUAGE</code> and <code>LANG</code> will be ignored.</p>
-</div>
-
- </div>
- <div id="stable-lifecycle">
- <h2>Stable Lifecycle</h2>
-
-
-<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
-The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
-<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
- </div>
- <div id="read-more-on-our-website-">
- <h2>Read more on Our Website!</h2>
-
-
-<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
- </div>
-
- <div id="ref-examples">
- <h2>Examples</h2>
- <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># The 'language' argument of below functions</span>
-<span class="co"># will be set automatically to your system language</span>
-<span class="co"># with get_AMR_locale()</span>
-
-<span class="co"># English</span>
-<span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span>
-<span class="co">#> "Coagulase-negative Staphylococcus (CoNS)"</span>
-
-<span class="co"># Danish</span>
-<span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"da"</span><span class="op">)</span>
-<span class="co">#> "Koagulase-negative stafylokokker (KNS)"</span>
-
-<span class="co"># Dutch</span>
-<span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"nl"</span><span class="op">)</span>
-<span class="co">#> "Coagulase-negatieve Staphylococcus (CNS)"</span>
-
-<span class="co"># German</span>
-<span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"de"</span><span class="op">)</span>
-<span class="co">#> "Koagulase-negative Staphylococcus (KNS)"</span>
-
-<span class="co"># Italian</span>
-<span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"it"</span><span class="op">)</span>
-<span class="co">#> "Staphylococcus negativo coagulasi (CoNS)"</span>
-
-<span class="co"># Portuguese</span>
-<span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"pt"</span><span class="op">)</span>
-<span class="co">#> "Staphylococcus coagulase negativo (CoNS)"</span>
-
-<span class="co"># Spanish</span>
-<span class="fu"><a href="mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span>
-<span class="co">#> "Staphylococcus coagulasa negativo (SCN)"</span>
-</code></pre></div>
- </div>
- </div>
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- </button>
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- <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">1.8.1.9014</span>
- </span>
- </div>
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- <span class="fa fa-dice"></span>
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- Predict antimicrobial resistance
- </a>
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- Data sets for download / own use
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- </a>
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- Work with WHONET data
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diff --git a/docs/whonet.png b/docs/whonet.png
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diff --git a/git_development.sh b/git_development.sh
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+++ /dev/null
@@ -1,200 +0,0 @@
-# ==================================================================== #
-# TITLE #
-# Antimicrobial Resistance (AMR) Data Analysis for R #
-# #
-# SOURCE #
-# https://github.com/msberends/AMR #
-# #
-# LICENCE #
-# (c) 2018-2022 Berends MS, Luz CF et al. #
-# Developed at the University of Groningen, the Netherlands, in #
-# collaboration with non-profit organisations Certe Medical #
-# Diagnostics & Advice, and University Medical Center Groningen. #
-# #
-# This R package is free software; you can freely use and distribute #
-# it for both personal and commercial purposes under the terms of the #
-# GNU General Public License version 2.0 (GNU GPL-2), as published by #
-# the Free Software Foundation. #
-# We created this package for both routine data analysis and academic #
-# research and it was publicly released in the hope that it will be #
-# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
-# #
-# Visit our website for the full manual and a complete tutorial about #
-# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
-# ==================================================================== #
-
-########################################################################
-# `git_development.sh` takes 3 parameters: #
-# 1. Commit message (character) [mandatory] #
-# 2. Lazy website generation (logical), with TRUE only changed #
-# files will be processed [defaults to TRUE] #
-# 3. Version number to be used in DESCRIPTION and NEWS.md #
-# [defaults to current tag and last commit number + 9000] #
-# #
-# To push new commits to the development branch, run: #
-# bash git_development.sh "commit message" #
-# This creates auto version numbering in DESCRIPTION and NEWS.md. #
-# #
-# After successful test checks, merge it to the main branch with: #
-# bash git_merge.sh #
-# #
-# To prerelease a new version number, run: #
-# bash git_development.sh "v1.x.x" FALSE "1.x.x" #
-# #
-# To only update the website, run: #
-# bash git_siteonly.sh #
-# (which is short for 'bash git_development.sh "website update" FALSE')#
-########################################################################
-
-if [ -z "$1" ]; then
- echo "FATAL - no commit message"
- exit 1
-fi
-if [ -z "$2" ]; then
- lazy="TRUE"
-else
- lazy=$2
-fi
-
-# be sure to be on development branch
-git checkout development --quiet
-
-echo "••••••••••••••••••••••••••••••••••••••••••••"
-echo "• Updating package date and version number •"
-echo "••••••••••••••••••••••••••••••••••••••••••••"
-sed -i -- "s/^Date: .*/Date: $(date '+%Y-%m-%d')/" DESCRIPTION
-if [ -z "$3" ]; then
- # no version number set, so get latest tags to create it
- git pull --tags --quiet
- current_tag=`git describe --tags --abbrev=0 | sed 's/v//'`
- if [ -z "current_tag" ]; then
- echo "FATAL - could not determine current tag"
- exit 1
- fi
- current_tag_full=`git describe --tags | sed 's/v//'`
- current_tag_dashes=`echo $current_tag_full | grep -o "[-]" | wc -l`
- if (( "$current_tag_dashes" < 1 )); then
- # so version number is like "1.0.0", commit nr is 0
- current_commit=0
- echo "---------------"
- echo "Mind NEWS.md! Assuming sequence number 9000."
- echo "---------------"
- else
- current_commit=`git describe --tags | sed 's/.*-\(.*\)-.*/\1/'`
- fi
- if [ -z "current_commit" ]; then
- echo "FATAL - could not determine last commit index number"
- exit 1
- fi
- # combine tag (e.g. 0.1.0) and commit number (like 40) increased by 9000 to indicate beta version
- new_version="$current_tag.$((current_commit + 9000))" # results in 0.1.0.9040
- # add date to 2nd line of NEWS.md when no version number was set
- sed -i -- "2s/.*/## \<small\>Last updated: $(date '+%e %B %Y')\<\/small\>/" NEWS.md
-else
- # version number set in command
- new_version=$3
- # rmove 2nd line of NEWS.md (the last changed date)
- sed -i -- "2s/.*//" NEWS.md
- echo "Run devtools::release() or devtools::submit_cran() after this script. Non-interactive mode will not work."
-fi
-# set version number to DESCRIPTION and NEWS files
-sed -i -- "s/^Version: .*/Version: ${new_version}/" DESCRIPTION
-sed -i -- "1s/.*/# \`AMR\` ${new_version}/" NEWS.md
-rm *-- || true
-echo "• First 3 lines of DESCRIPTION:"
-head -3 DESCRIPTION
-echo
-echo "• First 2 lines of NEWS.md:"
-head -2 NEWS.md
-
-echo
-echo "R library location:" $(Rscript -e "cat(.libPaths()[1])")
-echo "•••••••••••••••••••••••••••••••••"
-echo "• Reloading/documenting package •"
-echo "•••••••••••••••••••••••••••••••••"
-Rscript -e "devtools::load_all(quiet = TRUE)"
-echo "• Documenting..."
-Rscript -e "suppressMessages(devtools::document())"
-
-echo
-echo "••••••••••••••••••••••••••"
-echo "• Updating internal data •"
-echo "••••••••••••••••••••••••••"
-Rscript -e "source('data-raw/_internals.R')"
-
-echo
-echo "••••••••••••••••••••"
-echo "• Building package •"
-echo "••••••••••••••••••••"
-echo "• Building 'data-raw/AMR_latest.tar.gz'..."
-Rscript -e "x <- devtools::build(path = 'data-raw', vignettes = TRUE, manual = FALSE, binary = FALSE, quiet = TRUE)"
-rm data-raw/AMR_latest.tar.gz
-mv data-raw/AMR_*.tar.gz data-raw/AMR_latest.tar.gz
-
-# echo "• Installing..."
-# Rscript -e "devtools::install(quiet = TRUE, dependencies = FALSE)"
-
-echo
-echo "•••••••••••••••••"
-echo "• Building site •"
-echo "•••••••••••••••••"
-if [ $lazy == "FALSE" ]; then
- Rscript -e "devtools::install(quiet = TRUE, dependencies = FALSE)"
- Rscript -e "suppressMessages(pkgdown::build_site(lazy = FALSE, examples = FALSE, install = FALSE))"
-else
- # always build home page
- Rscript -e "pkgdown::build_home()"
- if ! git diff --quiet man; then
- # documentation has changed
- Rscript -e "pkgdown::build_reference(lazy = $lazy, examples = FALSE)"
- fi
- if ! git diff --quiet NEWS.md; then
- # news has changed
- Rscript -e "pkgdown::build_news()"
- fi
- if ! git diff --quiet pkgdown; then
- # something has changed in pkgdown files
- Rscript -e "suppressMessages(pkgdown::build_site(lazy = $lazy, examples = FALSE, install = TRUE))"
- fi
- if ! git diff --quiet vignettes; then
- # a vignette has changed
- Rscript -e "devtools::install(quiet = TRUE, dependencies = FALSE)"
- Rscript -e "pkgdown::build_articles(lazy = $lazy)"
- fi
-fi
-# always rebuild datasets vignette
-Rscript -e "pkgdown::build_article('datasets', lazy = FALSE, quiet = TRUE)"
-# add the survey page
-Rscript -e "source('data-raw/create_survey_page.R')"
-
-echo
-echo "•••••••••••••••••••••••••"
-echo "• List of changed files •"
-echo "•••••••••••••••••••••••••"
-git add .
-git status --short
-
-echo
-read -p "Uploading v${new_version} '$1'. Continue (Y/n)? " choice
-case "$choice" in
- n|N ) exit 1;;
- * ) ;;
-esac
-
-echo
-echo "•••••••••••••••••••••••••••"
-echo "• Uploading to repository •"
-echo "•••••••••••••••••••••••••••"
-# save latest changes as well
-git add .
-# and commit
-git commit -a -m "(v${new_version}) $1" --quiet
-git push --quiet
-echo "Comparison:"
-echo "https://github.com/msberends/AMR/compare/main...development?view=inline"
-
-echo
-echo "•••••••••"
-echo "• Done •"
-echo "••••••••"
-echo
diff --git a/git_merge.sh b/git_merge.sh
deleted file mode 100755
index f871a78f1..000000000
--- a/git_merge.sh
+++ /dev/null
@@ -1,78 +0,0 @@
-# ==================================================================== #
-# TITLE #
-# Antimicrobial Resistance (AMR) Data Analysis for R #
-# #
-# SOURCE #
-# https://github.com/msberends/AMR #
-# #
-# LICENCE #
-# (c) 2018-2022 Berends MS, Luz CF et al. #
-# Developed at the University of Groningen, the Netherlands, in #
-# collaboration with non-profit organisations Certe Medical #
-# Diagnostics & Advice, and University Medical Center Groningen. #
-# #
-# This R package is free software; you can freely use and distribute #
-# it for both personal and commercial purposes under the terms of the #
-# GNU General Public License version 2.0 (GNU GPL-2), as published by #
-# the Free Software Foundation. #
-# We created this package for both routine data analysis and academic #
-# research and it was publicly released in the hope that it will be #
-# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
-# #
-# Visit our website for the full manual and a complete tutorial about #
-# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
-# ==================================================================== #
-
-########################################################################
-# `git_development.sh` takes 3 parameters: #
-# 1. Commit message (character) [mandatory] #
-# 2. Lazy website generation (logical), with TRUE only changed #
-# files will be processed [defaults to TRUE] #
-# 3. Version number to be used in DESCRIPTION and NEWS.md #
-# [defaults to current tag and last commit number + 9000] #
-# #
-# To push new commits to the development branch, run: #
-# bash git_development.sh "commit message" #
-# This creates auto version numbering in DESCRIPTION and NEWS.md. #
-# #
-# After successful test checks, merge it to the main branch with: #
-# bash git_merge.sh #
-# #
-# To prerelease a new version number, run: #
-# bash git_development.sh "v1.x.x" FALSE "1.x.x" #
-# #
-# To only update the website, run: #
-# bash git_siteonly.sh #
-# (which is short for 'bash git_development.sh "website update" FALSE')#
-########################################################################
-
-# stash current changes
-# git stash --quiet
-
-# go to main
-git checkout main --quiet
-echo "• changed branch to main"
-
-# import everything from development
-git merge development --quiet
-# and send it to git
-git push --quiet
-echo "• pushed changes to main"
-
-# return to development
-git checkout development --quiet
-echo "• changed branch back to development"
-git status --short
-echo
-
-read -p "Use R-hub to simulate all CRAN checks (y/N)? " choice
-case "$choice" in
- y|Y|j|J ) ;;
- * ) exit 1;;
-esac
-Rscript -e "rhub::check(devtools::build(), platform = rhub::platforms()[!is.na(rhub::platforms()$`cran-name`), 'name'])"
-echo
-
-# and get stashed changes back
-# git stash apply --quiet
-
diff --git a/git_siteonly.sh b/git_siteonly.sh
deleted file mode 100755
index b6e9505d2..000000000
--- a/git_siteonly.sh
+++ /dev/null
@@ -1,58 +0,0 @@
-# ==================================================================== #
-# TITLE #
-# Antimicrobial Resistance (AMR) Data Analysis for R #
-# #
-# SOURCE #
-# https://github.com/msberends/AMR #
-# #
-# LICENCE #
-# (c) 2018-2022 Berends MS, Luz CF et al. #
-# Developed at the University of Groningen, the Netherlands, in #
-# collaboration with non-profit organisations Certe Medical #
-# Diagnostics & Advice, and University Medical Center Groningen. #
-# #
-# This R package is free software; you can freely use and distribute #
-# it for both personal and commercial purposes under the terms of the #
-# GNU General Public License version 2.0 (GNU GPL-2), as published by #
-# the Free Software Foundation. #
-# We created this package for both routine data analysis and academic #
-# research and it was publicly released in the hope that it will be #
-# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
-# #
-# Visit our website for the full manual and a complete tutorial about #
-# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
-# ==================================================================== #
-
-########################################################################
-# `git_development.sh` takes 3 parameters: #
-# 1. Commit message (character) [mandatory] #
-# 2. Lazy website generation (logical), with TRUE only changed #
-# files will be processed [defaults to TRUE] #
-# 3. Version number to be used in DESCRIPTION and NEWS.md #
-# [defaults to current tag and last commit number + 9000] #
-# #
-# To push new commits to the development branch, run: #
-# bash git_development.sh "commit message" #
-# This creates auto version numbering in DESCRIPTION and NEWS.md. #
-# #
-# After successful test checks, merge it to the main branch with: #
-# bash git_merge.sh #
-# #
-# To prerelease a new version number, run: #
-# bash git_development.sh "v1.x.x" FALSE "1.x.x" #
-# #
-# To only update the website, run: #
-# bash git_siteonly.sh #
-# (which is short for 'bash git_development.sh "website update" FALSE')#
-########################################################################
-
-bash git_development.sh "website update" FALSE
-
-echo
-echo "••••••••••••••••••••••••••••"
-echo "• Uploading to main branch •"
-echo "••••••••••••••••••••••••••••"
-git checkout main
-git merge development
-git push --quiet
-git checkout development
diff --git a/index.md b/index.md
index 876dc4d0c..a37b0dd4b 100644
--- a/index.md
+++ b/index.md
@@ -1,27 +1,22 @@
-# `AMR` (for R) <img src="./logo.svg" align="right"/>
+# The `AMR` Package for R <a href="https://msberends.github.io/AMR/"><img src="./logo.svg" align="right" height="139" /></a>
-> Update May 2022: EUCAST 2022 and CLSI 2022 guidelines have been added for `as.rsi()`!
->
-> Updates to the AMR interpretation rules (such as by EUCAST and CLSI), the microbial taxonomy, and the antibiotic dosages will all be updated every 6 to 12 months.
+### Introduction
-### What is `AMR` (for R)?
+The `AMR` package is a [free and open-source](#copyright) R package with [zero dependencies](https://en.wikipedia.org/wiki/Dependency_hell) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. The rationale behind this package was scientifically described in the Journal of Statistical Software (Volume xx, Issue xx; [DOI 10.18637/jss.v000.i00](https://doi.org/10.18637/jss.v000.i00) *- waiting for copy-editing to finish*).
-`AMR` is a free, open-source and independent [R package](https://www.r-project.org) (see [Copyright](#copyright)) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
+After installing this package, R knows [**~71,000 distinct microbial species**](./reference/microorganisms.html) and all [**~570 antibiotic, antimycotic and antiviral drugs**](./reference/antibiotics.html) by name and code (including ATC, WHONET/EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl). This R package formed the basis of two PhD theses ([DOI 10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and [DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)) but is [actively and durably maintained](./news) by two public healthcare organisations in the Netherlands.
-After installing this package, R knows [**~71,000 distinct microbial species**](./reference/microorganisms.html) and all [**~570 antibiotic, antimycotic and antiviral drugs**](./reference/antibiotics.html) by name and code (including ATC, WHONET/EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.
+##### Used in 175 countries, translated to 16 languages
-The `AMR` package is available in <img src="lang_da.svg" style="height: 11px !important; vertical-align: initial !important;"> Danish, <img src="lang_nl.svg" style="height: 11px !important; vertical-align: initial !important;"> Dutch, <img src="lang_en.svg" style="height: 11px !important; vertical-align: initial !important;"> English, <img src="lang_fr.svg" style="height: 11px !important; vertical-align: initial !important;"> French, <img src="lang_de.svg" style="height: 11px !important; vertical-align: initial !important;"> German, <img src="lang_it.svg" style="height: 11px !important; vertical-align: initial !important;"> Italian, <img src="lang_pt.svg" style="height: 11px !important; vertical-align: initial !important;"> Portuguese, <img src="lang_ru.svg" style="height: 11px !important; vertical-align: initial !important;"> Russian, <img src="lang_es.svg" style="height: 11px !important; vertical-align: initial !important;"> Spanish and <img src="lang_sv.svg" style="height: 11px !important; vertical-align: initial !important;"> Swedish. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
+<a href="./countries_large.png"><img src="./countries.png" target="_blank" align="right" style="max-width: 300px;" /></a>
-This package is [fully independent of any other R package](https://en.wikipedia.org/wiki/Dependency_hell) and works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl). This R package formed the basis of two PhD theses ([DOI 10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and [DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)) but is [actively and durably maintained](./news) by two public healthcare organisations in the Netherlands.
+Since its first public release in early 2018, this R package has been used in almost all countries in the world. Click the map to enlarge and to see the country names.
-<div class="main-content" style="display: inline-block;">
- <p>
- <a href="./countries_large.png" target="_blank"><img src="./countries.png" class="countries_map"></a>
- <strong>Used in 175 countries</strong><br>
- Since its first public release in early 2018, this R package has been used in almost all countries in the world. Click the map to enlarge and to see the country names.</p>
-</div>
+The `AMR` package is available in <img src="lang_en.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> English, <img src="lang_zh.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Chinese, <img src="lang_da.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Danish, <img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Dutch, <img src="lang_fr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> French, <img src="lang_de.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> German, <img src="lang_el.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Greek, <img src="lang_it.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Italian, <img src="lang_ja.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Japanese, <img src="lang_pl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Polish, <img src="lang_pt.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Portuguese, <img src="lang_ru.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Russian, <img src="lang_es.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Spanish, <img src="lang_sv.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Swedish, <img src="lang_tr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Turkish, and <img src="lang_uk.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
-##### With `AMR` (for R), there's always a knowledgeable microbiologist by your side!
+### Practical examples
+
+#### Filtering and selecting data
```r
# AMR works great with dplyr, but it's not required or neccesary
@@ -52,7 +47,7 @@ With only having defined a row filter on Gram-negative bacteria with intrinsic r
|*Pseudomonas aeruginosa* | S | S | S | R | | S |
|*Pseudomonas aeruginosa* | S | S | S | R | S | S |
-A base R equivalent would be, giving the exact same results:
+A base R equivalent would be:
```r
example_isolates$bacteria <- mo_fullname(example_isolates$mo)
@@ -61,21 +56,58 @@ example_isolates[which(mo_is_gram_negative() &
c("bacteria", aminoglycosides(), carbapenems())]
```
-#### Partners
+This base R snippet will work in any version of R since April 2013 (R-3.0).
-The development of this package is part of, related to, or made possible by:
+#### Calculating resistance per group
-<div align="center">
- <a href="https://www.rug.nl" title="University of Groningen"><img src="./logo_rug.png" class="partner_logo"></a>
- <a href="https://www.umcg.nl" title="University Medical Center Groningen"><img src="./logo_umcg.png" class="partner_logo"></a>
- <a href="https://www.certe.nl" title="Certe Medical Diagnostics and Advice Foundation"><img src="./logo_certe.png" class="partner_logo"></a>
- <a href="https://www.deutschland-nederland.eu" title="EurHealth-1-Health"><img src="./logo_eh1h.png" class="partner_logo"></a>
- <a href="https://www.deutschland-nederland.eu" title="INTERREG"><img src="./logo_interreg.png" class="partner_logo"></a>
-</div>
+```r
+library(AMR)
+library(dplyr)
-### What can you do with this package?
+out <- example_isolates %>%
+ # group by hospital code:
+ group_by(hospital_id) %>%
+ # calculate AMR using resistance(), over all aminoglycosides
+ # and polymyxins:
+ summarise(across(c(aminoglycosides(), polymyxins()),
+ resistance))
+out
+```
-This package can be used for:
+| hospital_id | GEN | TOB | AMK | KAN | COL |
+|:------------|:-----:|:-----:|:-----:|:-----:|:-----:|
+| A | 0.203 | 0.328 | 0.657 | 1 | 0.853 |
+| B | 0.274 | 0.367 | 0.645 | 1 | 0.845 |
+| C | 0.212 | 0.342 | 0.582 | 1 | 0.865 |
+| D | 0.251 | 0.332 | 0.642 | 1 | 0.745 |
+
+```r
+# transform the antibiotic columns to names:
+out %>% set_ab_names()
+```
+
+| hospital_id | gentamicin | tobramycin | amikacin | kanamycin | colistin |
+|:------------|:----------:|:----------:|:---------|:---------:|:---------:|
+| A | 0.203 | 0.328 | 0.657 | 1 | 0.853 |
+| B | 0.274 | 0.367 | 0.645 | 1 | 0.845 |
+| C | 0.212 | 0.342 | 0.582 | 1 | 0.865 |
+| D | 0.251 | 0.332 | 0.642 | 1 | 0.745 |
+
+```r
+# transform the antibiotic column to ATC codes:
+out %>% set_ab_names(property = "atc")
+```
+
+| hospital_id | J01GB03 | J01GB01 | J01GB06 | J01GB04 | J01XB01 |
+|:------------|:----------:|:----------:|:---------|:---------:|:---------:|
+| A | 0.203 | 0.328 | 0.657 | 1 | 0.853 |
+| B | 0.274 | 0.367 | 0.645 | 1 | 0.845 |
+| C | 0.212 | 0.342 | 0.582 | 1 | 0.865 |
+| D | 0.251 | 0.332 | 0.642 | 1 | 0.745 |
+
+### What else can you do with this package?
+
+This package was intended as a comprehensive toolbox for integrated AMR data analysis. This package can be used for:
* Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the [Catalogue of Life](http://www.catalogueoflife.org) and [List of Prokaryotic names with Standing in Nomenclature](https://lpsn.dsmz.de) ([manual](./reference/mo_property.html))
* Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines ([manual](./reference/as.rsi.html))
@@ -96,7 +128,7 @@ This package can be used for:
### Get this package
-#### Latest released version
+#### Latest official version
[](https://cran.r-project.org/package=AMR)
[](https://cran.r-project.org/package=AMR)
@@ -111,13 +143,14 @@ It will be downloaded and installed automatically. For RStudio, click on the men
**Note:** Not all functions on this website may be available in this latest release. To use all functions and data sets mentioned on this website, install the latest development version.
-
#### Latest development version
[](https://codecov.io/gh/msberends/AMR?branch=main)
[](https://www.codefactor.io/repository/github/msberends/amr)
[](https://codecov.io/gh/msberends/AMR?branch=main)
+Please read our [Developer Guideline here](https://github.com/msberends/AMR/wiki/Developer-Guideline).
+
The latest and unpublished development version can be installed from GitHub in two ways:
1. Manually, using:
@@ -136,66 +169,21 @@ The latest and unpublished development version can be installed from GitHub in t
After this, you can install and update this `AMR` package like any official release (e.g., using `install.packages("AMR")` or in RStudio via *Tools* > *Check for Package Updates...*).
-You can also download the latest build from our repository: <https://github.com/msberends/AMR/raw/main/data-raw/AMR_latest.tar.gz>
-
### Get started
To find out how to conduct AMR data analysis, please [continue reading here to get started](./articles/AMR.html) or click a link in the ['How to' menu](https://msberends.github.io/AMR/articles/).
-### Short introduction
+### Partners
-#### Microbial (taxonomic) reference data
+The development of this package is part of, related to, or made possible by:
-This package contains the complete taxonomic tree of almost all ~71,000 microorganisms from the authoritative and comprehensive Catalogue of Life (CoL, [www.catalogueoflife.org](http://www.catalogueoflife.org)), supplemented by data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, [lpsn.dsmz.de](https://lpsn.dsmz.de)). This supplementation is needed until the [CoL+ project](https://github.com/Sp2000/colplus) is finished, which we await. With `catalogue_of_life_version()` can be checked which version of the CoL is included in this package.
-
-Read more about which data from the Catalogue of Life [in our manual](./reference/catalogue_of_life.html).
-
-#### Antimicrobial reference data
-
-This package contains **all ~570 antibiotic, antimycotic and antiviral drugs** and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD, oral and IV) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, https://www.whocc.no) and the [Pharmaceuticals Community Register of the European Commission](https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm).
-
-**NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See https://www.whocc.no/copyright_disclaimer/.**
-
-Read more about the data from WHOCC [in our manual](./reference/WHOCC.html).
-
-#### WHONET / EARS-Net
-
-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 as 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).
-
-#### Overview of functions
-
-The `AMR` package basically does four important things:
-
-1. It **cleanses existing data** by providing new *classes* 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 intelligent rules to guess results that you would expect:
-
- * Use `as.mo()` to get a microbial ID. The IDs are human readable for the trained eye - the ID of *Klebsiella pneumoniae* is "B_KLBSL_PNMN" (B stands for Bacteria) and the ID of *S. aureus* is "B_STPHY_AURS". 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 intelligent rules combined with the included Catalogue of Life data set. It only takes milliseconds to find results, please see our [benchmarks](./articles/benchmarks.html). Moreover, it can group *Staphylococci* into coagulase negative and positive (CoNS and CoPS, see [source](./reference/as.mo.html#source)) and can categorise *Streptococci* into Lancefield groups (like beta-haemolytic *Streptococcus* Group B, [source](./reference/as.mo.html#source)).
- * Use `as.ab()` to get an antibiotic ID. Like microbial IDs, these IDs are also human readable based on those used by EARS-Net. For example, the ID of amoxicillin is `AMX` and the ID of gentamicin is `GEN`. The `as.ab()` function also uses intelligent rules to find results like accepting misspelling, trade names and abbrevations used in many laboratory systems. For instance, the values "Furabid", "Furadantin", "nitro" all return the ID of Nitrofurantoine. To accomplish this, the package contains a database with most LIS codes, official names, trade names, ATC codes, defined daily doses (DDD) and drug categories of antibiotics.
- * Use `as.rsi()` to get antibiotic interpretations based on raw MIC values (in mg/L) or disk diffusion values (in mm), or transform existing values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like "<=0.002; S" (combined MIC/RSI) will result in "S".
- * Use `as.mic()` to cleanse your MIC values. It produces a so-called factor (called *ordinal* in SPSS) with valid MIC values as levels. A value like "<=0.002; S" (combined MIC/RSI) will result in "<=0.002".
-
-2. It **enhances existing data** and **adds new data** from data sets included in this package.
-
- * Use `eucast_rules()` to apply [EUCAST expert rules to isolates](https://www.eucast.org/expert_rules_and_intrinsic_resistance/) (not the translation from MIC to R/SI values, use `as.rsi()` for that).
- * Use `first_isolate()` to identify the first isolates of every patient [using guidelines from the CLSI](https://clsi.org/standards/products/microbiology/documents/m39/) (Clinical and Laboratory Standards Institute).
- * You can also identify first *weighted* isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them.
- * Use `mdro()` to determine which micro-organisms are multi-drug resistant organisms (MDRO). It supports a variety of international guidelines, such as the MDR-paper by Magiorakos *et al.* (2012, [PMID 21793988](https://www.ncbi.nlm.nih.gov/pubmed/?term=21793988)), the exceptional phenotype definitions of EUCAST and the WHO guideline on multi-drug resistant TB. It also supports the national guidelines of the Netherlands and Germany.
- * The [data set microorganisms](./reference/microorganisms.html) contains the complete taxonomic tree of ~70,000 microorganisms. Furthermore, some colloquial names and all Gram stains 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 `mo_genus()`, `mo_family()`, `mo_gramstain()` or even `mo_phylum()`. Use `mo_snomed()` to look up any SNOMED CT code associated with a microorganism. As all these function use `as.mo()` internally, they also use the same intelligent rules for determination. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. They also come with support for German, Danish, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.
- * The [data set antibiotics](./reference/antibiotics.html) contains ~450 antimicrobial drugs with their EARS-Net code, ATC code, PubChem compound ID, LOINC code, official name, common LIS codes and DDDs of both oral and parenteral administration. It also contains all (thousands of) trade names found in PubChem. Use functions like `ab_name()`, `ab_group()`, `ab_atc()`, `ab_loinc()` and `ab_tradenames()` to look up values. The `ab_*` functions use `as.ab()` internally so they support the same intelligent rules to guess the most probable result. For example, `ab_name("Fluclox")`, `ab_name("Floxapen")` and `ab_name("J01CF05")` will all return `"Flucloxacillin"`. These functions can again be used to add new variables to your data.
-
-3. It **analyses the data** with convenient functions that use well-known methods.
-
- * Calculate the microbial susceptibility or resistance (and even co-resistance) with the `susceptibility()` and `resistance()` functions, or be even more specific with the `proportion_R()`, `proportion_IR()`, `proportion_I()`, `proportion_SI()` and `proportion_S()` functions. Similarly, the *number* of isolates can be determined with the `count_resistant()`, `count_susceptible()` and `count_all()` functions. All these functions can be used with the `dplyr` package (e.g. in conjunction with `summarise()`)
- * Plot AMR results with `geom_rsi()`, a function made for the `ggplot2` package
- * Predict antimicrobial resistance for the nextcoming years using logistic regression models with the `resistance_predict()` function
-
-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.
- * The package also contains example data sets:
- * The [`example_isolates` data set](./reference/example_isolates.html). This data set contains 2,000 microbial isolates with their full antibiograms. It reflects reality and can be used to practice AMR data analysis.
- * 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).
+<div align="center">
+ <a href="https://www.rug.nl" title="University of Groningen"><img src="./logo_rug.png" class="partner_logo"></a>
+ <a href="https://www.umcg.nl" title="University Medical Center Groningen"><img src="./logo_umcg.png" class="partner_logo"></a>
+ <a href="https://www.certe.nl" title="Certe Medical Diagnostics and Advice Foundation"><img src="./logo_certe.png" class="partner_logo"></a>
+ <a href="https://www.deutschland-nederland.eu" title="EurHealth-1-Health"><img src="./logo_eh1h.png" class="partner_logo"></a>
+ <a href="https://www.deutschland-nederland.eu" title="INTERREG"><img src="./logo_interreg.png" class="partner_logo"></a>
+</div>
### Copyright
diff --git a/man/AMR-deprecated.Rd b/man/AMR-deprecated.Rd
index 4a44ffb14..07b8221ed 100644
--- a/man/AMR-deprecated.Rd
+++ b/man/AMR-deprecated.Rd
@@ -6,15 +6,4 @@
\description{
These functions are so-called '\link{Deprecated}'. \strong{They will be removed in a future release.} Using the functions will give a warning with the name of the function it has been replaced by (if there is one).
}
-\section{Retired Lifecycle}{
-
-\if{html}{\figure{lifecycle_retired.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{retired}. A retired function is no longer under active development, and (if appropiate) a better alternative is available. No new arguments will be added, and only the most critical bugs will be fixed. In a future version, this function will be removed.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\keyword{internal}
diff --git a/man/WHOCC.Rd b/man/WHOCC.Rd
index 136fc9ca5..d3610eebd 100644
--- a/man/WHOCC.Rd
+++ b/man/WHOCC.Rd
@@ -18,11 +18,6 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun
\strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.} See \url{https://www.whocc.no/copyright_disclaimer/.}
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
as.ab("meropenem")
ab_name("J01DH02")
diff --git a/man/WHONET.Rd b/man/WHONET.Rd
index 3072cb9c0..87152716b 100644
--- a/man/WHONET.Rd
+++ b/man/WHONET.Rd
@@ -46,9 +46,7 @@ This example data set has the exact same structure as an export file from WHONET
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
+\examples{
+head(WHONET)
}
-
\keyword{datasets}
diff --git a/man/ab_from_text.Rd b/man/ab_from_text.Rd
index 5cf5164d3..f74a909ec 100644
--- a/man/ab_from_text.Rd
+++ b/man/ab_from_text.Rd
@@ -57,19 +57,6 @@ With using \code{collapse}, this function will return a \link{character}:\cr
\code{df \%>\% mutate(abx = ab_from_text(clinical_text, collapse = "|"))}
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# mind the bad spelling of amoxicillin in this line,
# straight from a true health care record:
diff --git a/man/ab_property.Rd b/man/ab_property.Rd
index c83f7875d..36af484ca 100644
--- a/man/ab_property.Rd
+++ b/man/ab_property.Rd
@@ -95,14 +95,6 @@ The function \code{\link[=ab_url]{ab_url()}} will return the direct URL to the o
The function \code{\link[=set_ab_names]{set_ab_names()}} is a special column renaming function for \link{data.frame}s. It renames columns names that resemble antimicrobial drugs. It always makes sure that the new column names are unique. If \code{property = "atc"} is set, preference is given to ATC codes from the J-group.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Source}{
World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/}
@@ -115,11 +107,6 @@ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{htt
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# all properties:
ab_name("AMX") # "Amoxicillin"
@@ -166,15 +153,18 @@ colnames(set_ab_names(example_isolates, NIT:VAN))
\donttest{
if (require("dplyr")) {
example_isolates \%>\%
- set_ab_names()
+ set_ab_names() \%>\%
+ head()
# this does the same:
example_isolates \%>\%
- rename_with(set_ab_names)
+ rename_with(set_ab_names)\%>\%
+ head()
# set_ab_names() works with any AB property:
example_isolates \%>\%
- set_ab_names(property = "atc")
+ set_ab_names(property = "atc")\%>\%
+ head()
example_isolates \%>\%
set_ab_names(where(is.rsi)) \%>\%
diff --git a/man/age.Rd b/man/age.Rd
index 92639fd17..906a563c1 100644
--- a/man/age.Rd
+++ b/man/age.Rd
@@ -21,34 +21,26 @@ age(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...)
An \link{integer} (no decimals) if \code{exact = FALSE}, a \link{double} (with decimals) otherwise
}
\description{
-Calculates age in years based on a reference date, which is the sytem date at default.
+Calculates age in years based on a reference date, which is the system date at default.
}
\details{
Ages below 0 will be returned as \code{NA} with a warning. Ages above 120 will only give a warning.
This function vectorises over both \code{x} and \code{reference}, meaning that either can have a length of 1 while the other argument has a larger length.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
-# 10 random birth dates
-df <- data.frame(birth_date = Sys.Date() - runif(10) * 25000)
+# 10 random pre-Y2K birth dates
+df <- data.frame(birth_date = as.Date("2000-01-01") - runif(10) * 25000)
+
# add ages
df$age <- age(df$birth_date)
+
# add exact ages
df$age_exact <- age(df$birth_date, exact = TRUE)
+# add age at millenium switch
+df$age_at_y2k <- age(df$birth_date, "2000-01-01")
+
df
}
\seealso{
diff --git a/man/age_groups.Rd b/man/age_groups.Rd
index aa976fea9..047cb9f43 100644
--- a/man/age_groups.Rd
+++ b/man/age_groups.Rd
@@ -33,19 +33,6 @@ The default is to split on young children (0-11), youth (12-24), young adults (2
}
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)
@@ -64,7 +51,7 @@ age_groups(ages, 1:20 * 5)
age_groups(ages, split_at = "fives")
# split specifically for children
-age_groups(ages, c(1, 2, 4, 6, 13, 17))
+age_groups(ages, c(1, 2, 4, 6, 13, 18))
age_groups(ages, "children")
\donttest{
@@ -75,7 +62,10 @@ if (require("dplyr")) {
filter(mo == as.mo("E. coli")) \%>\%
group_by(age_group = age_groups(age)) \%>\%
select(age_group, CIP) \%>\%
- ggplot_rsi(x = "age_group", minimum = 0)
+ ggplot_rsi(x = "age_group",
+ minimum = 0,
+ x.title = "Age Group",
+ title = "Ciprofloxacin resistance per age group")
}
}
}
diff --git a/man/antibiotic_class_selectors.Rd b/man/antibiotic_class_selectors.Rd
index 9ff7cff1b..707fba724 100644
--- a/man/antibiotic_class_selectors.Rd
+++ b/man/antibiotic_class_selectors.Rd
@@ -164,120 +164,109 @@ The \code{\link[=not_intrinsic_resistant]{not_intrinsic_resistant()}} function c
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Reference Data Publicly Available}{
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# `example_isolates` is a data set available in the AMR package.
# See ?example_isolates.
+df <- example_isolates[ , c("hospital_id", "mo",
+ "AMP", "AMC", "TZP", "CXM", "CRO", "GEN",
+ "TOB", "COL", "IPM", "MEM", "TEC", "VAN")]
# base R ------------------------------------------------------------------
# select columns 'IPM' (imipenem) and 'MEM' (meropenem)
-example_isolates[, carbapenems()]
+df[, carbapenems()]
# select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
-example_isolates[, c("mo", aminoglycosides())]
+df[, c("mo", aminoglycosides())]
# select only antibiotic columns with DDDs for oral treatment
-example_isolates[, administrable_per_os()]
+df[, administrable_per_os()]
# filter using any() or all()
-example_isolates[any(carbapenems() == "R"), ]
-subset(example_isolates, any(carbapenems() == "R"))
+df[any(carbapenems() == "R"), ]
+subset(df, any(carbapenems() == "R"))
# filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
-example_isolates[any(carbapenems()), ]
-example_isolates[all(carbapenems()), ]
+df[any(carbapenems()), ]
+df[all(carbapenems()), ]
# filter with multiple antibiotic selectors using c()
-example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]
+df[all(c(carbapenems(), aminoglycosides()) == "R"), ]
# filter + select in one go: get penicillins in carbapenems-resistant strains
-example_isolates[any(carbapenems() == "R"), penicillins()]
+df[any(carbapenems() == "R"), penicillins()]
# You can combine selectors with '&' to be more specific. For example,
# penicillins() would select benzylpenicillin ('peni G') and
# administrable_per_os() would select erythromycin. Yet, when combined these
# drugs are both omitted since benzylpenicillin is not administrable per os
# and erythromycin is not a penicillin:
-example_isolates[, penicillins() & administrable_per_os()]
+df[, penicillins() & administrable_per_os()]
# ab_selector() applies a filter in the `antibiotics` data set and is thus very
# flexible. For instance, to select antibiotic columns with an oral DDD of at
# least 1 gram:
-example_isolates[, ab_selector(oral_ddd > 1 & oral_units == "g")]
+df[, ab_selector(oral_ddd > 1 & oral_units == "g")]
# dplyr -------------------------------------------------------------------
\donttest{
if (require("dplyr")) {
# get AMR for all aminoglycosides e.g., per hospital:
- example_isolates \%>\%
+ df \%>\%
group_by(hospital_id) \%>\%
summarise(across(aminoglycosides(), resistance))
# You can combine selectors with '&' to be more specific:
- example_isolates \%>\%
+ df \%>\%
select(penicillins() & administrable_per_os())
# get AMR for only drugs that matter - no intrinsic resistance:
- example_isolates \%>\%
+ df \%>\%
filter(mo_genus() \%in\% c("Escherichia", "Klebsiella")) \%>\%
group_by(hospital_id) \%>\%
summarise(across(not_intrinsic_resistant(), resistance))
# get susceptibility for antibiotics whose name contains "trim":
- example_isolates \%>\%
+ df \%>\%
filter(first_isolate()) \%>\%
group_by(hospital_id) \%>\%
summarise(across(ab_selector(name \%like\% "trim"), susceptibility))
# this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
- example_isolates \%>\%
+ df \%>\%
select(carbapenems())
# this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
- example_isolates \%>\%
+ df \%>\%
select(mo, aminoglycosides())
# any() and all() work in dplyr's filter() too:
- example_isolates \%>\%
+ df \%>\%
filter(any(aminoglycosides() == "R"),
all(cephalosporins_2nd() == "R"))
# also works with c():
- example_isolates \%>\%
+ df \%>\%
filter(any(c(carbapenems(), aminoglycosides()) == "R"))
# not setting any/all will automatically apply all():
- example_isolates \%>\%
+ df \%>\%
filter(aminoglycosides() == "R")
- #> i Assuming a filter on all 4 aminoglycosides.
# this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
- example_isolates \%>\%
+ df \%>\%
select(mo, ab_class("mycobact"))
- # get bug/drug combinations for only macrolides in Gram-positives:
- example_isolates \%>\%
+ # get bug/drug combinations for only glycopeptides in Gram-positives:
+ df \%>\%
filter(mo_is_gram_positive()) \%>\%
- select(mo, macrolides()) \%>\%
+ select(mo, glycopeptides()) \%>\%
bug_drug_combinations() \%>\%
format()
@@ -286,10 +275,12 @@ if (require("dplyr")) {
select(penicillins()) # only the 'J01CA01' column will be selected
- # with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal:
- example_isolates[carbapenems() == "R", ]
- example_isolates \%>\% filter(carbapenems() == "R")
- example_isolates \%>\% filter(across(carbapenems(), ~.x == "R"))
+ # with recent versions of dplyr this is all equal:
+ x <- df[carbapenems() == "R", ]
+ y <- df \%>\% filter(carbapenems() == "R")
+ z <- df \%>\% filter(if_all(carbapenems(), ~.x == "R"))
+ identical(x, y)
+ identical(y, z)
}
}
}
diff --git a/man/antibiotics.Rd b/man/antibiotics.Rd
index 816060f53..5fc10a20d 100644
--- a/man/antibiotics.Rd
+++ b/man/antibiotics.Rd
@@ -90,11 +90,10 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun
\strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.} See \url{https://www.whocc.no/copyright_disclaimer/.}
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
+\examples{
+head(antibiotics)
+head(antivirals)
}
-
\seealso{
\link{microorganisms}, \link{intrinsic_resistant}
}
diff --git a/man/as.ab.Rd b/man/as.ab.Rd
index 1a7f69528..0eb5c663d 100644
--- a/man/as.ab.Rd
+++ b/man/as.ab.Rd
@@ -47,14 +47,6 @@ World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodo
European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{WHOCC}{
\if{html}{\figure{logo_who.png}{options: height="60" style=margin-bottom:"5"} \cr}
@@ -72,11 +64,6 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# these examples all return "ERY", the ID of erythromycin:
as.ab("J01FA01")
diff --git a/man/as.disk.Rd b/man/as.disk.Rd
index d8193ec0a..a0b8852a4 100644
--- a/man/as.disk.Rd
+++ b/man/as.disk.Rd
@@ -33,39 +33,31 @@ Interpret disk values as RSI values with \code{\link[=as.rsi]{as.rsi()}}. It sup
\code{NA_disk_} is a missing value of the new \verb{<disk>} class.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
-\donttest{
-# transform existing disk zones to the `disk` class
-df <- data.frame(microorganism = "E. coli",
+# transform existing disk zones to the `disk` class (using base R)
+df <- data.frame(microorganism = "Escherichia coli",
AMP = 20,
CIP = 14,
GEN = 18,
TOB = 16)
df[, 2:5] <- lapply(df[, 2:5], as.disk)
-# same with dplyr:
-# df \%>\% mutate(across(AMP:TOB, as.disk))
+str(df)
+
+#' \donttest{
+# transforming is easier with dplyr:
+if (require("dplyr")) {
+ df \%>\% mutate(across(AMP:TOB, as.disk))
+}
+}
# interpret disk values, see ?as.rsi
as.rsi(x = as.disk(18),
mo = "Strep pneu", # `mo` will be coerced with as.mo()
ab = "ampicillin", # and `ab` with as.ab()
guideline = "EUCAST")
-
-as.rsi(df)
-}
+
+# interpret whole data set, pretend to be all from urinary tract infections:
+as.rsi(df, uti = TRUE)
}
\seealso{
\code{\link[=as.rsi]{as.rsi()}}
diff --git a/man/as.mic.Rd b/man/as.mic.Rd
index 8d8f3b68d..09c9fc53d 100755
--- a/man/as.mic.Rd
+++ b/man/as.mic.Rd
@@ -77,44 +77,35 @@ Use \code{\link[=droplevels]{droplevels()}} to drop unused levels. At default, i
\code{NA_mic_} is a missing value of the new \verb{<mic>} class, analogous to e.g. base \R's \code{\link[base:NA]{NA_character_}}.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
+mic_data
is.mic(mic_data)
# this can also coerce combined MIC/RSI values:
-as.mic("<=0.002; S") # will return <=0.002
+as.mic("<=0.002; S")
-# mathematical processing treats MICs as [numeric] values
+# mathematical processing treats MICs as numeric values
fivenum(mic_data)
quantile(mic_data)
all(mic_data < 512)
# interpret MIC values
as.rsi(x = as.mic(2),
- mo = as.mo("S. pneumoniae"),
+ mo = as.mo("Streptococcus pneumoniae"),
ab = "AMX",
guideline = "EUCAST")
-as.rsi(x = as.mic(4),
- mo = as.mo("S. pneumoniae"),
+as.rsi(x = as.mic(c(0.01, 2, 4, 8)),
+ mo = as.mo("Streptococcus pneumoniae"),
ab = "AMX",
guideline = "EUCAST")
# plot MIC values, see ?plot
plot(mic_data)
plot(mic_data, mo = "E. coli", ab = "cipro")
+autoplot(mic_data, mo = "E. coli", ab = "cipro")
+autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "nl") # Dutch
+autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "uk") # Ukrainian
}
\seealso{
\code{\link[=as.rsi]{as.rsi()}}
diff --git a/man/as.mo.Rd b/man/as.mo.Rd
index ad582ce8d..512a68649 100644
--- a/man/as.mo.Rd
+++ b/man/as.mo.Rd
@@ -138,14 +138,6 @@ The intelligent rules consider the prevalence of microorganisms in humans groupe
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Matching Score for Microorganisms}{
With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
@@ -184,11 +176,6 @@ This package contains the complete taxonomic tree of almost all microorganisms (
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
\donttest{
# These examples all return "B_STPHY_AURS", the ID of S. aureus:
diff --git a/man/as.rsi.Rd b/man/as.rsi.Rd
index faf6ccb06..ef2ad8068 100755
--- a/man/as.rsi.Rd
+++ b/man/as.rsi.Rd
@@ -154,32 +154,15 @@ A microorganism is categorised as \emph{Susceptible, Increased exposure} when th
This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Reference Data Publicly Available}{
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
+example_isolates
summary(example_isolates) # see all R/SI results at a glance
-\donttest{
-if (require("skimr")) {
- # class <rsi> supported in skim() too:
- skim(example_isolates)
-}
-}
+
# For INTERPRETING disk diffusion and MIC values -----------------------
# a whole data set, even with combined MIC values and disk zones
diff --git a/man/atc_online.Rd b/man/atc_online.Rd
index 208e40664..8fceab112 100644
--- a/man/atc_online.Rd
+++ b/man/atc_online.Rd
@@ -69,19 +69,6 @@ Abbreviations of return values when using \code{property = "U"} (unit):
\strong{N.B. This function requires an internet connection and only works if the following packages are installed: \code{curl}, \code{rvest}, \code{xml2}.}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
\donttest{
if (requireNamespace("curl") && requireNamespace("rvest") && requireNamespace("xml2")) {
diff --git a/man/availability.Rd b/man/availability.Rd
index caaeb92f5..8338b8c43 100644
--- a/man/availability.Rd
+++ b/man/availability.Rd
@@ -20,19 +20,6 @@ Easy check for data availability of all columns in a data set. This makes it eas
\details{
The function returns a \link{data.frame} with columns \code{"resistant"} and \code{"visual_resistance"}. The values in that columns are calculated with \code{\link[=resistance]{resistance()}}.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
availability(example_isolates)
\donttest{
diff --git a/man/bug_drug_combinations.Rd b/man/bug_drug_combinations.Rd
index 16a7be314..44605858c 100644
--- a/man/bug_drug_combinations.Rd
+++ b/man/bug_drug_combinations.Rd
@@ -63,23 +63,10 @@ Determine antimicrobial resistance (AMR) of all bug-drug combinations in your da
\details{
The function \code{\link[=format]{format()}} calculates the resistance per bug-drug combination. Use \code{combine_IR = FALSE} (default) to test R vs. S+I and \code{combine_IR = TRUE} to test R+I vs. S.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
\donttest{
x <- bug_drug_combinations(example_isolates)
-x
+head(x)
format(x, translate_ab = "name (atc)")
# Use FUN to change to transformation of microorganism codes
diff --git a/man/catalogue_of_life.Rd b/man/catalogue_of_life.Rd
index a6f1d49e7..65da2bc1d 100644
--- a/man/catalogue_of_life.Rd
+++ b/man/catalogue_of_life.Rd
@@ -31,11 +31,6 @@ The Catalogue of Life (\url{http://www.catalogueoflife.org}) is the most compreh
The syntax used to transform the original data to a cleansed \R format, can be found here: \url{https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R}.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# Get version info of included data set
catalogue_of_life_version()
@@ -43,28 +38,19 @@ catalogue_of_life_version()
# Get a note when a species was renamed
mo_shortname("Chlamydophila psittaci")
-# Note: 'Chlamydophila psittaci' (Everett et al., 1999) was renamed back to
-# 'Chlamydia psittaci' (Page, 1968)
-#> [1] "C. psittaci"
# Get any property from the entire taxonomic tree for all included species
mo_class("E. coli")
-#> [1] "Gammaproteobacteria"
mo_family("E. coli")
-#> [1] "Enterobacteriaceae"
mo_gramstain("E. coli") # based on kingdom and phylum, see ?mo_gramstain
-#> [1] "Gram-negative"
mo_ref("E. coli")
-#> [1] "Castellani et al., 1919"
# Do not get mistaken - this package is about microorganisms
mo_kingdom("C. elegans")
-#> [1] "Fungi" # Fungi?!
mo_name("C. elegans")
-#> [1] "Cladosporium elegans" # Because a microorganism was found
}
\seealso{
Data set \link{microorganisms} for the actual data. \cr
diff --git a/man/catalogue_of_life_version.Rd b/man/catalogue_of_life_version.Rd
index d56589f5c..9d85322d5 100644
--- a/man/catalogue_of_life_version.Rd
+++ b/man/catalogue_of_life_version.Rd
@@ -23,11 +23,6 @@ This package contains the complete taxonomic tree of almost all microorganisms (
\link[=catalogue_of_life]{Click here} for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with \code{\link[=catalogue_of_life_version]{catalogue_of_life_version()}}.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\seealso{
\link{microorganisms}
}
diff --git a/man/count.Rd b/man/count.Rd
index 1a06e682a..e68a6371a 100644
--- a/man/count.Rd
+++ b/man/count.Rd
@@ -72,14 +72,6 @@ The function \code{\link[=n_rsi]{n_rsi()}} is an alias of \code{\link[=count_all
The function \code{\link[=count_df]{count_df()}} takes any variable from \code{data} that has an \code{\link{rsi}} class (created with \code{\link[=as.rsi]{as.rsi()}}) and counts the number of S's, I's and R's. It also supports grouped variables. The function \code{\link[=rsi_df]{rsi_df()}} works exactly like \code{\link[=count_df]{count_df()}}, but adds the percentage of S, I and R.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Interpretation of R and S/I}{
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
@@ -132,15 +124,11 @@ and that, in combination therapies, for \code{only_all_tested = FALSE} applies t
Using \code{only_all_tested} has no impact when only using one antibiotic as input.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# example_isolates is a data set available in the AMR package.
-?example_isolates
+# run ?example_isolates for more info.
+# base R ------------------------------------------------------------
count_resistant(example_isolates$AMX) # counts "R"
count_susceptible(example_isolates$AMX) # counts "S" and "I"
count_all(example_isolates$AMX) # counts "S", "I" and "R"
@@ -163,6 +151,7 @@ n_rsi(example_isolates$AMX)
count_susceptible(example_isolates$AMX)
susceptibility(example_isolates$AMX) * n_rsi(example_isolates$AMX)
+# dplyr -------------------------------------------------------------
\donttest{
if (require("dplyr")) {
example_isolates \%>\%
diff --git a/man/custom_eucast_rules.Rd b/man/custom_eucast_rules.Rd
index 0bcd9b6cc..294d4fe33 100644
--- a/man/custom_eucast_rules.Rd
+++ b/man/custom_eucast_rules.Rd
@@ -24,51 +24,51 @@ Some organisations have their own adoption of EUCAST rules. This function can be
If you are familiar with the \code{\link[dplyr:case_when]{case_when()}} function of the \code{dplyr} package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written \emph{before} the tilde (\code{~}) and the consequence of the rule is written \emph{after} the tilde:
-\if{html}{\out{<div class="sourceCode">}}\preformatted{x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
+\if{html}{\out{<div class="sourceCode r">}}\preformatted{x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
TZP == "R" ~ aminopenicillins == "R")
}\if{html}{\out{</div>}}
These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:
-\if{html}{\out{<div class="sourceCode">}}\preformatted{x
+\if{html}{\out{<div class="sourceCode r">}}\preformatted{x
#> A set of custom EUCAST rules:
#>
-#> 1. If TZP is S then set to S:
+#> 1. If TZP is "S" then set to S :
#> amoxicillin (AMX), ampicillin (AMP)
#>
-#> 2. If TZP is R then set to R:
+#> 2. If TZP is "R" then set to R :
#> amoxicillin (AMX), ampicillin (AMP)
}\if{html}{\out{</div>}}
The rules (the part \emph{before} the tilde, in above example \code{TZP == "S"} and \code{TZP == "R"}) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column \code{TZP} must exist. We will create a sample data set and test the rules set:
-\if{html}{\out{<div class="sourceCode">}}\preformatted{df <- data.frame(mo = c("E. coli", "K. pneumoniae"),
- TZP = "R",
- amox = "",
- AMP = "")
+\if{html}{\out{<div class="sourceCode r">}}\preformatted{df <- data.frame(mo = c("Escherichia coli", "Klebsiella pneumoniae"),
+ TZP = as.rsi("R"),
+ ampi = as.rsi("S"),
+ cipro = as.rsi("S"))
df
-#> mo TZP amox AMP
-#> 1 E. coli R
-#> 2 K. pneumoniae R
-
-eucast_rules(df, rules = "custom", custom_rules = x)
-#> mo TZP amox AMP
-#> 1 E. coli R R R
-#> 2 K. pneumoniae R R R
+#> mo TZP ampi cipro
+#> 1 Escherichia coli R S S
+#> 2 Klebsiella pneumoniae R S S
+
+eucast_rules(df, rules = "custom", custom_rules = x, info = FALSE)
+#> mo TZP ampi cipro
+#> 1 Escherichia coli R R S
+#> 2 Klebsiella pneumoniae R R S
}\if{html}{\out{</div>}}
}
\subsection{Using taxonomic properties in rules}{
-There is one exception in variables used for the rules: all column names of the \link{microorganisms} data set can also be used, but do not have to exist in the data set. These column names are: mo, fullname, kingdom, phylum, class, order, family, genus, species, subspecies, rank, ref, species_id, source, prevalence and snomed. Thus, this next example will work as well, despite the fact that the \code{df} data set does not contain a column \code{genus}:
+There is one exception in variables used for the rules: all column names of the \link{microorganisms} data set can also be used, but do not have to exist in the data set. These column names are: "mo", "fullname", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "species_id", "source", "prevalence" and "snomed". Thus, this next example will work as well, despite the fact that the \code{df} data set does not contain a column \code{genus}:
-\if{html}{\out{<div class="sourceCode">}}\preformatted{y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
+\if{html}{\out{<div class="sourceCode r">}}\preformatted{y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
TZP == "R" & genus == "Klebsiella" ~ aminopenicillins == "R")
-eucast_rules(df, rules = "custom", custom_rules = y)
-#> mo TZP amox AMP
-#> 1 E. coli R
-#> 2 K. pneumoniae R R R
+eucast_rules(df, rules = "custom", custom_rules = y, info = FALSE)
+#> mo TZP ampi cipro
+#> 1 Escherichia coli R S S
+#> 2 Klebsiella pneumoniae R R S
}\if{html}{\out{</div>}}
}
@@ -76,58 +76,49 @@ eucast_rules(df, rules = "custom", custom_rules = y)
It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part \emph{after} the tilde. In above examples, the antibiotic group \code{aminopenicillins} is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the agents that will be matched when running the rule.
\itemize{
-\item aminoglycosides\cr(amikacin, amikacin/fosfomycin, amphotericin B-high, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin and tobramycin-high)
-\item aminopenicillins\cr(amoxicillin and ampicillin)
-\item antifungals\cr(5-fluorocytosine, amphotericin B, anidulafungin, butoconazole, caspofungin, ciclopirox, clotrimazole, econazole, fluconazole, fosfluconazole, griseofulvin, hachimycin, ibrexafungerp, isavuconazole, isoconazole, itraconazole, ketoconazole, manogepix, micafungin, miconazole, nystatin, pimaricin, posaconazole, rezafungin, ribociclib, sulconazole, terbinafine, terconazole and voriconazole)
-\item antimycobacterials\cr(4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, morinamide, p-aminosalicylic acid, pretomanid, prothionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, simvastatin/fenofibrate, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone/isoniazid, tiocarlide and viomycin)
-\item betalactams\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, biapenem, carbenicillin, carindacillin, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/nacubactam, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, tebipenem, temocillin, ticarcillin and ticarcillin/clavulanic acid)
-\item carbapenems\cr(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil and tebipenem)
-\item cephalosporins\cr(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)
-\item cephalosporins_1st\cr(cefacetrile, cefadroxil, cefaloridine, cefatrizine, cefazedone, cefazolin, cefroxadine, ceftezole, cephalexin, cephalothin, cephapirin and cephradine)
-\item cephalosporins_2nd\cr(cefaclor, cefamandole, cefmetazole, cefonicid, ceforanide, cefotetan, cefotiam, cefoxitin, cefoxitin screening, cefprozil, cefuroxime, cefuroxime axetil and loracarbef)
-\item cephalosporins_3rd\cr(cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefetamet, cefetamet pivoxil, cefixime, cefmenoxime, cefodizime, cefoperazone, cefoperazone/sulbactam, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotiam hexetil, cefovecin, cefpimizole, cefpiramide, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefsulodin, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftriaxone and latamoxef)
-\item cephalosporins_4th\cr(cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetecol, cefoselis, cefozopran, cefpirome and cefquinome)
-\item cephalosporins_5th\cr(ceftaroline, ceftaroline/avibactam, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor and ceftolozane/tazobactam)
-\item cephalosporins_except_caz\cr(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)
-\item fluoroquinolones\cr(besifloxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nifuroquine, norfloxacin, ofloxacin, orbifloxacin, pazufloxacin, pefloxacin, pradofloxacin, premafloxacin, prulifloxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)
-\item glycopeptides\cr(avoparcin, dalbavancin, norvancomycin, oritavancin, ramoplanin, teicoplanin, teicoplanin-macromethod, telavancin, vancomycin and vancomycin-macromethod)
-\item glycopeptides_except_lipo\cr(avoparcin, norvancomycin, ramoplanin, teicoplanin, teicoplanin-macromethod, vancomycin and vancomycin-macromethod)
-\item lincosamides\cr(acetylmidecamycin, acetylspiramycin, clindamycin, gamithromycin, kitasamycin, lincomycin, meleumycin, nafithromycin, pirlimycin, primycin, solithromycin, tildipirosin, tilmicosin, tulathromycin, tylosin and tylvalosin)
-\item lipoglycopeptides\cr(dalbavancin, oritavancin and telavancin)
-\item macrolides\cr(acetylmidecamycin, acetylspiramycin, azithromycin, clarithromycin, dirithromycin, erythromycin, flurithromycin, gamithromycin, josamycin, kitasamycin, meleumycin, midecamycin, miocamycin, nafithromycin, oleandomycin, pirlimycin, primycin, rokitamycin, roxithromycin, solithromycin, spiramycin, telithromycin, tildipirosin, tilmicosin, troleandomycin, tulathromycin, tylosin and tylvalosin)
-\item oxazolidinones\cr(cadazolid, cycloserine, linezolid, tedizolid and thiacetazone)
-\item penicillins\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, carbenicillin, carindacillin, cefepime/nacubactam, ciclacillin, clometocillin, cloxacillin, dicloxacillin, epicillin, flucloxacillin, hetacillin, lenampicillin, mecillinam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, temocillin, ticarcillin and ticarcillin/clavulanic acid)
-\item polymyxins\cr(colistin, polymyxin B and polymyxin B/polysorbate 80)
-\item quinolones\cr(besifloxacin, cinoxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, flumequine, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nalidixic acid, nifuroquine, nitroxoline, norfloxacin, ofloxacin, orbifloxacin, oxolinic acid, pazufloxacin, pefloxacin, pipemidic acid, piromidic acid, pradofloxacin, premafloxacin, prulifloxacin, rosoxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)
-\item streptogramins\cr(pristinamycin and quinupristin/dalfopristin)
-\item tetracyclines\cr(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline, tetracycline and tigecycline)
-\item tetracyclines_except_tgc\cr(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline and tetracycline)
-\item trimethoprims\cr(brodimoprim, sulfadiazine, sulfadiazine/tetroxoprim, sulfadiazine/trimethoprim, sulfadimethoxine, sulfadimidine, sulfadimidine/trimethoprim, sulfafurazole, sulfaisodimidine, sulfalene, sulfamazone, sulfamerazine, sulfamerazine/trimethoprim, sulfamethizole, sulfamethoxazole, sulfamethoxypyridazine, sulfametomidine, sulfametoxydiazine, sulfametrole/trimethoprim, sulfamoxole, sulfamoxole/trimethoprim, sulfanilamide, sulfaperin, sulfaphenazole, sulfapyridine, sulfathiazole, sulfathiourea, trimethoprim and trimethoprim/sulfamethoxazole)
-\item ureidopenicillins\cr(azlocillin, mezlocillin, piperacillin and piperacillin/tazobactam)
+\item "aminoglycosides"\cr(amikacin, amikacin/fosfomycin, amphotericin B-high, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin and tobramycin-high)
+\item "aminopenicillins"\cr(amoxicillin and ampicillin)
+\item "antifungals"\cr(5-fluorocytosine, amphotericin B, anidulafungin, butoconazole, caspofungin, ciclopirox, clotrimazole, econazole, fluconazole, fosfluconazole, griseofulvin, hachimycin, ibrexafungerp, isavuconazole, isoconazole, itraconazole, ketoconazole, manogepix, micafungin, miconazole, nystatin, pimaricin, posaconazole, rezafungin, ribociclib, sulconazole, terbinafine, terconazole and voriconazole)
+\item "antimycobacterials"\cr(4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, morinamide, p-aminosalicylic acid, pretomanid, prothionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, simvastatin/fenofibrate, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone/isoniazid, tiocarlide and viomycin)
+\item "betalactams"\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, biapenem, carbenicillin, carindacillin, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/nacubactam, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, tebipenem, temocillin, ticarcillin and ticarcillin/clavulanic acid)
+\item "carbapenems"\cr(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil and tebipenem)
+\item "cephalosporins"\cr(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)
+\item "cephalosporins_1st"\cr(cefacetrile, cefadroxil, cefaloridine, cefatrizine, cefazedone, cefazolin, cefroxadine, ceftezole, cephalexin, cephalothin, cephapirin and cephradine)
+\item "cephalosporins_2nd"\cr(cefaclor, cefamandole, cefmetazole, cefonicid, ceforanide, cefotetan, cefotiam, cefoxitin, cefoxitin screening, cefprozil, cefuroxime, cefuroxime axetil and loracarbef)
+\item "cephalosporins_3rd"\cr(cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefetamet, cefetamet pivoxil, cefixime, cefmenoxime, cefodizime, cefoperazone, cefoperazone/sulbactam, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotiam hexetil, cefovecin, cefpimizole, cefpiramide, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefsulodin, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftriaxone and latamoxef)
+\item "cephalosporins_4th"\cr(cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetecol, cefoselis, cefozopran, cefpirome and cefquinome)
+\item "cephalosporins_5th"\cr(ceftaroline, ceftaroline/avibactam, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor and ceftolozane/tazobactam)
+\item "cephalosporins_except_caz"\cr(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)
+\item "fluoroquinolones"\cr(besifloxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nifuroquine, norfloxacin, ofloxacin, orbifloxacin, pazufloxacin, pefloxacin, pradofloxacin, premafloxacin, prulifloxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)
+\item "glycopeptides"\cr(avoparcin, dalbavancin, norvancomycin, oritavancin, ramoplanin, teicoplanin, teicoplanin-macromethod, telavancin, vancomycin and vancomycin-macromethod)
+\item "glycopeptides_except_lipo"\cr(avoparcin, norvancomycin, ramoplanin, teicoplanin, teicoplanin-macromethod, vancomycin and vancomycin-macromethod)
+\item "lincosamides"\cr(acetylmidecamycin, acetylspiramycin, clindamycin, gamithromycin, kitasamycin, lincomycin, meleumycin, nafithromycin, pirlimycin, primycin, solithromycin, tildipirosin, tilmicosin, tulathromycin, tylosin and tylvalosin)
+\item "lipoglycopeptides"\cr(dalbavancin, oritavancin and telavancin)
+\item "macrolides"\cr(acetylmidecamycin, acetylspiramycin, azithromycin, clarithromycin, dirithromycin, erythromycin, flurithromycin, gamithromycin, josamycin, kitasamycin, meleumycin, midecamycin, miocamycin, nafithromycin, oleandomycin, pirlimycin, primycin, rokitamycin, roxithromycin, solithromycin, spiramycin, telithromycin, tildipirosin, tilmicosin, troleandomycin, tulathromycin, tylosin and tylvalosin)
+\item "oxazolidinones"\cr(cadazolid, cycloserine, linezolid, tedizolid and thiacetazone)
+\item "penicillins"\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, carbenicillin, carindacillin, cefepime/nacubactam, ciclacillin, clometocillin, cloxacillin, dicloxacillin, epicillin, flucloxacillin, hetacillin, lenampicillin, mecillinam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, temocillin, ticarcillin and ticarcillin/clavulanic acid)
+\item "polymyxins"\cr(colistin, polymyxin B and polymyxin B/polysorbate 80)
+\item "quinolones"\cr(besifloxacin, cinoxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, flumequine, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nalidixic acid, nifuroquine, nitroxoline, norfloxacin, ofloxacin, orbifloxacin, oxolinic acid, pazufloxacin, pefloxacin, pipemidic acid, piromidic acid, pradofloxacin, premafloxacin, prulifloxacin, rosoxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)
+\item "streptogramins"\cr(pristinamycin and quinupristin/dalfopristin)
+\item "tetracyclines"\cr(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline, tetracycline and tigecycline)
+\item "tetracyclines_except_tgc"\cr(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline and tetracycline)
+\item "trimethoprims"\cr(brodimoprim, sulfadiazine, sulfadiazine/tetroxoprim, sulfadiazine/trimethoprim, sulfadimethoxine, sulfadimidine, sulfadimidine/trimethoprim, sulfafurazole, sulfaisodimidine, sulfalene, sulfamazone, sulfamerazine, sulfamerazine/trimethoprim, sulfamethizole, sulfamethoxazole, sulfamethoxypyridazine, sulfametomidine, sulfametoxydiazine, sulfametrole/trimethoprim, sulfamoxole, sulfamoxole/trimethoprim, sulfanilamide, sulfaperin, sulfaphenazole, sulfapyridine, sulfathiazole, sulfathiourea, trimethoprim and trimethoprim/sulfamethoxazole)
+\item "ureidopenicillins"\cr(azlocillin, mezlocillin, piperacillin and piperacillin/tazobactam)
}
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+x
+
+# run the custom rule set (verbose = TRUE will return a logbook instead of the data set):
eucast_rules(example_isolates,
rules = "custom",
custom_rules = x,
- info = FALSE)
+ info = FALSE,
+ verbose = TRUE)
# combine rule sets
x2 <- c(x,
diff --git a/man/dosage.Rd b/man/dosage.Rd
index cf5a3d25f..279545553 100644
--- a/man/dosage.Rd
+++ b/man/dosage.Rd
@@ -32,9 +32,7 @@ EUCAST breakpoints used in this package are based on the dosages in this data se
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
+\examples{
+head(dosage)
}
-
\keyword{datasets}
diff --git a/man/eucast_rules.Rd b/man/eucast_rules.Rd
index fafd15db2..7e1773478 100644
--- a/man/eucast_rules.Rd
+++ b/man/eucast_rules.Rd
@@ -15,6 +15,7 @@ Leclercq et al. \strong{EUCAST expert rules in antimicrobial susceptibility test
\item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_9.0_Breakpoint_Tables.xlsx}{(link)}
\item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 10.0, 2020. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_10.0_Breakpoint_Tables.xlsx}{(link)}
\item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 11.0, 2021. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_11.0_Breakpoint_Tables.xlsx}{(link)}
+\item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 12.0, 2022. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_12.0_Breakpoint_Tables.xlsx}{(link)}
}
}
\usage{
@@ -78,10 +79,31 @@ The file containing all EUCAST rules is located here: \url{https://github.com/ms
Custom rules can be created using \code{\link[=custom_eucast_rules]{custom_eucast_rules()}}, e.g.:
-\if{html}{\out{<div class="sourceCode">}}\preformatted{x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
+\if{html}{\out{<div class="sourceCode r">}}\preformatted{x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
-eucast_rules(example_isolates, rules = "custom", custom_rules = x)
+eucast_rules(example_isolates, rules = "custom", custom_rules = x, info = FALSE)
+#> # A tibble: 2,000 x 49
+#> date hospit~1 ward_~2 ward_~3 ward_~4 age gender patie~5 mo
+#> * <date> <fct> <lgl> <lgl> <lgl> <dbl> <chr> <chr> <mo>
+#> 1 2002-01-02 D FALSE TRUE FALSE 65 F A77334 B_ESCHR_COLI
+#> 2 2002-01-03 D FALSE TRUE FALSE 65 F A77334 B_ESCHR_COLI
+#> 3 2002-01-07 B TRUE FALSE FALSE 45 F 067927 B_STPHY_EPDR
+#> 4 2002-01-07 B TRUE FALSE FALSE 45 F 067927 B_STPHY_EPDR
+#> 5 2002-01-13 B TRUE FALSE FALSE 45 F 067927 B_STPHY_EPDR
+#> 6 2002-01-13 B TRUE FALSE FALSE 45 F 067927 B_STPHY_EPDR
+#> 7 2002-01-14 D FALSE TRUE FALSE 78 M 462729 B_STPHY_AURS
+#> 8 2002-01-14 D FALSE TRUE FALSE 78 M 462729 B_STPHY_AURS
+#> 9 2002-01-16 B TRUE FALSE FALSE 45 F 067927 B_STPHY_EPDR
+#> 10 2002-01-17 B TRUE FALSE FALSE 79 F 858515 B_STPHY_EPDR
+#> # ... with 1,990 more rows, 40 more variables: PEN <rsi>, OXA <rsi>, FLC <rsi>,
+#> # AMX <rsi>, AMC <rsi>, AMP <rsi>, TZP <rsi>, CZO <rsi>, FEP <rsi>,
+#> # CXM <rsi>, FOX <rsi>, CTX <rsi>, CAZ <rsi>, CRO <rsi>, GEN <rsi>,
+#> # TOB <rsi>, AMK <rsi>, KAN <rsi>, TMP <rsi>, SXT <rsi>, NIT <rsi>,
+#> # FOS <rsi>, LNZ <rsi>, CIP <rsi>, MFX <rsi>, VAN <rsi>, TEC <rsi>,
+#> # TCY <rsi>, TGC <rsi>, DOX <rsi>, ERY <rsi>, CLI <rsi>, AZM <rsi>,
+#> # IPM <rsi>, MEM <rsi>, MTR <rsi>, CHL <rsi>, COL <rsi>, MUP <rsi>, ...
+#> # i Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names
}\if{html}{\out{</div>}}
}
@@ -107,24 +129,11 @@ The following antibiotics are eligible for the functions \code{\link[=eucast_rul
Amikacin (\code{AMK}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB06&showdescription=no}{S01AE08}), amoxicillin (\code{AMX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA04&showdescription=no}{J01MA02}), amoxicillin/clavulanic acid (\code{AMC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CR02&showdescription=no}{J01MA23}), ampicillin (\code{AMP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA01&showdescription=no}{J01MA04}), ampicillin/sulbactam (\code{SAM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CR01&showdescription=no}{J01MA08}), arbekacin (\code{ARB}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB12&showdescription=no}{J01MA19}), aspoxicillin (\code{APX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA19&showdescription=no}{J01MA16}), azidocillin (\code{AZD}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE04&showdescription=no}{J01MA15}), azithromycin (\code{AZM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA10&showdescription=no}{J01MA11}), azlocillin (\code{AZL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA09&showdescription=no}{J01MA12}), aztreonam (\code{ATM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DF01&showdescription=no}{J01MA24}), bacampicillin (\code{BAM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA06&showdescription=no}{J01MA07}), bekanamycin (\code{BEK}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB13&showdescription=no}{J01MA14}), benzathine benzylpenicillin (\code{BNB}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE08&showdescription=no}{D10AF05}), benzathine phenoxymethylpenicillin (\code{BNP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE10&showdescription=no}{J01MA06}), benzylpenicillin (\code{PEN}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE01&showdescription=no}{J01MA01}), besifloxacin (\code{BES}, \href{https://www.whocc.no/atc_ddd_index/?code=S01AE08&showdescription=no}{J01MA18}), biapenem (\code{BIA}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DH05&showdescription=no}{J01MA03}), carbenicillin (\code{CRB}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA03&showdescription=no}{J01MA17}), carindacillin (\code{CRN}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA05&showdescription=no}{J01MA10}), cefacetrile (\code{CAC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB10&showdescription=no}{J01MA21}), cefaclor (\code{CEC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC04&showdescription=no}{J01MA09}), cefadroxil (\code{CFR}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB05&showdescription=no}{J01MA05}), cefaloridine (\code{RID}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB02&showdescription=no}{P01AA05}), cefamandole (\code{MAN}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC03&showdescription=no}{J01MA22}), cefatrizine (\code{CTZ}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB07&showdescription=no}{J01MA13}), cefazedone (\code{CZD}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB06&showdescription=no}{J01CA01}), cefazolin (\code{CZO}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB04&showdescription=no}{J01CA04}), cefcapene (\code{CCP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD17&showdescription=no}{J01CA12}), cefdinir (\code{CDR}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD15&showdescription=no}{J01CR05}), cefditoren (\code{DIT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD16&showdescription=no}{J01CA13}), cefepime (\code{FEP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DE01&showdescription=no}{J01AA02}), cefetamet (\code{CAT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD10&showdescription=no}{J01FA10}), cefixime (\code{CFM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD08&showdescription=no}{J01FA09}), cefmenoxime (\code{CMX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD05&showdescription=no}{J01CR02}), cefmetazole (\code{CMZ}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC09&showdescription=no}{J01AA08}), cefodizime (\code{DIZ}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD09&showdescription=no}{J01FA06}), cefonicid (\code{CID}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC06&showdescription=no}{J01CF04}), cefoperazone (\code{CFP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD12&showdescription=no}{J01CF05}), cefoperazone/sulbactam (\code{CSL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD62&showdescription=no}{J01CR01}), ceforanide (\code{CND}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC11&showdescription=no}{J01CA19}), cefotaxime (\code{CTX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD01&showdescription=no}{J01CE04}), cefotetan (\code{CTT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC05&showdescription=no}{J01CA09}), cefotiam (\code{CTF}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC07&showdescription=no}{J01DF01}), cefoxitin (\code{FOX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC01&showdescription=no}{J01CA06}), cefozopran (\code{ZOP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DE03&showdescription=no}{J01CE08}), cefpiramide (\code{CPM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD11&showdescription=no}{J01CE10}), cefpirome (\code{CPO}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DE02&showdescription=no}{J01CE01}), cefpodoxime (\code{CPD}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD13&showdescription=no}{J01CA03}), cefprozil (\code{CPR}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC10&showdescription=no}{J01CA05}), cefroxadine (\code{CRD}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB11&showdescription=no}{J01CE07}), cefsulodin (\code{CFS}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD03&showdescription=no}{J01CF02}), ceftaroline (\code{CPT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DI02&showdescription=no}{J01CF01}), ceftazidime (\code{CAZ}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD02&showdescription=no}{J01CA07}), ceftazidime/clavulanic acid (\code{CCV}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD52&showdescription=no}{J01CA18}), cefteram (\code{CEM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD18&showdescription=no}{J01CA11}), ceftezole (\code{CTL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB12&showdescription=no}{J01CA14}), ceftibuten (\code{CTB}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD14&showdescription=no}{J01CF03}), ceftizoxime (\code{CZX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD07&showdescription=no}{J01CA10}), ceftobiprole medocaril (\code{CFM1}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DI01&showdescription=no}{J01CF06}), ceftolozane/enzyme inhibitor (\code{CEI}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DI54&showdescription=no}{J01CE06}), ceftriaxone (\code{CRO}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD04&showdescription=no}{J01CE05}), cefuroxime (\code{CXM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC02&showdescription=no}{J01CE02}), cephalexin (\code{LEX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB01&showdescription=no}{J01CA02}), cephalothin (\code{CEP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB03&showdescription=no}{J01CA08}), cephapirin (\code{HAP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB08&showdescription=no}{J01CE09}), cephradine (\code{CED}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DB09&showdescription=no}{J01CE03}), chloramphenicol (\code{CHL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01BA01&showdescription=no}{J01CG01}), ciprofloxacin (\code{CIP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA02&showdescription=no}{J01CA16}), clarithromycin (\code{CLR}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA09&showdescription=no}{J01CR04}), clindamycin (\code{CLI}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FF01&showdescription=no}{J01CA15}), clometocillin (\code{CLM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE07&showdescription=no}{J01CG02}), cloxacillin (\code{CLO}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CF02&showdescription=no}{J01CA17}), colistin (\code{COL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XB01&showdescription=no}{J01CR03}), cycloserine (\code{CYC}, \href{https://www.whocc.no/atc_ddd_index/?code=J04AB01&showdescription=no}{J01DB10}), dalbavancin (\code{DAL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XA04&showdescription=no}{J01DC04}), daptomycin (\code{DAP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XX09&showdescription=no}{J01DB05}), delafloxacin (\code{DFX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA23&showdescription=no}{J01DB02}), dibekacin (\code{DKB}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB09&showdescription=no}{J01DC03}), dicloxacillin (\code{DIC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CF01&showdescription=no}{J01DB07}), dirithromycin (\code{DIR}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA13&showdescription=no}{J01DB06}), doripenem (\code{DOR}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DH04&showdescription=no}{J01DB04}), doxycycline (\code{DOX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01AA02&showdescription=no}{J01DD17}), enoxacin (\code{ENX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA04&showdescription=no}{J01DD15}), epicillin (\code{EPC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA07&showdescription=no}{J01DD16}), ertapenem (\code{ETP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DH03&showdescription=no}{J01DE01}), erythromycin (\code{ERY}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA01&showdescription=no}{J01DD10}), fleroxacin (\code{FLE}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA08&showdescription=no}{J01DD08}), flucloxacillin (\code{FLC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CF05&showdescription=no}{J01DD05}), flurithromycin (\code{FLR1}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA14&showdescription=no}{J01DC09}), fosfomycin (\code{FOS}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XX01&showdescription=no}{J01DD09}), framycetin (\code{FRM}, \href{https://www.whocc.no/atc_ddd_index/?code=D09AA01&showdescription=no}{J01DC06}), fusidic acid (\code{FUS}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XC01&showdescription=no}{J01DD12}), garenoxacin (\code{GRN}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA19&showdescription=no}{J01DD62}), gatifloxacin (\code{GAT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA16&showdescription=no}{J01DC11}), gemifloxacin (\code{GEM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA15&showdescription=no}{J01DD01}), gentamicin (\code{GEN}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB03&showdescription=no}{J01DC05}), grepafloxacin (\code{GRX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA11&showdescription=no}{J01DC07}), hetacillin (\code{HET}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA18&showdescription=no}{J01DC01}), imipenem (\code{IPM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DH51&showdescription=no}{J01DE03}), isepamicin (\code{ISE}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB11&showdescription=no}{J01DD11}), josamycin (\code{JOS}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA07&showdescription=no}{J01DE02}), kanamycin (\code{KAN}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB04&showdescription=no}{J01DD13}), latamoxef (\code{LTM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DD06&showdescription=no}{J01DC10}), levofloxacin (\code{LVX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA12&showdescription=no}{J01DB11}), levonadifloxacin (\code{LND}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA24&showdescription=no}{J01DD03}), lincomycin (\code{LIN}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FF02&showdescription=no}{J01DI02}), linezolid (\code{LNZ}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XX08&showdescription=no}{J01DD02}), lomefloxacin (\code{LOM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA07&showdescription=no}{J01DD52}), loracarbef (\code{LOR}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DC08&showdescription=no}{J01DD18}), mecillinam (\code{MEC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA11&showdescription=no}{J01DB12}), meropenem (\code{MEM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DH02&showdescription=no}{J01DD14}), meropenem/vaborbactam (\code{MEV}, \href{https://www.whocc.no/atc_ddd_index/?code=J01DH52&showdescription=no}{J01DD07}), metampicillin (\code{MTM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA14&showdescription=no}{J01DI01}), methicillin (\code{MET}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CF03&showdescription=no}{J01DI54}), mezlocillin (\code{MEZ}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA10&showdescription=no}{J01DD04}), micronomicin (\code{MCR}, \href{https://www.whocc.no/atc_ddd_index/?code=S01AA22&showdescription=no}{J01DC02}), midecamycin (\code{MID}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA03&showdescription=no}{J01DB01}), minocycline (\code{MNO}, \href{https://www.whocc.no/atc_ddd_index/?code=J01AA08&showdescription=no}{J01DB03}), miocamycin (\code{MCM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA11&showdescription=no}{J01DB08}), moxifloxacin (\code{MFX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA14&showdescription=no}{J01DB09}), nadifloxacin (\code{NAD}, \href{https://www.whocc.no/atc_ddd_index/?code=D10AF05&showdescription=no}{J01DD06}), nafcillin (\code{NAF}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CF06&showdescription=no}{J01DC08}), nalidixic acid (\code{NAL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MB02&showdescription=no}{J01DH05}), neomycin (\code{NEO}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB05&showdescription=no}{J01DH04}), netilmicin (\code{NET}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB07&showdescription=no}{J01DH03}), nitrofurantoin (\code{NIT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XE01&showdescription=no}{J01DH51}), norfloxacin (\code{NOR}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA06&showdescription=no}{J01DH02}), ofloxacin (\code{OFX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA01&showdescription=no}{J01DH52}), oleandomycin (\code{OLE}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA05&showdescription=no}{J01XA02}), oritavancin (\code{ORI}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XA05&showdescription=no}{J01XA01}), oxacillin (\code{OXA}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CF04&showdescription=no}{J01XC01}), pazufloxacin (\code{PAZ}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA18&showdescription=no}{J01FA13}), pefloxacin (\code{PEF}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA03&showdescription=no}{J01FA01}), penamecillin (\code{PNM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE06&showdescription=no}{J01FA14}), phenethicillin (\code{PHE}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE05&showdescription=no}{J01FA07}), phenoxymethylpenicillin (\code{PHN}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE02&showdescription=no}{J01FA03}), piperacillin (\code{PIP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA12&showdescription=no}{J01FA11}), piperacillin/tazobactam (\code{TZP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CR05&showdescription=no}{J01FA05}), pivampicillin (\code{PVM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA02&showdescription=no}{J01FA12}), pivmecillinam (\code{PME}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA08&showdescription=no}{J01FA16}), plazomicin (\code{PLZ}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB14&showdescription=no}{J01FA02}), polymyxin B (\code{PLB}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XB02&showdescription=no}{J01FA15}), pristinamycin (\code{PRI}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FG01&showdescription=no}{J01FA08}), procaine benzylpenicillin (\code{PRB}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE09&showdescription=no}{J01FF02}), propicillin (\code{PRP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CE03&showdescription=no}{J01FG01}), prulifloxacin (\code{PRU}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA17&showdescription=no}{J01FG02}), quinupristin/dalfopristin (\code{QDA}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FG02&showdescription=no}{J04AB02}), ribostamycin (\code{RST}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB10&showdescription=no}{J01XX09}), rifampicin (\code{RIF}, \href{https://www.whocc.no/atc_ddd_index/?code=J04AB02&showdescription=no}{J01XX08}), rokitamycin (\code{ROK}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA12&showdescription=no}{J01AA07}), roxithromycin (\code{RXT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA06&showdescription=no}{J01XB01}), rufloxacin (\code{RFL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA10&showdescription=no}{J01XB02}), sisomicin (\code{SIS}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB08&showdescription=no}{J01XE01}), sitafloxacin (\code{SIT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA21&showdescription=no}{J01AA12}), solithromycin (\code{SOL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA16&showdescription=no}{J01EA01}), sparfloxacin (\code{SPX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA09&showdescription=no}{J01XX01}), spiramycin (\code{SPI}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA02&showdescription=no}{J01BA01}), streptoduocin (\code{STR}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GA02&showdescription=no}{J01GB06}), streptomycin (\code{STR1}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GA01&showdescription=no}{J01GB12}), sulbactam (\code{SUL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CG01&showdescription=no}{J01GB13}), sulbenicillin (\code{SBC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA16&showdescription=no}{J01GB09}), sulfadiazine (\code{SDI}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EC02&showdescription=no}{D09AA01}), sulfadiazine/trimethoprim (\code{SLT1}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EE02&showdescription=no}{J01GB03}), sulfadimethoxine (\code{SUD}, \href{https://www.whocc.no/atc_ddd_index/?code=J01ED01&showdescription=no}{J01GB11}), sulfadimidine (\code{SDM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EB03&showdescription=no}{J01GB04}), sulfadimidine/trimethoprim (\code{SLT2}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EE05&showdescription=no}{S01AA22}), sulfafurazole (\code{SLF}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EB05&showdescription=no}{J01GB05}), sulfaisodimidine (\code{SLF1}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EB01&showdescription=no}{J01GB07}), sulfalene (\code{SLF2}, \href{https://www.whocc.no/atc_ddd_index/?code=J01ED02&showdescription=no}{J01GB14}), sulfamazone (\code{SZO}, \href{https://www.whocc.no/atc_ddd_index/?code=J01ED09&showdescription=no}{J01GB10}), sulfamerazine (\code{SLF3}, \href{https://www.whocc.no/atc_ddd_index/?code=J01ED07&showdescription=no}{J01GB08}), sulfamerazine/trimethoprim (\code{SLT3}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EE07&showdescription=no}{J01GA02}), sulfamethizole (\code{SLF4}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EB02&showdescription=no}{J01GA01}), sulfamethoxazole (\code{SMX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EC01&showdescription=no}{J01GB01}), sulfamethoxypyridazine (\code{SLF5}, \href{https://www.whocc.no/atc_ddd_index/?code=J01ED05&showdescription=no}{J01EE01}), sulfametomidine (\code{SLF6}, \href{https://www.whocc.no/atc_ddd_index/?code=J01ED03&showdescription=no}{J01MB02}), sulfametoxydiazine (\code{SLF7}, \href{https://www.whocc.no/atc_ddd_index/?code=J01ED04&showdescription=no}{J01FF01}), sulfametrole/trimethoprim (\code{SLT4}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EE03&showdescription=no}{J01XA04}), sulfamoxole (\code{SLF8}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EC03&showdescription=no}{J01XA05}), sulfamoxole/trimethoprim (\code{SLT5}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EE04&showdescription=no}{J01XA03}), sulfanilamide (\code{SLF9}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EB06&showdescription=no}{J04AB01}), sulfaperin (\code{SLF10}, \href{https://www.whocc.no/atc_ddd_index/?code=J01ED06&showdescription=no}{J01XX11}), sulfaphenazole (\code{SLF11}, \href{https://www.whocc.no/atc_ddd_index/?code=J01ED08&showdescription=no}{J01EC02}), sulfapyridine (\code{SLF12}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EB04&showdescription=no}{J01ED01}), sulfathiazole (\code{SUT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EB07&showdescription=no}{J01EB03}), sulfathiourea (\code{SLF13}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EB08&showdescription=no}{J01EB05}), sultamicillin (\code{SLT6}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CR04&showdescription=no}{J01EB01}), talampicillin (\code{TAL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA15&showdescription=no}{J01ED02}), tazobactam (\code{TAZ}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CG02&showdescription=no}{J01ED09}), tedizolid (\code{TZD}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XX11&showdescription=no}{J01ED07}), teicoplanin (\code{TEC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XA02&showdescription=no}{J01EB02}), telavancin (\code{TLV}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XA03&showdescription=no}{J01EC01}), telithromycin (\code{TLT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA15&showdescription=no}{J01ED05}), temafloxacin (\code{TMX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA05&showdescription=no}{J01ED03}), temocillin (\code{TEM}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA17&showdescription=no}{J01ED04}), tetracycline (\code{TCY}, \href{https://www.whocc.no/atc_ddd_index/?code=J01AA07&showdescription=no}{J01EC03}), ticarcillin (\code{TIC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CA13&showdescription=no}{J01EB06}), ticarcillin/clavulanic acid (\code{TCC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01CR03&showdescription=no}{J01ED06}), tigecycline (\code{TGC}, \href{https://www.whocc.no/atc_ddd_index/?code=J01AA12&showdescription=no}{J01ED08}), tilbroquinol (\code{TBQ}, \href{https://www.whocc.no/atc_ddd_index/?code=P01AA05&showdescription=no}{J01EB04}), tobramycin (\code{TOB}, \href{https://www.whocc.no/atc_ddd_index/?code=J01GB01&showdescription=no}{J01EB07}), tosufloxacin (\code{TFX}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA22&showdescription=no}{J01EB08}), trimethoprim (\code{TMP}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EA01&showdescription=no}{J01EE02}), trimethoprim/sulfamethoxazole (\code{SXT}, \href{https://www.whocc.no/atc_ddd_index/?code=J01EE01&showdescription=no}{J01EE05}), troleandomycin (\code{TRL}, \href{https://www.whocc.no/atc_ddd_index/?code=J01FA08&showdescription=no}{J01EE07}), trovafloxacin (\code{TVA}, \href{https://www.whocc.no/atc_ddd_index/?code=J01MA13&showdescription=no}{J01EE03}), vancomycin (\code{VAN}, \href{https://www.whocc.no/atc_ddd_index/?code=J01XA01&showdescription=no}{J01EE04})
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Reference Data Publicly Available}{
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
\donttest{
a <- data.frame(mo = c("Staphylococcus aureus",
@@ -141,31 +150,24 @@ a <- data.frame(mo = c("Staphylococcus aureus",
FOX = "S", # Cefoxitin
stringsAsFactors = FALSE)
-a
-# mo VAN AMX COL CAZ CXM PEN FOX
-# 1 Staphylococcus aureus - - - - - S S
-# 2 Enterococcus faecalis - - - - - S S
-# 3 Escherichia coli - - - - - S S
-# 4 Klebsiella pneumoniae - - - - - S S
-# 5 Pseudomonas aeruginosa - - - - - S S
+head(a)
# apply EUCAST rules: some results wil be changed
b <- eucast_rules(a)
-b
-# mo VAN AMX COL CAZ CXM PEN FOX
-# 1 Staphylococcus aureus - S R R S S S
-# 2 Enterococcus faecalis - - R R R S R
-# 3 Escherichia coli R - - - - R S
-# 4 Klebsiella pneumoniae R R - - - R S
-# 5 Pseudomonas aeruginosa R R - - R R R
+head(b)
# do not apply EUCAST rules, but rather get a data.frame
# containing all details about the transformations:
c <- eucast_rules(a, verbose = TRUE)
+head(c)
}
+# Dosage guidelines:
+
eucast_dosage(c("tobra", "genta", "cipro"), "iv")
+
+eucast_dosage(c("tobra", "genta", "cipro"), "iv", version_breakpoints = 10)
}
diff --git a/man/example_isolates.Rd b/man/example_isolates.Rd
index 5171c8670..21e1ca374 100644
--- a/man/example_isolates.Rd
+++ b/man/example_isolates.Rd
@@ -30,9 +30,7 @@ A data set containing 2,000 microbial isolates with their full antibiograms. The
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
+\examples{
+head(example_isolates)
}
-
\keyword{datasets}
diff --git a/man/example_isolates_unclean.Rd b/man/example_isolates_unclean.Rd
index ec7c958fd..81071f580 100644
--- a/man/example_isolates_unclean.Rd
+++ b/man/example_isolates_unclean.Rd
@@ -25,9 +25,7 @@ A data set containing 3,000 microbial isolates that are not cleaned up and conse
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
+\examples{
+head(example_isolates_unclean)
}
-
\keyword{datasets}
diff --git a/man/figures/lifecycle_archived.svg b/man/figures/lifecycle_archived.svg
deleted file mode 100644
index 5f27d819d..000000000
--- a/man/figures/lifecycle_archived.svg
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/man/figures/lifecycle_dormant.svg b/man/figures/lifecycle_dormant.svg
deleted file mode 100644
index bd3aa7942..000000000
--- a/man/figures/lifecycle_dormant.svg
+++ /dev/null
@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="112" height="20"><linearGradient id="b" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="a"><rect width="112" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#a)"><path fill="#555" d="M0 0h55v20H0z"/><path fill="#007ec6" d="M55 0h57v20H55z"/><path fill="url(#b)" d="M0 0h112v20H0z"/></g><g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="110"> <text x="285" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="450">lifecycle</text><text x="285" y="140" transform="scale(.1)" textLength="450">lifecycle</text><text x="825" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="470">dormant</text><text x="825" y="140" transform="scale(.1)" textLength="470">dormant</text></g> </svg>
\ No newline at end of file
diff --git a/man/figures/lifecycle_experimental.svg b/man/figures/lifecycle_experimental.svg
deleted file mode 100644
index d43aa63d6..000000000
--- a/man/figures/lifecycle_experimental.svg
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/man/figures/lifecycle_maturing.svg b/man/figures/lifecycle_maturing.svg
deleted file mode 100644
index fb793aced..000000000
--- a/man/figures/lifecycle_maturing.svg
+++ /dev/null
@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="116" height="20"><linearGradient id="b" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="a"><rect width="116" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#a)"><path fill="#555" d="M0 0h55v20H0z"/><path fill="#007ec6" d="M55 0h61v20H55z"/><path fill="url(#b)" d="M0 0h116v20H0z"/></g><g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="110"> <text x="285" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="450">lifecycle</text><text x="285" y="140" transform="scale(.1)" textLength="450">lifecycle</text><text x="845" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="510">maturing</text><text x="845" y="140" transform="scale(.1)" textLength="510">maturing</text></g> </svg>
\ No newline at end of file
diff --git a/man/figures/lifecycle_questioning.svg b/man/figures/lifecycle_questioning.svg
deleted file mode 100644
index 137d4ecdd..000000000
--- a/man/figures/lifecycle_questioning.svg
+++ /dev/null
@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="128" height="20"><linearGradient id="b" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="a"><rect width="128" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#a)"><path fill="#555" d="M0 0h55v20H0z"/><path fill="#007ec6" d="M55 0h73v20H55z"/><path fill="url(#b)" d="M0 0h128v20H0z"/></g><g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="110"> <text x="285" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="450">lifecycle</text><text x="285" y="140" transform="scale(.1)" textLength="450">lifecycle</text><text x="905" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="630">questioning</text><text x="905" y="140" transform="scale(.1)" textLength="630">questioning</text></g> </svg>
\ No newline at end of file
diff --git a/man/figures/lifecycle_retired.svg b/man/figures/lifecycle_retired.svg
deleted file mode 100644
index 33f406b12..000000000
--- a/man/figures/lifecycle_retired.svg
+++ /dev/null
@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="102" height="20"><linearGradient id="b" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="a"><rect width="102" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#a)"><path fill="#555" d="M0 0h55v20H0z"/><path fill="#fe7d37" d="M55 0h47v20H55z"/><path fill="url(#b)" d="M0 0h102v20H0z"/></g><g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="110"> <text x="285" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="450">lifecycle</text><text x="285" y="140" transform="scale(.1)" textLength="450">lifecycle</text><text x="775" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="370">retired</text><text x="775" y="140" transform="scale(.1)" textLength="370">retired</text></g> </svg>
\ No newline at end of file
diff --git a/man/figures/lifecycle_stable.svg b/man/figures/lifecycle_stable.svg
deleted file mode 100644
index be0966740..000000000
--- a/man/figures/lifecycle_stable.svg
+++ /dev/null
@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="98" height="20"><linearGradient id="b" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="a"><rect width="98" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#a)"><path fill="#555" d="M0 0h55v20H0z"/><path fill="#4c1" d="M55 0h43v20H55z"/><path fill="url(#b)" d="M0 0h98v20H0z"/></g><g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="110"> <text x="285" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="450">lifecycle</text><text x="285" y="140" transform="scale(.1)" textLength="450">lifecycle</text><text x="755" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="330">stable</text><text x="755" y="140" transform="scale(.1)" textLength="330">stable</text></g> </svg>
\ No newline at end of file
diff --git a/man/figures/lifecycle_tidyverse.svg b/man/figures/lifecycle_tidyverse.svg
deleted file mode 100644
index 1d8db94f5..000000000
--- a/man/figures/lifecycle_tidyverse.svg
+++ /dev/null
@@ -1,32 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<svg width="510.24pt" height="184.25pt" version="1.1" viewBox="0 0 510.24 184.25" xmlns="http://www.w3.org/2000/svg">
-<style>
- text {
- fill: white;
- font-family: "Helvetica Neue";
- }
-</style>
-<defs>
-<marker id="a" color="black" overflow="visible" markerHeight="6" markerWidth="7" orient="auto" viewBox="-1 -3 7 6">
-<path d="m4.8 0-4.8-1.8v3.6z" fill="currentColor" stroke="currentColor"/>
-</marker>
-</defs>
-<g fill="none">
-<title>Canvas 1</title>
-<rect width="510.24" height="184.25" fill="#fff"/>
-<g>
-<title>Layer 1</title>
-<rect x="5.6693" y="5.6693" width="116.22" height="48.189" fill="#fd8008"/>
-<text transform="translate(63.7793 29.7638)" dominant-baseline="middle" text-anchor="middle">experimental</text>
-<rect x="161.57" y="113.39" width="150.24" height="68.031" fill="#108001"/>
-<text transform="translate(236.69 147.4055)" dominant-baseline="middle" text-anchor="middle" font-size="19">stable</text>
-<path d="m63.356 53.858c2.0388 19.203 10.427 45.968 38.691 65.197 13.679 9.3061 30.217 15.625 46.951 19.9" marker-end="url(#a)" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="2"/>
-<path d="m311.81 131.57c18.392-5.7638 38.128-13.509 56.693-23.85 25.216-14.046 43.275-30.1 55.731-43.973" marker-end="url(#a)" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="2"/>
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-<text transform="translate(447.875 143.1545)" dominant-baseline="middle" text-anchor="middle">superseded</text>
-<line x1="311.81" x2="378.29" y1="147.22" y2="145.23" marker-end="url(#a)" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="2"/>
-<rect x="391.18" y="5.6693" width="113.39" height="48.189" fill="#fd8008"/>
-<text transform="translate(447.875 29.7638)" dominant-baseline="middle" text-anchor="middle">deprecated</text>
-</g>
-</g>
-</svg>
diff --git a/man/first_isolate.Rd b/man/first_isolate.Rd
index 83e073519..e6db158cf 100755
--- a/man/first_isolate.Rd
+++ b/man/first_isolate.Rd
@@ -164,19 +164,6 @@ The default method is phenotype-based (using \code{type = "points"}) and episode
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# `example_isolates` is a data set available in the AMR package.
# See ?example_isolates.
@@ -184,7 +171,7 @@ On our website \url{https://msberends.github.io/AMR/} you can find \href{https:/
example_isolates[first_isolate(), ]
\donttest{
# get all first Gram-negatives
-example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
+example_isolates[which(first_isolate(info = FALSE) & mo_is_gram_negative()), ]
if (require("dplyr")) {
# filter on first isolates using dplyr:
@@ -193,12 +180,13 @@ if (require("dplyr")) {
# short-hand version:
example_isolates \%>\%
- filter_first_isolate()
+ filter_first_isolate(info = FALSE)
- # grouped determination of first isolates (also prints group names):
+ # flag the first isolates per group:
example_isolates \%>\%
group_by(hospital_id) \%>\%
- mutate(first = first_isolate())
+ mutate(first = first_isolate()) \%>\%
+ select(hospital_id, date, patient_id, mo, first)
# now let's see if first isolates matter:
A <- example_isolates \%>\%
@@ -213,6 +201,9 @@ if (require("dplyr")) {
resistance = resistance(GEN)) # gentamicin resistance
# Have a look at A and B.
+ A
+ B
+
# B is more reliable because every isolate is counted only once.
# Gentamicin resistance in hospital D appears to be 4.2\% higher than
# when you (erroneously) would have used all isolates for analysis.
diff --git a/man/g.test.Rd b/man/g.test.Rd
index 886f29ae3..5081cc04f 100644
--- a/man/g.test.Rd
+++ b/man/g.test.Rd
@@ -99,17 +99,6 @@ where \code{df} are the degrees of freedom.
If there are more than two categories and you want to find out which ones are significantly different from their null expectation, you can use the same method of testing each category vs. the sum of all categories, with the Bonferroni correction. You use \emph{G}-tests for each category, of course.
}
}
-\section{Questioning Lifecycle}{
-
-\if{html}{\figure{lifecycle_questioning.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{questioning}. This function might be no longer be optimal approach, or is it questionable whether this function should be in this \code{AMR} package at all.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# = EXAMPLE 1 =
# Shivrain et al. (2006) crossed clearfield rice (which are resistant
@@ -121,8 +110,7 @@ On our website \url{https://msberends.github.io/AMR/} you can find \href{https:/
# ratio.
x <- c(772, 1611, 737)
-G <- g.test(x, p = c(1, 2, 1) / 4)
-# G$p.value = 0.12574.
+g.test(x, p = c(1, 2, 1) / 4)
# There is no significant difference from a 1:2:1 ratio.
# Meaning: resistance controlled by a single gene with two co-dominant
@@ -138,11 +126,9 @@ G <- g.test(x, p = c(1, 2, 1) / 4)
x <- c(1752, 1895)
g.test(x)
-# p = 0.01787343
# There is a significant difference from a 1:1 ratio.
# Meaning: there are significantly more left-billed birds.
-
}
\references{
\enumerate{
diff --git a/man/get_episode.Rd b/man/get_episode.Rd
index 9cf329c4f..3bd0e4e4a 100644
--- a/man/get_episode.Rd
+++ b/man/get_episode.Rd
@@ -32,28 +32,16 @@ The \code{\link[=first_isolate]{first_isolate()}} function is a wrapper around t
The \code{dplyr} package is not required for these functions to work, but these functions do support \link[dplyr:group_by]{variable grouping} and work conveniently inside \code{dplyr} verbs such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# `example_isolates` is a data set available in the AMR package.
-# See ?example_isolates.
+# See ?example_isolates
+df <- example_isolates[sample(seq_len(2000), size = 200), ]
-get_episode(example_isolates$date, episode_days = 60) # indices
-is_new_episode(example_isolates$date, episode_days = 60) # TRUE/FALSE
+get_episode(df$date, episode_days = 60) # indices
+is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
# filter on results from the third 60-day episode only, using base R
-example_isolates[which(get_episode(example_isolates$date, 60) == 3), ]
+df[which(get_episode(df$date, 60) == 3), ]
# the functions also work for less than a day, e.g. to include one per hour:
get_episode(c(Sys.time(),
@@ -64,24 +52,24 @@ get_episode(c(Sys.time(),
if (require("dplyr")) {
# is_new_episode() can also be used in dplyr verbs to determine patient
# episodes based on any (combination of) grouping variables:
- example_isolates \%>\%
+ df \%>\%
mutate(condition = sample(x = c("A", "B", "C"),
size = 2000,
replace = TRUE)) \%>\%
group_by(condition) \%>\%
- mutate(new_episode = is_new_episode(date, 365))
+ mutate(new_episode = is_new_episode(date, 365)) \%>\%
+ select(patient_id, date, condition, new_episode)
- example_isolates \%>\%
+ df \%>\%
group_by(hospital_id, patient_id) \%>\%
transmute(date,
patient_id,
new_index = get_episode(date, 60),
new_logical = is_new_episode(date, 60))
-
- example_isolates \%>\%
+ df \%>\%
group_by(hospital_id) \%>\%
- summarise(patients = n_distinct(patient_id),
+ summarise(n_patients = n_distinct(patient_id),
n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),
n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),
n_episodes_30 = sum(is_new_episode(date, episode_days = 30)))
@@ -89,21 +77,23 @@ if (require("dplyr")) {
# grouping on patients and microorganisms leads to the same
# results as first_isolate() when using 'episode-based':
- x <- example_isolates \%>\%
+ x <- df \%>\%
filter_first_isolate(include_unknown = TRUE,
method = "episode-based")
- y <- example_isolates \%>\%
+ y <- df \%>\%
group_by(patient_id, mo) \%>\%
- filter(is_new_episode(date, 365))
+ filter(is_new_episode(date, 365)) \%>\%
+ ungroup()
- identical(x$patient_id, y$patient_id)
+ identical(x, y)
# but is_new_episode() has a lot more flexibility than first_isolate(),
# since you can now group on anything that seems relevant:
- example_isolates \%>\%
+ df \%>\%
group_by(patient_id, mo, hospital_id, ward_icu) \%>\%
- mutate(flag_episode = is_new_episode(date, 365))
+ mutate(flag_episode = is_new_episode(date, 365)) \%>\%
+ select(group_vars(.), flag_episode)
}
}
}
diff --git a/man/ggplot_pca.Rd b/man/ggplot_pca.Rd
index 08ef13dd5..75fa8aec6 100644
--- a/man/ggplot_pca.Rd
+++ b/man/ggplot_pca.Rd
@@ -108,35 +108,32 @@ Produces a \code{ggplot2} variant of a so-called \href{https://en.wikipedia.org/
\details{
The colours for labels and points can be changed by adding another scale layer for colour, such as \code{scale_colour_viridis_d()} and \code{scale_colour_brewer()}.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\examples{
# `example_isolates` is a data set available in the AMR package.
# See ?example_isolates.
-# See ?pca for more info about Principal Component Analysis (PCA).
\donttest{
if (require("dplyr")) {
- pca_model <- example_isolates \%>\%
- filter(mo_genus(mo) == "Staphylococcus") \%>\%
- group_by(species = mo_shortname(mo)) \%>\%
- summarise_if (is.rsi, resistance) \%>\%
- pca(FLC, AMC, CXM, GEN, TOB, TMP, SXT, CIP, TEC, TCY, ERY)
+ # calculate the resistance per group first
+ resistance_data <- example_isolates \%>\%
+ group_by(order = mo_order(mo), # group on anything, like order
+ genus = mo_genus(mo)) \%>\% # and genus as we do here;
+ filter(n() >= 30) \%>\% # filter on only 30 results per group
+ summarise_if(is.rsi, resistance) # then get resistance of all drugs
- # old (base R)
- biplot(pca_model)
+ # now conduct PCA for certain antimicrobial agents
+ pca_result <- resistance_data \%>\%
+ pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)
+
+ summary(pca_result)
- # new
- ggplot_pca(pca_model)
+ # old base R plotting method:
+ biplot(pca_result)
+ # new ggplot2 plotting method using this package:
+ ggplot_pca(pca_result)
if (require("ggplot2")) {
- ggplot_pca(pca_model) +
+ ggplot_pca(pca_result) +
scale_colour_viridis_d() +
labs(title = "Title here")
}
diff --git a/man/ggplot_rsi.Rd b/man/ggplot_rsi.Rd
index b805696a1..f29e35d1a 100644
--- a/man/ggplot_rsi.Rd
+++ b/man/ggplot_rsi.Rd
@@ -140,19 +140,6 @@ At default, the names of antibiotics will be shown on the plots using \code{\lin
\code{\link[=ggplot_rsi]{ggplot_rsi()}} is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (\verb{\%>\%}). See \emph{Examples}.
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
\donttest{
if (require("ggplot2") & require("dplyr")) {
diff --git a/man/guess_ab_col.Rd b/man/guess_ab_col.Rd
index 9f72be7a9..4f06e966a 100644
--- a/man/guess_ab_col.Rd
+++ b/man/guess_ab_col.Rd
@@ -29,19 +29,6 @@ This tries to find a column name in a data set based on information from the \li
\details{
You can look for an antibiotic (trade) name or abbreviation and it will search \code{x} and the \link{antibiotics} data set for any column containing a name or code of that antibiotic. \strong{Longer columns names take precedence over shorter column names.}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
df <- data.frame(amox = "S",
tetr = "R")
diff --git a/man/intrinsic_resistant.Rd b/man/intrinsic_resistant.Rd
index 6c3e01f79..7dfe72f1b 100644
--- a/man/intrinsic_resistant.Rd
+++ b/man/intrinsic_resistant.Rd
@@ -27,21 +27,7 @@ This data set is based on \href{https://www.eucast.org/expert_rules_and_expected
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
-\donttest{
-if (require("dplyr")) {
- intrinsic_resistant \%>\%
- mutate(mo = mo_name(mo),
- ab = ab_name(mo))
- filter(ab == "Vancomycin" & mo \%like\% "Enterococcus") \%>\%
- pull(mo)
- #> [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"
-}
-}
+head(intrinsic_resistant)
}
\keyword{datasets}
diff --git a/man/italicise_taxonomy.Rd b/man/italicise_taxonomy.Rd
index 9d5ba2a84..b472c43f5 100644
--- a/man/italicise_taxonomy.Rd
+++ b/man/italicise_taxonomy.Rd
@@ -15,7 +15,7 @@ italicize_taxonomy(string, type = c("markdown", "ansi"))
\item{type}{type of conversion of the taxonomic names, either "markdown" or "ansi", see \emph{Details}}
}
\description{
-According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italic. This function finds taxonomic names within strings and makes them italic.
+According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italics. This function finds taxonomic names within strings and makes them italic.
}
\details{
This function finds the taxonomic names and makes them italic based on the \link{microorganisms} data set.
@@ -24,32 +24,9 @@ The taxonomic names can be italicised using markdown (the default) by adding \co
This function also supports abbreviation of the genus if it is followed by a species, such as "E. coli" and "K. pneumoniae ozaenae".
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
italicise_taxonomy("An overview of Staphylococcus aureus isolates")
italicise_taxonomy("An overview of S. aureus isolates")
cat(italicise_taxonomy("An overview of S. aureus isolates", type = "ansi"))
-
-# since ggplot2 supports no markdown (yet), use
-# italicise_taxonomy() and the `ggtext` package for titles:
-\donttest{
-if (require("ggplot2") && require("ggtext")) {
- autoplot(example_isolates$AMC,
- title = italicise_taxonomy("Amoxi/clav in E. coli")) +
- theme(plot.title = ggtext::element_markdown())
-}
-}
}
diff --git a/man/join.Rd b/man/join.Rd
index 3b647791a..6c488a771 100755
--- a/man/join.Rd
+++ b/man/join.Rd
@@ -43,19 +43,6 @@ Join the data set \link{microorganisms} easily to an existing data set or to a \
If the \code{dplyr} package is installed, their join functions will be used. Otherwise, the much slower \code{\link[=merge]{merge()}} and \code{\link[=interaction]{interaction()}} functions from base \R will be used.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
left_join_microorganisms(as.mo("K. pneumoniae"))
left_join_microorganisms("B_KLBSL_PNMN")
diff --git a/man/key_antimicrobials.Rd b/man/key_antimicrobials.Rd
index d74297aab..529fd1954 100644
--- a/man/key_antimicrobials.Rd
+++ b/man/key_antimicrobials.Rd
@@ -107,19 +107,6 @@ The default antimicrobial agents used for \strong{fungi} (set in \code{antifunga
\item Voriconazole
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# `example_isolates` is a data set available in the AMR package.
# See ?example_isolates.
@@ -147,7 +134,7 @@ if (require("dplyr")) {
first_weighted = first_isolate(col_keyantimicrobials = "keyab")
)
- # Check the difference, in this data set it results in more isolates:
+ # Check the difference in this data set, 'weighted' results in more isolates:
sum(my_patients$first_regular, na.rm = TRUE)
sum(my_patients$first_weighted, na.rm = TRUE)
}
diff --git a/man/kurtosis.Rd b/man/kurtosis.Rd
index 08d541464..3dd712165 100644
--- a/man/kurtosis.Rd
+++ b/man/kurtosis.Rd
@@ -25,19 +25,10 @@ kurtosis(x, na.rm = FALSE, excess = FALSE)
\description{
Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. A normal distribution has a kurtosis of 3 and a excess kurtosis of 0.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
+\examples{
+kurtosis(rnorm(10000))
+kurtosis(rnorm(10000), excess = TRUE)
}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\seealso{
\code{\link[=skewness]{skewness()}}
}
diff --git a/man/lifecycle.Rd b/man/lifecycle.Rd
deleted file mode 100644
index 5062077f2..000000000
--- a/man/lifecycle.Rd
+++ /dev/null
@@ -1,43 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/lifecycle.R
-\name{lifecycle}
-\alias{lifecycle}
-\title{Lifecycles of Functions in the \code{AMR} Package}
-\description{
-Functions in this \code{AMR} package are categorised using \href{https://lifecycle.r-lib.org/articles/stages.html}{the lifecycle circle of the Tidyverse as found on www.tidyverse.org/lifecycle}.
-
-\if{html}{\figure{lifecycle_tidyverse.svg}{options: height="200" style=margin-bottom:"5"} \cr}
-This page contains a section for every lifecycle (with text borrowed from the aforementioned Tidyverse website), so they can be used in the manual pages of the functions.
-}
-\section{Experimental Lifecycle}{
-
-\if{html}{\figure{lifecycle_experimental.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{experimental}. An experimental function is in early stages of development. The unlying code might be changing frequently. Experimental functions might be removed without deprecation, so you are generally best off waiting until a function is more mature before you use it in production code. Experimental functions are only available in development versions of this \code{AMR} package and will thus not be included in releases that are submitted to CRAN, since such functions have not yet matured enough.
-}
-
-\section{Maturing Lifecycle}{
-
-\if{html}{\figure{lifecycle_maturing.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome \href{https://github.com/msberends/AMR/issues}{to suggest changes at our repository} or \link[=AMR]{write us an email (see section 'Contact Us')}.
-}
-
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Retired Lifecycle}{
-
-\if{html}{\figure{lifecycle_retired.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{retired}. A retired function is no longer under active development, and (if appropiate) a better alternative is available. No new arguments will be added, and only the most critical bugs will be fixed. In a future version, this function will be removed.
-}
-
-\section{Questioning Lifecycle}{
-
-\if{html}{\figure{lifecycle_questioning.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{questioning}. This function might be no longer be optimal approach, or is it questionable whether this function should be in this \code{AMR} package at all.
-}
-
diff --git a/man/like.Rd b/man/like.Rd
index a6dc2fbbd..306071a95 100755
--- a/man/like.Rd
+++ b/man/like.Rd
@@ -45,39 +45,20 @@ These \code{\link[=like]{like()}} and \verb{\%like\%}/\verb{\%unlike\%} function
Using RStudio? The \verb{\%like\%}/\verb{\%unlike\%} functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like \code{Shift+Ctrl+L} or \code{Shift+Cmd+L} (see menu \code{Tools} > \verb{Modify Keyboard Shortcuts...}). If you keep pressing your shortcut, the inserted text will be iterated over \verb{\%like\%} -> \verb{\%unlike\%} -> \verb{\%like_case\%} -> \verb{\%unlike_case\%}.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
a <- "This is a test"
b <- "TEST"
a \%like\% b
-#> TRUE
b \%like\% a
-#> FALSE
# also supports multiple patterns
a <- c("Test case", "Something different", "Yet another thing")
b <- c( "case", "diff", "yet")
a \%like\% b
-#> TRUE TRUE TRUE
a \%unlike\% b
-#> FALSE FALSE FALSE
a[1] \%like\% b
-#> TRUE FALSE FALSE
a \%like\% b[1]
-#> TRUE FALSE FALSE
# get isolates whose name start with 'Ent' or 'ent'
example_isolates[which(mo_name(example_isolates$mo) \%like\% "^ent"), ]
diff --git a/man/mdro.Rd b/man/mdro.Rd
index 6d4d18025..6c9aed657 100644
--- a/man/mdro.Rd
+++ b/man/mdro.Rd
@@ -163,14 +163,6 @@ table(x)
The rules set (the \code{custom} object in this case) could be exported to a shared file location using \code{\link[=saveRDS]{saveRDS()}} if you collaborate with multiple users. The custom rules set could then be imported using \code{\link[=readRDS]{readRDS()}}.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Antibiotics}{
To define antibiotics column names, leave as it is to determine it automatically with \code{\link[=guess_ab_col]{guess_ab_col()}} or input a text (case-insensitive), or use \code{NULL} to skip a column (e.g. \code{TIC = NULL} to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.
@@ -195,17 +187,15 @@ A microorganism is categorised as \emph{Susceptible, Increased exposure} when th
This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
-mdro(example_isolates, guideline = "EUCAST")
+out <- mdro(example_isolates, guideline = "EUCAST")
+str(out)
+table(out)
-mdro(example_isolates,
- guideline = custom_mdro_guideline(AMX == "R" ~ "Custom MDRO 1",
- VAN == "R" ~ "Custom MDRO 2"))
+out <- mdro(example_isolates,
+ guideline = custom_mdro_guideline(AMX == "R" ~ "Custom MDRO 1",
+ VAN == "R" ~ "Custom MDRO 2"))
+table(out)
\donttest{
if (require("dplyr")) {
@@ -215,10 +205,10 @@ if (require("dplyr")) {
# no need to define `x` when used inside dplyr verbs:
example_isolates \%>\%
- mutate(MDRO = mdro(),
- EUCAST = eucast_exceptional_phenotypes(),
- BRMO = brmo(),
- MRGN = mrgn())
+ mutate(MDRO = mdro()) \%>\%
+ pull(MDRO) \%>\%
+ table()
+
}
}
}
diff --git a/man/microorganisms.Rd b/man/microorganisms.Rd
index 2eca7af11..e1189be41 100755
--- a/man/microorganisms.Rd
+++ b/man/microorganisms.Rd
@@ -90,11 +90,9 @@ This package contains the complete taxonomic tree of almost all microorganisms (
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
+\examples{
+head(microorganisms)
}
-
\seealso{
\code{\link[=as.mo]{as.mo()}}, \code{\link[=mo_property]{mo_property()}}, \link{microorganisms.codes}, \link{intrinsic_resistant}
}
diff --git a/man/microorganisms.codes.Rd b/man/microorganisms.codes.Rd
index 85341cf35..08f81729b 100644
--- a/man/microorganisms.codes.Rd
+++ b/man/microorganisms.codes.Rd
@@ -30,11 +30,9 @@ This package contains the complete taxonomic tree of almost all microorganisms (
\link[=catalogue_of_life]{Click here} for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with \code{\link[=catalogue_of_life_version]{catalogue_of_life_version()}}.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
+\examples{
+head(microorganisms.codes)
}
-
\seealso{
\code{\link[=as.mo]{as.mo()}} \link{microorganisms}
}
diff --git a/man/microorganisms.old.Rd b/man/microorganisms.old.Rd
index f5e991682..c3d4f900f 100644
--- a/man/microorganisms.old.Rd
+++ b/man/microorganisms.old.Rd
@@ -37,11 +37,9 @@ This package contains the complete taxonomic tree of almost all microorganisms (
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
+\examples{
+head(microorganisms.old)
}
-
\seealso{
\code{\link[=as.mo]{as.mo()}} \code{\link[=mo_property]{mo_property()}} \link{microorganisms}
}
diff --git a/man/mo_matching_score.Rd b/man/mo_matching_score.Rd
index ed09b53a0..edc4cb944 100644
--- a/man/mo_matching_score.Rd
+++ b/man/mo_matching_score.Rd
@@ -39,24 +39,11 @@ All matches are sorted descending on their matching score and for all user input
Since \code{AMR} version 1.8.1, common microorganism abbreviations are ignored in determining the matching score. These abbreviations are currently: AIEC, ATEC, BORSA, CRSM, DAEC, EAEC, EHEC, EIEC, EPEC, ETEC, GISA, MRPA, MRSA, MRSE, MSSA, MSSE, NMEC, PISP, PRSP, STEC, UPEC, VISA, VISP, VRE, VRSA and VRSP.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Reference Data Publicly Available}{
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
as.mo("E. coli")
mo_uncertainties()
diff --git a/man/mo_property.Rd b/man/mo_property.Rd
index 335395151..31b5f29ac 100644
--- a/man/mo_property.Rd
+++ b/man/mo_property.Rd
@@ -139,14 +139,6 @@ The function \code{\link[=mo_url]{mo_url()}} will return the direct URL to the o
SNOMED codes - \code{\link[=mo_snomed]{mo_snomed()}} - are from the US Edition of SNOMED CT from 1 September 2020. See \emph{Source} and the \link{microorganisms} data set for more info.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Matching Score for Microorganisms}{
With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
@@ -198,97 +190,91 @@ This package contains the complete taxonomic tree of almost all microorganisms (
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# taxonomic tree -----------------------------------------------------------
-mo_kingdom("E. coli") # "Bacteria"
-mo_phylum("E. coli") # "Proteobacteria"
-mo_class("E. coli") # "Gammaproteobacteria"
-mo_order("E. coli") # "Enterobacterales"
-mo_family("E. coli") # "Enterobacteriaceae"
-mo_genus("E. coli") # "Escherichia"
-mo_species("E. coli") # "coli"
-mo_subspecies("E. coli") # ""
+mo_kingdom("Klebsiella pneumoniae")
+mo_phylum("Klebsiella pneumoniae")
+mo_class("Klebsiella pneumoniae")
+mo_order("Klebsiella pneumoniae")
+mo_family("Klebsiella pneumoniae")
+mo_genus("Klebsiella pneumoniae")
+mo_species("Klebsiella pneumoniae")
+mo_subspecies("Klebsiella pneumoniae")
# colloquial properties ----------------------------------------------------
-mo_name("E. coli") # "Escherichia coli"
-mo_fullname("E. coli") # "Escherichia coli" - same as mo_name()
-mo_shortname("E. coli") # "E. coli"
+mo_name("Klebsiella pneumoniae")
+mo_fullname("Klebsiella pneumoniae")
+mo_shortname("Klebsiella pneumoniae")
# other properties ---------------------------------------------------------
-mo_gramstain("E. coli") # "Gram-negative"
-mo_snomed("E. coli") # 112283007, 116395006, ... (SNOMED codes)
-mo_type("E. coli") # "Bacteria" (equal to kingdom, but may be translated)
-mo_rank("E. coli") # "species"
-mo_url("E. coli") # get the direct url to the online database entry
-mo_synonyms("E. coli") # get previously accepted taxonomic names
+mo_gramstain("Klebsiella pneumoniae")
+mo_snomed("Klebsiella pneumoniae")
+mo_type("Klebsiella pneumoniae")
+mo_rank("Klebsiella pneumoniae")
+mo_url("Klebsiella pneumoniae")
+mo_synonyms("Klebsiella pneumoniae")
# scientific reference -----------------------------------------------------
-mo_ref("E. coli") # "Castellani et al., 1919"
-mo_authors("E. coli") # "Castellani et al."
-mo_year("E. coli") # 1919
-mo_lpsn("E. coli") # 776057 (LPSN record ID)
+mo_ref("Klebsiella pneumoniae")
+mo_authors("Klebsiella pneumoniae")
+mo_year("Klebsiella pneumoniae")
+mo_lpsn("Klebsiella pneumoniae")
# abbreviations known in the field -----------------------------------------
-mo_genus("MRSA") # "Staphylococcus"
-mo_species("MRSA") # "aureus"
-mo_shortname("VISA") # "S. aureus"
-mo_gramstain("VISA") # "Gram-positive"
+mo_genus("MRSA")
+mo_species("MRSA")
+mo_shortname("VISA")
+mo_gramstain("VISA")
-mo_genus("EHEC") # "Escherichia"
-mo_species("EHEC") # "coli"
+mo_genus("EHEC")
+mo_species("EHEC")
# known subspecies ---------------------------------------------------------
-mo_name("doylei") # "Campylobacter jejuni doylei"
-mo_genus("doylei") # "Campylobacter"
-mo_species("doylei") # "jejuni"
-mo_subspecies("doylei") # "doylei"
+mo_name("doylei")
+mo_genus("doylei")
+mo_species("doylei")
+mo_subspecies("doylei")
-mo_fullname("K. pneu rh") # "Klebsiella pneumoniae rhinoscleromatis"
-mo_shortname("K. pneu rh") # "K. pneumoniae"
+mo_fullname("K. pneu rh")
+mo_shortname("K. pneu rh")
\donttest{
# Becker classification, see ?as.mo ----------------------------------------
-mo_fullname("S. epi") # "Staphylococcus epidermidis"
-mo_fullname("S. epi", Becker = TRUE) # "Coagulase-negative Staphylococcus (CoNS)"
-mo_shortname("S. epi") # "S. epidermidis"
-mo_shortname("S. epi", Becker = TRUE) # "CoNS"
+mo_fullname("S. epi")
+mo_fullname("S. epi", Becker = TRUE)
+mo_shortname("S. epi")
+mo_shortname("S. epi", Becker = TRUE)
# Lancefield classification, see ?as.mo ------------------------------------
-mo_fullname("S. pyo") # "Streptococcus pyogenes"
-mo_fullname("S. pyo", Lancefield = TRUE) # "Streptococcus group A"
-mo_shortname("S. pyo") # "S. pyogenes"
-mo_shortname("S. pyo", Lancefield = TRUE) # "GAS" (='Group A Streptococci')
+mo_fullname("S. pyo")
+mo_fullname("S. pyo", Lancefield = TRUE)
+mo_shortname("S. pyo")
+mo_shortname("S. pyo", Lancefield = TRUE)
# language support --------------------------------------------------------
-mo_gramstain("E. coli", language = "de") # "Gramnegativ"
-mo_gramstain("E. coli", language = "nl") # "Gram-negatief"
-mo_gramstain("E. coli", language = "es") # "Gram negativo"
+mo_gramstain("Klebsiella pneumoniae", language = "de")
+mo_gramstain("Klebsiella pneumoniae", language = "nl")
+mo_gramstain("Klebsiella pneumoniae", language = "es")
# mo_type is equal to mo_kingdom, but mo_kingdom will remain official
-mo_kingdom("E. coli") # "Bacteria" on a German system
-mo_type("E. coli") # "Bakterien" on a German system
-mo_type("E. coli") # "Bacteria" on an English system
+mo_kingdom("Klebsiella pneumoniae")
+mo_type("Klebsiella pneumoniae")
+mo_type("Klebsiella pneumoniae")
mo_fullname("S. pyogenes",
Lancefield = TRUE,
- language = "de") # "Streptococcus Gruppe A"
+ language = "de")
mo_fullname("S. pyogenes",
Lancefield = TRUE,
- language = "nl") # "Streptococcus groep A"
+ language = "nl")
# other --------------------------------------------------------------------
-mo_is_yeast(c("Candida", "E. coli")) # TRUE, FALSE
+mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
-# gram stains and intrinsic resistance can also be used as a filter in dplyr verbs
-\donttest{
+# gram stains and intrinsic resistance can be used as a filter in dplyr verbs
if (require("dplyr")) {
example_isolates \%>\%
filter(mo_is_gram_positive())
@@ -299,11 +285,11 @@ if (require("dplyr")) {
# get a list with the complete taxonomy (from kingdom to subspecies)
-mo_taxonomy("E. coli")
+mo_taxonomy("Klebsiella pneumoniae")
+
# get a list with the taxonomy, the authors, Gram-stain,
-# SNOMED codes, and URL to the online database
-mo_info("E. coli")
-}
+# SNOMED codes, and URL to the online database
+mo_info("Klebsiella pneumoniae")
}
}
\seealso{
diff --git a/man/mo_source.Rd b/man/mo_source.Rd
index 74e809720..90f8cc5ef 100644
--- a/man/mo_source.Rd
+++ b/man/mo_source.Rd
@@ -107,16 +107,3 @@ To delete the reference data file, just use \code{""}, \code{NULL} or \code{FALS
If the original file (in the previous case an Excel file) is moved or deleted, the \code{mo_source.rds} file will be removed upon the next use of \code{\link[=as.mo]{as.mo()}} or any \code{\link[=mo_property]{mo_*}} function.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
diff --git a/man/pca.Rd b/man/pca.Rd
index e46118984..b5643f909 100644
--- a/man/pca.Rd
+++ b/man/pca.Rd
@@ -59,19 +59,6 @@ The \code{\link[=pca]{pca()}} function takes a \link{data.frame} as input and pe
The result of the \code{\link[=pca]{pca()}} function is a \link{prcomp} object, with an additional attribute \code{non_numeric_cols} which is a vector with the column names of all columns that do not contain \link{numeric} values. These are probably the groups and labels, and will be used by \code{\link[=ggplot_pca]{ggplot_pca()}}.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# `example_isolates` is a data set available in the AMR package.
# See ?example_isolates.
@@ -82,6 +69,7 @@ if (require("dplyr")) {
resistance_data <- example_isolates \%>\%
group_by(order = mo_order(mo), # group on anything, like order
genus = mo_genus(mo)) \%>\% # and genus as we do here;
+ filter(n() >= 30) \%>\% # filter on only 30 results per group
summarise_if(is.rsi, resistance) # then get resistance of all drugs
# now conduct PCA for certain antimicrobial agents
@@ -90,8 +78,17 @@ if (require("dplyr")) {
pca_result
summary(pca_result)
+
+ # old base R plotting method:
biplot(pca_result)
- ggplot_pca(pca_result) # a new and convenient plot function
+ # new ggplot2 plotting method using this package:
+ ggplot_pca(pca_result)
+
+ if (require("ggplot2")) {
+ ggplot_pca(pca_result) +
+ scale_colour_viridis_d() +
+ labs(title = "Title here")
+ }
}
}
}
diff --git a/man/plot.Rd b/man/plot.Rd
index 3108eead1..3d6c4753a 100644
--- a/man/plot.Rd
+++ b/man/plot.Rd
@@ -130,19 +130,6 @@ For interpreting MIC values as well as disk diffusion diameters, supported guide
Simply using \code{"CLSI"} or \code{"EUCAST"} as input will automatically select the latest version of that guideline.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
some_mic_values <- random_mic(size = 100)
some_disk_values <- random_disk(size = 100, mo = "Escherichia coli", ab = "cipro")
diff --git a/man/proportion.Rd b/man/proportion.Rd
index 7d092a32f..f844b5ac2 100644
--- a/man/proportion.Rd
+++ b/man/proportion.Rd
@@ -124,14 +124,6 @@ and that, in combination therapies, for \code{only_all_tested = FALSE} applies t
Using \code{only_all_tested} has no impact when only using one antibiotic as input.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Interpretation of R and S/I}{
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
@@ -147,15 +139,11 @@ A microorganism is categorised as \emph{Susceptible, Increased exposure} when th
This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# example_isolates is a data set available in the AMR package.
-?example_isolates
+# run ?example_isolates for more info.
+# base R ------------------------------------------------------------
resistance(example_isolates$AMX) # determines \%R
susceptibility(example_isolates$AMX) # determines \%S+I
@@ -166,6 +154,7 @@ proportion_I(example_isolates$AMX)
proportion_IR(example_isolates$AMX)
proportion_R(example_isolates$AMX)
+# dplyr -------------------------------------------------------------
\donttest{
if (require("dplyr")) {
example_isolates \%>\%
@@ -220,10 +209,11 @@ if (require("dplyr")) {
proportion_df(translate = FALSE)
# It also supports grouping variables
+ # (use rsi_df to also include the count)
example_isolates \%>\%
select(hospital_id, AMX, CIP) \%>\%
group_by(hospital_id) \%>\%
- proportion_df(translate = FALSE)
+ rsi_df(translate = FALSE)
}
}
}
diff --git a/man/random.Rd b/man/random.Rd
index d176073b3..46eef6de6 100644
--- a/man/random.Rd
+++ b/man/random.Rd
@@ -35,32 +35,19 @@ The base \R function \code{\link[=sample]{sample()}} is used for generating valu
Generated values are based on the EUCAST 2022 guideline as implemented in the \link{rsi_translation} data set. To create specific generated values per bug or drug, set the \code{mo} and/or \code{ab} argument.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
-random_mic(100)
-random_disk(100)
-random_rsi(100)
+random_mic(25)
+random_disk(25)
+random_rsi(25)
\donttest{
# make the random generation more realistic by setting a bug and/or drug:
-random_mic(100, "Klebsiella pneumoniae") # range 0.0625-64
-random_mic(100, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
-random_mic(100, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
+random_mic(25, "Klebsiella pneumoniae") # range 0.0625-64
+random_mic(25, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
+random_mic(25, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
-random_disk(100, "Klebsiella pneumoniae") # range 8-50
-random_disk(100, "Klebsiella pneumoniae", "ampicillin") # range 11-17
-random_disk(100, "Streptococcus pneumoniae", "ampicillin") # range 12-27
+random_disk(25, "Klebsiella pneumoniae") # range 8-50
+random_disk(25, "Klebsiella pneumoniae", "ampicillin") # range 11-17
+random_disk(25, "Streptococcus pneumoniae", "ampicillin") # range 12-27
}
}
diff --git a/man/resistance_predict.Rd b/man/resistance_predict.Rd
index 952b69652..1951f59c4 100644
--- a/man/resistance_predict.Rd
+++ b/man/resistance_predict.Rd
@@ -110,14 +110,6 @@ Valid options for the statistical model (argument \code{model}) are:
\item \code{"lin"} or \code{"linear"}: a linear regression model
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
\section{Interpretation of R and S/I}{
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
@@ -133,11 +125,6 @@ A microorganism is categorised as \emph{Susceptible, Increased exposure} when th
This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
x <- resistance_predict(example_isolates,
col_ab = "AMX",
@@ -172,24 +159,8 @@ if (require("dplyr") & require("ggplot2")) {
model = "binomial",
info = FALSE,
minimum = 15)
-
+ head(data)
autoplot(data)
-
- ggplot(data,
- aes(x = year)) +
- geom_col(aes(y = value),
- fill = "grey75") +
- geom_errorbar(aes(ymin = se_min,
- ymax = se_max),
- colour = "grey50") +
- scale_y_continuous(limits = c(0, 1),
- breaks = seq(0, 1, 0.1),
- labels = paste0(seq(0, 100, 10), "\%")) +
- labs(title = expression(paste("Forecast of Amoxicillin Resistance in ",
- italic("E. coli"))),
- y = "\%R",
- x = "Year") +
- theme_minimal(base_size = 13)
}
}
}
diff --git a/man/rsi_translation.Rd b/man/rsi_translation.Rd
index 5f54998f7..d67a54a9a 100644
--- a/man/rsi_translation.Rd
+++ b/man/rsi_translation.Rd
@@ -27,25 +27,6 @@ rsi_translation
Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (2011-2022) and CLSI (2011-2022). Use \code{\link[=as.rsi]{as.rsi()}} to transform MICs or disks measurements to R/SI values.
}
\details{
-Overview of the data set:
-
-\if{html}{\out{<div class="sourceCode r">}}\preformatted{head(rsi_translation)
-#> guideline method site mo rank_index ab ref_tbl disk_dose
-#> 1 EUCAST 2022 MIC <NA> F_ASPRG_MGTS 2 AMB Aspergillus <NA>
-#> 2 EUCAST 2022 MIC <NA> F_ASPRG_NIGR 2 AMB Aspergillus <NA>
-#> 3 EUCAST 2022 MIC <NA> F_CANDD 3 AMB Candida <NA>
-#> 4 EUCAST 2022 MIC <NA> F_CANDD_ALBC 2 AMB Candida <NA>
-#> 5 EUCAST 2022 MIC <NA> F_CANDD_DBLN 2 AMB Candida <NA>
-#> 6 EUCAST 2022 MIC <NA> F_CANDD_KRUS 2 AMB Candida <NA>
-#> breakpoint_S breakpoint_R uti
-#> 1 1 1 FALSE
-#> 2 1 1 FALSE
-#> 3 1 1 FALSE
-#> 4 1 1 FALSE
-#> 5 1 1 FALSE
-#> 6 1 1 FALSE
-}\if{html}{\out{</div>}}
-
The repository of this \code{AMR} package contains a file comprising this exact data set: \url{https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt}. This file \strong{allows for machine reading EUCAST and CLSI guidelines}, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically and the \code{mo} and \code{ab} columns have been transformed to contain the full official names instead of codes.
}
\section{Reference Data Publicly Available}{
@@ -53,11 +34,9 @@ The repository of this \code{AMR} package contains a file comprising this exact
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
+\examples{
+head(rsi_translation)
}
-
\seealso{
\link{intrinsic_resistant}
}
diff --git a/man/skewness.Rd b/man/skewness.Rd
index 137f6a45f..125d32ae6 100644
--- a/man/skewness.Rd
+++ b/man/skewness.Rd
@@ -25,19 +25,9 @@ Skewness is a measure of the asymmetry of the probability distribution of a real
When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0.
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
+\examples{
+skewness(runif(1000))
}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\seealso{
\code{\link[=kurtosis]{kurtosis()}}
}
diff --git a/man/translate.Rd b/man/translate.Rd
index 44127050b..e3e470b70 100644
--- a/man/translate.Rd
+++ b/man/translate.Rd
@@ -27,7 +27,7 @@ For language-dependent output of AMR functions, like \code{\link[=mo_name]{mo_na
\details{
The currently 16 supported languages are English, Chinese, Danish, Dutch, French, German, Greek, Italian, Japanese, Polish, Portuguese, Russian, Spanish, Swedish, Turkish and Ukrainian. All these languages have translations available for all antimicrobial agents and colloquial microorganism names.
-Please read about adding or updating a language in \href{https://github.com/msberends/AMR/blob/main/developer-guideline.md}{our developer guideline}.
+Please read about adding or updating a language in \href{https://github.com/msberends/AMR/wiki/}{our Wiki}.
\subsection{Changing the Default Language}{
The system language will be used at default (as returned by \code{Sys.getenv("LANG")} or, if \code{LANG} is not set, \link{Sys.getlocale("LC_COLLATE")}), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:
@@ -41,19 +41,6 @@ Note that setting an \R option only works in the same session. Save the command
Thus, if the R option \code{AMR_locale} is set, the system variables \code{LANGUAGE} and \code{LANG} will be ignored.
}
}
-\section{Stable Lifecycle}{
-
-\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-
-If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-}
-
-\section{Read more on Our Website!}{
-
-On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
\examples{
# Current settings (based on system language)
ab_name("Ciprofloxacin")
diff --git a/pkgdown/extra.css b/pkgdown/extra.css
index ddc0c382a..a812063fd 100644
--- a/pkgdown/extra.css
+++ b/pkgdown/extra.css
@@ -25,293 +25,60 @@
# ==================================================================== #
*/
-/* R for Data Science (r4ds) on vignettes (articles) */
-#r4ds {
- display: flex;
- border-bottom: 1px solid #ddd;
- margin-bottom: 10px;
- padding-bottom: 10px;
+h1, h2 {
+ text-align: left !important;
}
-#r4ds .txt {
- width: 67%;
-}
-#r4ds .img {
- width: 33%;
-}
-#r4ds .img img {
- height: 120px;
-}
-
-/* class for footer */
-.footer_logo {
- float: right;
- height: 43px;
- margin-top: 2px;
-}
-.partner_logo {
- width: 19%;
- min-width: 125px;
-}
-.countries_map {
- float: left;
- padding: 0 10px 10px 0;
- max-width: 35% !important;
-}
-@media only screen and (max-width: 992px) {
- .footer_logo {
- float: left;
- margin-top: 15px;
- }
-}
-footer p {
- display: inline-block;
-}
-footer {
- padding: 15px 0 20px !important;
-}
-
-/* Supports icons for brand using font-awesome */
-.fab {
- font-family: "Font Awesome 5 Brands" !important;
-}
-
-/* Remove the 'Read more on our website!' part from the manual pages */
-#read-more-on-our-website-,
-#read-more-on-our-website- + p,
-li a[href="#read-more-on-our-website-"] {
- display: none !important;
-}
-
-code {
- color: black;
- background-color: #f4f4f4;
-}
-/* make colour darker and better readable for links */
-code a, code a:hover, code a:focus,
-pre a, pre a:hover, pre a:focus,
-a, a:hover, a:focus {
- /* do not set colour to element without href attribute, they aren't links! */
- color: black;
-}
-a[href], a[href]:hover, a[href]:focus,
-code a[href], code a[href]:hover, code a[href]:focus,
-a[href] code, a[href] code:hover, a[href] code:focus,
-pre a[href], pre a[href]:hover, pre a[href]:focus,
-a code[href], a code[href]:hover, a code[href]:focus,
-a pre[href], a pre[href]:hover, a pre[href]:focus {
- /* adjusted colour for all real links; having href attribute */
- color: #128f76;
-}
-
-.ot, .dv, .fl, .cn {
- /* numbers and TRUE/FALSE */
- color: slategray;
-}
-
-/* syntax font */
-pre, code {
- font-size: 95% !important;
-}
-pre code {
- word-wrap: normal !important;
- white-space: pre !important;
-}
-pre {
- font-size: 90% !important;
-}
-kbd {
- display: inline-block;
- padding: 0 4px;
- box-shadow: 1px 1px 1px slategrey;
- margin: 1px;
- font-size: small;
- color: #2c3e50;
- background: #eeeeee;
-}
-
-li, p {
- line-height: 1.5;
-}
-li p {
- margin-top: 10.5px;
-}
-.template-news li p {
- margin: 0;
-}
-.template-news h3 {
- padding-top: 10px;
-}
-
-/* slightly smaller blockquote */
-blockquote {
- font-size: 98%;
-}
-.template-home blockquote {
- border: 5px solid #128f7645 !important;
-}
-
-/* 2nd list in navigation should be smaller */
-#tocnav li li {
- font-size: 90%;
- margin-left: 5px;
-}
-
-/* new <help> element with dotted underline */
-help {
- border-bottom: 1px dotted;
- cursor: help;
-}
-
-/* replace 'Developers' with 'Authors' */
+/* replace 'Developers' with 'Maintainers' */
.developers h2 {
display: none;
}
.developers:before {
content: 'Maintainers';
- font-size: 1.5em;
}
-/* Beautify manually added 'Last updated' text of NEWS */
-div[id^=last-updated] h2 {
- padding-top: 10px;
-}
-.version.label {
- display: none;
-}
+/* SYNTAX */
+/* These are simple changes for the syntax highlighting */
-/* Date of vignettes */
-.template-article .date:before {
- content: 'Last updated: ';
+pre code {
+ /* never wrap code on smaller screens */
+ word-wrap: normal !important;
+ white-space: pre !important;
}
-.template-article .date {
- font-size: 14px;
- padding-top: 40px;
+.ot, .dv, .fl, .cn, .at,
+.op a {
+ /* numbers, TRUE/FALSE and operators */
+ color: var(--bs-dark) !important;
}
-
-/* more space between icon and text in top menu */
-#navbar .fa,
-#navbar .fab,
-#navbar .fal,
-#navbar .far,
-#navbar .fas {
- margin-right: 5px;
+pre .fu, .fu {
+ /* functions */
+ color: var(--bs-primary) !important;
+ font-weight: bold !important;
+ letter-spacing: -1px !important;
}
-#navbar li.dropdown li .fa {
- font-size: 120%;
- width: 24px;
- text-align: center;
+pre .st, .st {
+ /* strings, regular text */
+ color: #60a799 !important;
}
-
-/* tables, make them look like scientific ones */
-.table {
- font-size: 90%;
+pre .co, .co {
+ /* comments */
+ color: #999999 !important;
+ font-style: italic !important;
}
-.table * {
- vertical-align: middle !important;
+code a[href],
+a[href] code,
+pre a[href],
+a code[href],
+a pre[href] {
+ /* adjusted colour for all real links; having href attribute */
+ color: var(--bs-success);
+ text-decoration: none;
}
-.table td {
- padding: 4px !important;
-}
-.table thead,
-.template-reference-topic .table tr:first-child {
- /* tables in manual are in LaTeX and thus have no thead */
- border-top: 2px solid black;
- border-bottom: 2px solid black;
-}
-.table thead ~ tbody,
-.template-reference-topic .table tr:last-child {
- /* only when it has a header */
- /* tables in manual are in LaTeX and thus have no thead */
- border-bottom: 2px solid black;
-}
-.table thead th {
- /* text-align: inherit; */
-}
-/* all tables, including argument lists */
-table a:not(.btn) {
- text-decoration: inherit;
-}
-table a:not(.btn):hover {
+code a[href]:hover, code a[href]:focus,
+a[href] code:hover, a[href] code:focus,
+pre a[href]:hover, pre a[href]:focus,
+a code[href]:hover, a code[href]:focus,
+a pre[href]:hover, a pre[href]:focus {
+ /* adjusted colour for all real links; having href attribute */
text-decoration: underline;
}
-.template-article thead th {
- text-align: inherit;
-}
-
-/* text below header in manual overview */
-.template-reference-index h2 ~ p {
- font-size: 15px;
-}
-.template-reference-topic h2 {
- font-size: 24px;
-}
-.template-reference-topic h3 {
- font-size: 18px;
-}
-.template-reference-topic h4 {
- font-size: 15px;
- font-weight: bold;
- padding-top: 35px;
-}
-
-.template-home h4 {
- padding-top: 40px !important;
- font-weight: bold !important;
-}
-.template-home h5 {
- font-weight: normal;
- font-style: italic;
- font-size: 16px;
-}
-
-/* AMR logo on index page */
-.template-home h1 img {
- height: 120px;
- margin-right: 10px !important;
-}
-
-.btn.btn-info.btn-amr {
- background: #128f76;
- color: #ffffff;
- border-color: #128f76;
- line-height: 1;
- width: 100%;
- font-weight: bold;
-}
-.btn.btn-info.btn-amr:hover {
- background: #128f7645;
- color: #2c3e50;
-}
-.home-buttons {
- display: flex;
- margin-bottom: 5px;
-}
-.home-buttons a {
- display: grid;
- text-align: center;
- font-size: 14px;
- text-transform: uppercase;
- max-width: 25%;
-}
-.home-buttons a:hover {
- text-decoration: none;
- opacity: 0.75;
-}
-.home-buttons div {
- display: grid;
- padding: 10px;
-}
-.home-buttons .fa {
- font-size: 3.5em;
-}
-.dataset-within-r {
- display: none;
-}
-.dataset-download-button {
- margin-right: 2%;
-}
-.dataset-download-button img {
- width: 80px !important;
- max-width: 14% !important;
-}
diff --git a/pkgdown/extra.js b/pkgdown/extra.js
index b0fa1c774..c7e099b79 100644
--- a/pkgdown/extra.js
+++ b/pkgdown/extra.js
@@ -25,27 +25,8 @@
# ==================================================================== #
*/
-// Add updated Font Awesome 5.8.2 library
-$('head').append('<!-- Updated Font Awesome library --><link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.8.2/css/all.css">');
-
$(document).ready(function() {
- // remove version label from header
- $(".version.label").remove();
-
- // redirect GitLab to GitHub
- var url_old = window.location.href;
- var url_new = url_old.replace("gitlab", "github");
- if (url_old != url_new) {
- window.location.replace(url_new);
- }
-
- // Edit title of manual
- $('.template-reference-index h1').text('Manual');
-
- // replace 'Value' in manual with 'Returned value'
- $(".template-reference-topic h2#value").text("Returned value");
-
// replace \donttest and \dontrun texts in Examples
if ($(".ref-examples pre").length > 0) {
$(".ref-examples pre").html($(".ref-examples pre").html().replaceAll("# \\donttest{", ""));
@@ -57,67 +38,34 @@ $(document).ready(function() {
if ($("body .template-news").length > 0) {
$("body .template-news").html($("body .template-news").html().replaceAll('sourceCode R">\n<span', 'sourceCode R"><span'));
}
- // change H1 header on dev version on changelog, since pkgdown uses the version number from the installed version
- // (rather then using the DESCRIPTION file)
- $("h1[id^=unreleased]").text("Current development version");
-
- // PR for 'R for Data Science' on How To pages
- if ($(".template-article").length > 0) {
- $('#pkgdown-sidebar').prepend(
- '<div id="r4ds">' +
- ' <div class="txt">' +
- ' <p>' +
- ' Learn R reading this great book: <i>R for Data Science</i>.' +
- ' <br><br>' +
- ' <a target="_blank" href="https://r4ds.had.co.nz/">' +
- ' Click to read it online - it was published for free.' +
- ' </a>' +
- ' </p>' +
- ' </div>' +
- ' <div class="img">' +
- ' <a target="_blank" href="https://r4ds.had.co.nz/">' +
- ' <img src="https://github.com/msberends/AMR/raw/main/docs/cover_r4ds.png">' +
- ' </a>' +
- ' </div>' +
- '</div>');
- }
- // edit footer
- $('footer').html(
- '<div>' +
- '<p><code>AMR</code> (for R). Developed at the <a target="_blank" href="https://www.rug.nl">University of Groningen</a> in collaboration with non-profit organisations<br><a target="_blank" href="https://www.certe.nl">Certe Medical Diagnostics and Advice Foundation</a> and <a target="_blank" href="https://www.umcg.nl">University Medical Center Groningen</a>.</p>' +
- '<a target="_blank" href="https://www.rug.nl"><img src="https://github.com/msberends/AMR/raw/main/docs/logo_rug.png" class="footer_logo"></a>' +
- '</div>');
-
- // doctoral titles of authors
+ // add doctoral titles to authors
function doct_tit(x) {
if (typeof(x) != "undefined") {
- // authors
- x = x.replace(/Author, maintainer/g, "Maintainer");
- x = x.replace(/Author, contributor/g, "Maintainer");
+ x = x.replace(/Author, maintainer/g, "Principle developer");
+ x = x.replace(/Author, contributor/g, "Contributing maintainer");
x = x.replace(/Author, thesis advisor/g, "Doctoral advisor");
x = x.replace(/Thesis advisor/g, "Doctoral advisor");
- x = x.replace("Matthijs", "Dr Matthijs");
- x = x.replace("Christian", "Dr Christian");
- x = x.replace("Alex", "Prof. Alex");
- x = x.replace("Bhanu", "Prof. Bhanu");
- x = x.replace("Casper", "Prof. Casper");
- x = x.replace("Corinna", "Dr Corinna");
- // others
- x = x.replace("Bart", "Dr Bart");
- x = x.replace("Sofia", "Dr Sofia");
- x = x.replace("Dennis", "Dr Dennis");
- x = x.replace("Judith", "Dr Judith");
- x = x.replace("Gwen", "Dr Gwen");
- x = x.replace("Anthony", "Dr Anthony");
- x = x.replace("Rogier", "Dr Rogier");
+ // authors
+ x = x.replace("Alex", "Prof. Dr. Alex");
+ x = x.replace("Anthony", "Dr. Anthony");
+ x = x.replace("Bart", "Dr. Bart");
+ x = x.replace("Bhanu", "Prof. Dr. Bhanu");
+ x = x.replace("Casper", "Prof. Dr. Casper");
+ x = x.replace("Christian", "Dr. Christian");
+ x = x.replace("Corinna", "Dr. Corinna");
+ x = x.replace("Dennis", "Dr. Dennis");
+ x = x.replace("Gwen", "Dr. Gwen");
+ x = x.replace("Judith", "Dr. Judith");
+ x = x.replace("Matthijs", "Dr. Matthijs");
+ x = x.replace("Peter", "Dr. Peter");
+ x = x.replace("Rogier", "Dr. Rogier");
+ x = x.replace("Sofia", "Dr. Sofia");
}
return(x);
}
$(".template-authors").html(doct_tit($(".template-authors").html()));
$(".template-citation-authors").html(doct_tit($(".template-citation-authors").html()));
- $('.template-citation-authors h1').eq(0).html("All contributors of the <code>AMR</code> package");
- $('.template-citation-authors h1').eq(1).html("How to cite the <code>AMR</code> package");
$(".developers").html(doct_tit($(".developers").html()));
$(".developers a[href='authors.html']").text("All contributors...");
});
diff --git a/pkgdown/logos/cover_r4ds.png b/pkgdown/logos/cover_r4ds.png
deleted file mode 100755
index a7150bdfa..000000000
Binary files a/pkgdown/logos/cover_r4ds.png and /dev/null differ
diff --git a/pkgdown/logos/lang_el.svg b/pkgdown/logos/lang_el.svg
new file mode 100644
index 000000000..532046f61
--- /dev/null
+++ b/pkgdown/logos/lang_el.svg
@@ -0,0 +1,5 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg xmlns="http://www.w3.org/2000/svg" width="600" height="400" viewBox="0 0 27 18">
+<rect fill="#0D5EAF" width="27" height="18"/>
+<path fill="none" stroke-width="2" stroke="#FFF" d="M5,0V11 M0,5H10 M10,3H27 M10,7H27 M0,11H27 M0,15H27"/>
+</svg>
\ No newline at end of file
diff --git a/pkgdown/logos/lang_ja.svg b/pkgdown/logos/lang_ja.svg
new file mode 100644
index 000000000..8f4547524
--- /dev/null
+++ b/pkgdown/logos/lang_ja.svg
@@ -0,0 +1,5 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg xmlns="http://www.w3.org/2000/svg" width="900" height="600">
+<rect fill="#fff" height="600" width="900"/>
+<circle fill="#bc002d" cx="450" cy="300" r="180"/>
+</svg>
\ No newline at end of file
diff --git a/pkgdown/logos/lang_pl.svg b/pkgdown/logos/lang_pl.svg
new file mode 100644
index 000000000..5556266bb
--- /dev/null
+++ b/pkgdown/logos/lang_pl.svg
@@ -0,0 +1,5 @@
+<?xml version="1.0"?>
+<svg xmlns="http://www.w3.org/2000/svg" width="640" height="400" viewBox="0 0 8 5">
+<rect width="8" height="5" fill="#dc143c"/>
+<rect width="8" height="2.5" fill="#fff"/>
+</svg>
\ No newline at end of file
diff --git a/pkgdown/logos/lang_tr.svg b/pkgdown/logos/lang_tr.svg
new file mode 100644
index 000000000..33f5ad1fd
--- /dev/null
+++ b/pkgdown/logos/lang_tr.svg
@@ -0,0 +1,5 @@
+<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="800" viewBox="0 -30000 90000 60000">
+ <title>Flag of Turkey</title>
+ <path fill="#e30a17" d="m0-30000h90000v60000H0z"/>
+ <path fill="#fff" d="m41750 0 13568-4408-8386 11541V-7133l8386 11541zm925 8021a15000 15000 0 1 1 0-16042 12000 12000 0 1 0 0 16042z"/>
+</svg>
diff --git a/pkgdown/logos/lang_uk.svg b/pkgdown/logos/lang_uk.svg
new file mode 100644
index 000000000..8f4b0a436
--- /dev/null
+++ b/pkgdown/logos/lang_uk.svg
@@ -0,0 +1,4 @@
+<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="800">
+<rect width="1200" height="800" fill="#005BBB"/>
+<rect width="1200" height="400" y="400" fill="#FFD500"/>
+</svg>
\ No newline at end of file
diff --git a/pkgdown/logos/lang_zh.svg b/pkgdown/logos/lang_zh.svg
new file mode 100644
index 000000000..61f4fdcbd
--- /dev/null
+++ b/pkgdown/logos/lang_zh.svg
@@ -0,0 +1,12 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="900" height="600" viewBox="0 0 30 20">
+<defs>
+<path id="s" d="M0,-1 0.587785,0.809017 -0.951057,-0.309017H0.951057L-0.587785,0.809017z" fill="#FFFF00"/>
+</defs>
+<rect width="30" height="20" fill="#EE1C25"/>
+<use xlink:href="#s" transform="translate(5,5) scale(3)"/>
+<use xlink:href="#s" transform="translate(10,2) rotate(23.036243)"/>
+<use xlink:href="#s" transform="translate(12,4) rotate(45.869898)"/>
+<use xlink:href="#s" transform="translate(12,7) rotate(69.945396)"/>
+<use xlink:href="#s" transform="translate(10,9) rotate(20.659808)"/>
+</svg>
\ No newline at end of file
diff --git a/pkgdown/logos/lifecycle_archived.svg b/pkgdown/logos/lifecycle_archived.svg
deleted file mode 100644
index 5f27d819d..000000000
--- a/pkgdown/logos/lifecycle_archived.svg
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/pkgdown/logos/lifecycle_dormant.svg b/pkgdown/logos/lifecycle_dormant.svg
deleted file mode 100644
index bd3aa7942..000000000
--- a/pkgdown/logos/lifecycle_dormant.svg
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/pkgdown/logos/lifecycle_experimental.svg b/pkgdown/logos/lifecycle_experimental.svg
deleted file mode 100644
index d43aa63d6..000000000
--- a/pkgdown/logos/lifecycle_experimental.svg
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/pkgdown/logos/lifecycle_maturing.svg b/pkgdown/logos/lifecycle_maturing.svg
deleted file mode 100644
index fb793aced..000000000
--- a/pkgdown/logos/lifecycle_maturing.svg
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/pkgdown/logos/lifecycle_questioning.svg b/pkgdown/logos/lifecycle_questioning.svg
deleted file mode 100644
index 137d4ecdd..000000000
--- a/pkgdown/logos/lifecycle_questioning.svg
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/pkgdown/logos/lifecycle_retired.svg b/pkgdown/logos/lifecycle_retired.svg
deleted file mode 100644
index 33f406b12..000000000
--- a/pkgdown/logos/lifecycle_retired.svg
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/pkgdown/logos/lifecycle_stable.svg b/pkgdown/logos/lifecycle_stable.svg
deleted file mode 100644
index be0966740..000000000
--- a/pkgdown/logos/lifecycle_stable.svg
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/pkgdown/logos/lifecycle_tidyverse.svg b/pkgdown/logos/lifecycle_tidyverse.svg
deleted file mode 100644
index 1d8db94f5..000000000
--- a/pkgdown/logos/lifecycle_tidyverse.svg
+++ /dev/null
@@ -1,32 +0,0 @@
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-<svg width="510.24pt" height="184.25pt" version="1.1" viewBox="0 0 510.24 184.25" xmlns="http://www.w3.org/2000/svg">
-<style>
- text {
- fill: white;
- font-family: "Helvetica Neue";
- }
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-<path d="m4.8 0-4.8-1.8v3.6z" fill="currentColor" stroke="currentColor"/>
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diff --git a/vignettes/resistance_predict.Rmd b/vignettes/resistance_predict.Rmd
index 2dd9ca1c8..182595a4b 100755
--- a/vignettes/resistance_predict.Rmd
+++ b/vignettes/resistance_predict.Rmd
@@ -96,7 +96,7 @@ example_isolates %>%
ggplot_rsi_predict()
```
-Vancomycin resistance could be 100% in ten years, but might also stay around 0%.
+Vancomycin resistance could be 100% in ten years, but might remain very low.
You can define the model with the `model` parameter. The model chosen above is a generalised linear regression model using a binomial distribution, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance.
@@ -108,7 +108,7 @@ Valid values are:
| `"loglin"` or `"poisson"` | `glm(..., family = poisson)` | Generalised linear model with poisson distribution |
| `"lin"` or `"linear"` | `lm()` | Linear model |
-For the vancomycin resistance in Gram-positive bacteria, a linear model might be more appropriate since no binomial distribution is to be expected based on the observed years:
+For the vancomycin resistance in Gram-positive bacteria, a linear model might be more appropriate:
```{r}
example_isolates %>%
@@ -117,8 +117,6 @@ example_isolates %>%
ggplot_rsi_predict()
```
-This seems more likely, doesn't it?
-
The model itself is also available from the object, as an `attribute`:
```{r}
model <- attributes(predict_TZP)$model