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(v1.5.0.9014) only_rsi_columns, is.rsi.eligible improvement

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dr. M.S. (Matthijs) Berends
2021-02-02 23:57:35 +01:00
parent 20d638c193
commit 2eca8c3f01
246 changed files with 1171 additions and 965 deletions
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43
R/aa_helper_functions.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
# faster implementation of left_join than using merge() by poorman - we use match():
@ -673,6 +673,45 @@ get_current_data <- function(arg_name, call) {
}
}
get_current_column <- function() {
# try dplyr::cur_columns() first
cur_column <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
if (!is.null(cur_column)) {
out <- tryCatch(cur_column(), error = function(e) NULL)
if (!is.null(out)) {
return(out)
}
}
# cur_column() doesn't always work (only allowed for conditions set by dplyr), but it's probably still possible:
frms <- lapply(sys.frames(), function(el) {
if ("i" %in% names(el)) {
if ("tibble_vars" %in% names(el)) {
# for mutate_if()
el$tibble_vars[el$i]
} else {
# for mutate(across())
df <- tryCatch(get_current_data(NA, 0), error = function(e) NULL)
if (is.data.frame(df)) {
colnames(df)[el$i]
} else {
el$i
}
}
} else {
NULL
}
})
vars <- unlist(frms)
if (length(vars) > 0) {
vars[length(vars)]
} else {
# not found, so:
NULL
}
}
unique_call_id <- function(entire_session = FALSE) {
if (entire_session == TRUE) {
c(envir = "session",

4
R/aa_helper_pm_functions.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
# ------------------------------------------------

22
R/ab.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Transform Input to an Antibiotic ID
@ -103,19 +103,20 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
initial_search <- is.null(list(...)$initial_search)
already_regex <- isTRUE(list(...)$already_regex)
fast_mode <- isTRUE(list(...)$fast_mode)
if (all(toupper(x) %in% antibiotics$ab)) {
# valid AB code, but not yet right class
return(set_clean_class(toupper(x),
new_class = c("ab", "character")))
}
x_bak <- x
x <- toupper(x)
# remove diacritics
x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT")
x <- gsub('"', "", x, fixed = TRUE)
x <- gsub("(specimen|specimen date|specimen_date|spec_date)", "", x, ignore.case = TRUE, perl = TRUE)
x <- gsub("(specimen|specimen date|specimen_date|spec_date|^dates?$)", "", x, ignore.case = TRUE, perl = TRUE)
x_bak_clean <- x
if (already_regex == FALSE) {
x_bak_clean <- generalise_antibiotic_name(x_bak_clean)
@ -145,6 +146,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
}
for (i in seq_len(length(x))) {
if (initial_search == TRUE) {
progress$tick()
}
@ -161,7 +163,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
next
}
if (isTRUE(flag_multiple_results) & x[i] %like% "[ ]") {
if (fast_mode == FALSE && flag_multiple_results == TRUE && x[i] %like% "[ ]") {
from_text <- tryCatch(suppressWarnings(ab_from_text(x[i], initial_search = FALSE, translate_ab = FALSE)[[1]]),
error = function(e) character(0))
} else {
@ -282,8 +284,8 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
}
# INITIAL SEARCH - More uncertain results ----
if (initial_search == TRUE) {
if (initial_search == TRUE && fast_mode == FALSE) {
# only run on first try
# try by removing all spaces
@ -358,7 +360,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
# try from a bigger text, like from a health care record, see ?ab_from_text
# already calculated above if flag_multiple_results = TRUE
if (isTRUE(flag_multiple_results)) {
if (flag_multiple_results == TRUE) {
found <- from_text[1L]
} else {
found <- tryCatch(suppressWarnings(ab_from_text(x[i], initial_search = FALSE, translate_ab = FALSE)[[1]][1L]),
@ -457,7 +459,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
call = FALSE)
}
if (length(x_unknown) > 0) {
if (length(x_unknown) > 0 & fast_mode == FALSE) {
warning_("These values could not be coerced to a valid antimicrobial ID: ",
paste('"', sort(unique(x_unknown)), '"', sep = "", collapse = ", "),
".",
@ -466,7 +468,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
x_result <- data.frame(x = x_bak_clean, stringsAsFactors = FALSE) %pm>%
pm_left_join(data.frame(x = x, x_new = x_new, stringsAsFactors = FALSE), by = "x") %pm>%
pm_pull(x_new)
pm_pull(x_new)
if (length(x_result) == 0) {
x_result <- NA_character_

69
R/ab_class_selectors.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,13 +20,14 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Antibiotic Class Selectors
#'
#' These functions help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. \strong{\Sexpr{ifelse(as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2, paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
#' @inheritSection lifecycle Stable Lifecycle
#' @param only_rsi_columns a logical to indicate whether only columns of class [`<rsi>`]([rsi]) must be selected. If set to `NULL` (default), it will be `TRUE` if any column of the data was [transformed to class `<rsi>`]([rsi]) on beforehand, and `FALSE` otherwise.
#' @inheritParams filter_ab_class
#' @details \strong{\Sexpr{ifelse(as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2, paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
#'
@ -79,91 +80,95 @@
#' example_isolates %>% filter_carbapenems("R", "all")
#' example_isolates %>% filter(across(carbapenems(), ~. == "R"))
#' }
ab_class <- function(ab_class) {
ab_class <- function(ab_class,
only_rsi_columns = NULL) {
ab_selector(ab_class, function_name = "ab_class")
}
#' @rdname antibiotic_class_selectors
#' @export
aminoglycosides <- function() {
aminoglycosides <- function(only_rsi_columns = NULL) {
ab_selector("aminoglycoside", function_name = "aminoglycosides")
}
#' @rdname antibiotic_class_selectors
#' @export
carbapenems <- function() {
ab_selector("carbapenem", function_name = "carbapenems")
carbapenems <- function(only_rsi_columns = NULL) {
ab_selector("carbapenem", function_name = "carbapenems", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins <- function() {
ab_selector("cephalosporin", function_name = "cephalosporins")
cephalosporins <- function(only_rsi_columns = NULL) {
ab_selector("cephalosporin", function_name = "cephalosporins", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_1st <- function() {
ab_selector("cephalosporins.*1", function_name = "cephalosporins_1st")
cephalosporins_1st <- function(only_rsi_columns = NULL) {
ab_selector("cephalosporins.*1", function_name = "cephalosporins_1st", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_2nd <- function() {
ab_selector("cephalosporins.*2", function_name = "cephalosporins_2nd")
cephalosporins_2nd <- function(only_rsi_columns = NULL) {
ab_selector("cephalosporins.*2", function_name = "cephalosporins_2nd", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_3rd <- function() {
ab_selector("cephalosporins.*3", function_name = "cephalosporins_3rd")
cephalosporins_3rd <- function(only_rsi_columns = NULL) {
ab_selector("cephalosporins.*3", function_name = "cephalosporins_3rd", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_4th <- function() {
ab_selector("cephalosporins.*4", function_name = "cephalosporins_4th")
cephalosporins_4th <- function(only_rsi_columns = NULL) {
ab_selector("cephalosporins.*4", function_name = "cephalosporins_4th", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
cephalosporins_5th <- function() {
ab_selector("cephalosporins.*5", function_name = "cephalosporins_5th")
cephalosporins_5th <- function(only_rsi_columns = NULL) {
ab_selector("cephalosporins.*5", function_name = "cephalosporins_5th", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
fluoroquinolones <- function() {
ab_selector("fluoroquinolone", function_name = "fluoroquinolones")
fluoroquinolones <- function(only_rsi_columns = NULL) {
ab_selector("fluoroquinolone", function_name = "fluoroquinolones", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
glycopeptides <- function() {
ab_selector("glycopeptide", function_name = "glycopeptides")
glycopeptides <- function(only_rsi_columns = NULL) {
ab_selector("glycopeptide", function_name = "glycopeptides", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
macrolides <- function() {
ab_selector("macrolide", function_name = "macrolides")
macrolides <- function(only_rsi_columns = NULL) {
ab_selector("macrolide", function_name = "macrolides", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
penicillins <- function() {
ab_selector("penicillin", function_name = "penicillins")
penicillins <- function(only_rsi_columns = NULL) {
ab_selector("penicillin", function_name = "penicillins", only_rsi_columns = only_rsi_columns)
}
#' @rdname antibiotic_class_selectors
#' @export
tetracyclines <- function() {
ab_selector("tetracycline", function_name = "tetracyclines")
tetracyclines <- function(only_rsi_columns = NULL) {
ab_selector("tetracycline", function_name = "tetracyclines", only_rsi_columns = only_rsi_columns)
}
ab_selector <- function(ab_class, function_name) {
ab_selector <- function(ab_class,
function_name,
only_rsi_columns) {
meet_criteria(ab_class, allow_class = "character", has_length = 1, .call_depth = 1)
meet_criteria(function_name, allow_class = "character", has_length = 1, .call_depth = 1)
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1, allow_NULL = TRUE, .call_depth = 1)
if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2) {
warning_("antibiotic class selectors such as ", function_name,
@ -173,10 +178,12 @@ ab_selector <- function(ab_class, function_name) {
}
vars_df <- get_current_data(arg_name = NA, call = -3)
if (is.null(only_rsi_columns)) {
only_rsi_columns <- any(is.rsi(vars_df))
}
# improve speed here so it will only run once when e.g. in one select call
if (!identical(pkg_env$ab_selector, unique_call_id())) {
ab_in_data <- get_column_abx(vars_df, info = FALSE)
ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns)
pkg_env$ab_selector <- unique_call_id()
pkg_env$ab_selector_cols <- ab_in_data
} else {

4
R/ab_from_text.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Retrieve Antimicrobial Drug Names and Doses from Clinical Text

4
R/ab_property.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Get Properties of an Antibiotic

4
R/age.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Age in Years of Individuals

8
R/amr.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' The `AMR` Package
@ -37,7 +37,7 @@
#' - 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
#' - Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines
#' - Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records
#' - Determining first isolates to be used for AMR analysis
#' - Determining first isolates to be used for AMR data analysis
#' - Calculating antimicrobial resistance
#' - Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)
#' - Calculating (empirical) susceptibility of both mono therapy and combination therapies
@ -54,7 +54,7 @@
#' @section Reference Data Publicly Available:
#' All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this `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 [all download links on our website](https://msberends.github.io/AMR/articles/datasets.html), which is automatically updated with every code change.
#' @section Read more on Our Website!:
#' On our website <https://msberends.github.io/AMR/> you can find [a comprehensive tutorial](https://msberends.github.io/AMR/articles/AMR.html) about how to conduct AMR analysis, the [complete documentation of all functions](https://msberends.github.io/AMR/reference/) and [an example analysis using WHONET data](https://msberends.github.io/AMR/articles/WHONET.html). As we would like to better understand the backgrounds and needs of our users, please [participate in our survey](https://msberends.github.io/AMR/survey.html)!
#' On our website <https://msberends.github.io/AMR/> you can find [a comprehensive tutorial](https://msberends.github.io/AMR/articles/AMR.html) about how to conduct AMR data analysis, the [complete documentation of all functions](https://msberends.github.io/AMR/reference/) and [an example analysis using WHONET data](https://msberends.github.io/AMR/articles/WHONET.html). As we would like to better understand the backgrounds and needs of our users, please [participate in our survey](https://msberends.github.io/AMR/survey.html)!
#' @section Contact Us:
#' For suggestions, comments or questions, please contact us at:
#'

4
R/atc_online.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Get ATC Properties from WHOCC Website

4
R/availability.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Check Availability of Columns

4
R/bug_drug_combinations.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Determine Bug-Drug Combinations

4
R/catalogue_of_life.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
format_included_data_number <- function(data) {

4
R/count.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Count Available Isolates

8
R/data.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Data Sets with `r format(nrow(antibiotics) + nrow(antivirals), big.mark = ",")` Antimicrobials
@ -174,7 +174,7 @@ catalogue_of_life <- list(
#' Data Set with `r format(nrow(example_isolates), big.mark = ",")` Example Isolates
#'
#' A data set containing `r format(nrow(example_isolates), big.mark = ",")` microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html).
#' A data set containing `r format(nrow(example_isolates), big.mark = ",")` microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR data analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html).
#' @format A [data.frame] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables:
#' - `date`\cr date of receipt at the laboratory
#' - `hospital_id`\cr ID of the hospital, from A to D
@ -192,7 +192,7 @@ catalogue_of_life <- list(
#' Data Set with Unclean Data
#'
#' A data set containing `r format(nrow(example_isolates_unclean), big.mark = ",")` microbial isolates that are not cleaned up and consequently not ready for AMR analysis. This data set can be used for practice.
#' A data set containing `r format(nrow(example_isolates_unclean), big.mark = ",")` microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice.
#' @format A [data.frame] with `r format(nrow(example_isolates_unclean), big.mark = ",")` observations and `r ncol(example_isolates_unclean)` variables:
#' - `patient_id`\cr ID of the patient
#' - `date`\cr date of receipt at the laboratory

4
R/deprecated.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Deprecated Functions

4
R/disk.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Transform Input to Disk Diffusion Diameters

4
R/episode.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Determine (New) Episodes for Patients

12
R/eucast_rules.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,11 +20,11 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
# add new version numbers here, and add the rules themselves to "data-raw/eucast_rules.tsv" and rsi_translation
# (running "data-raw/internals.R" will process the TSV file)
# (sourcing "data-raw/_internals.R" will process the TSV file)
EUCAST_VERSION_BREAKPOINTS <- list("11.0" = list(version_txt = "v11.0",
year = 2021,
title = "'EUCAST Clinical Breakpoint Tables'",
@ -77,6 +77,7 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
#' @param ... column name of an antibiotic, see section *Antibiotics* below
#' @param ab any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
#' @param administration route of administration, either `r vector_or(dosage$administration)`
#' @param only_rsi_columns a logical to indicate whether only antibiotic columns must be detected that were [transformed to class `<rsi>`]([rsi]) on beforehand. Defaults to `TRUE` if any column of `x` is of class `<rsi>`.
#' @inheritParams first_isolate
#' @details
#' **Note:** This function does not translate MIC values to RSI values. Use [as.rsi()] for that. \cr
@ -165,6 +166,7 @@ eucast_rules <- function(x,
version_breakpoints = 11.0,
version_expertrules = 3.2,
ampc_cephalosporin_resistance = NA,
only_rsi_columns = any(is.rsi(x)),
...) {
meet_criteria(x, allow_class = "data.frame")
meet_criteria(col_mo, allow_class = "character", has_length = 1, is_in = colnames(x), allow_NULL = TRUE)
@ -174,6 +176,7 @@ eucast_rules <- function(x,
meet_criteria(version_breakpoints, allow_class = c("numeric", "integer"), has_length = 1, is_in = as.double(names(EUCAST_VERSION_BREAKPOINTS)))
meet_criteria(version_expertrules, allow_class = c("numeric", "integer"), has_length = 1, is_in = as.double(names(EUCAST_VERSION_EXPERT_RULES)))
meet_criteria(ampc_cephalosporin_resistance, has_length = 1, allow_NA = TRUE, allow_NULL = TRUE, is_in = c("R", "S", "I"))
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
x_deparsed <- deparse(substitute(x))
if (length(x_deparsed) > 1 || !all(x_deparsed %like% "[a-z]+")) {
@ -276,6 +279,7 @@ eucast_rules <- function(x,
hard_dependencies = NULL,
verbose = verbose,
info = info,
only_rsi_columns = only_rsi_columns,
...)
AMC <- cols_ab["AMC"]
@ -748,7 +752,7 @@ eucast_rules <- function(x,
# this allows: eucast_rules(x, eucast_rules_df = AMR:::eucast_rules_file %>% filter(is.na(have_these_values)))
eucast_rules_df <- list(...)$eucast_rules_df
} else {
# otherwise internal data file, created in data-raw/internals.R
# otherwise internal data file, created in data-raw/_internals.R
eucast_rules_df <- eucast_rules_file
}

8
R/filter_ab_class.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Filter Isolates on Result in Antimicrobial Class
@ -31,7 +31,8 @@
#' @param ab_class an antimicrobial class, like `"carbapenems"`. The columns `group`, `atc_group1` and `atc_group2` of the [antibiotics] data set will be searched (case-insensitive) for this value.
#' @param result an antibiotic result: S, I or R (or a combination of more of them)
#' @param scope the scope to check which variables to check, can be `"any"` (default) or `"all"`
#' @param ... previously used when this package still depended on the `dplyr` package, now ignored
#' @param only_rsi_columns a logical to indicate whether only columns must be included that were [transformed to class `<rsi>`]([rsi]) on beforehand. Defaults to `TRUE` if any column of `x` is of class `<rsi>`.
#' @param ... arguments passed on to [filter_ab_class()]
#' @details All columns of `x` will be searched for known antibiotic names, abbreviations, brand names and codes (ATC, EARS-Net, WHO, etc.). This means that a filter function like e.g. [filter_aminoglycosides()] will include column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
#' @rdname filter_ab_class
#' @seealso [antibiotic_class_selectors()] for the `select()` equivalent.
@ -81,6 +82,7 @@ filter_ab_class <- function(x,
ab_class,
result = NULL,
scope = "any",
only_rsi_columns = any(is.rsi(x)),
...) {
.call_depth <- list(...)$`.call_depth`
if (is.null(.call_depth)) {

6
R/first_isolate.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Determine First (Weighted) Isolates
@ -255,7 +255,7 @@ first_isolate <- function(x,
# create original row index
x$newvar_row_index <- seq_len(nrow(x))
x$newvar_mo <- x[, col_mo, drop = TRUE]
x$newvar_mo <- as.mo(x[, col_mo, drop = TRUE])
x$newvar_genus_species <- paste(mo_genus(x$newvar_mo), mo_species(x$newvar_mo))
x$newvar_date <- x[, col_date, drop = TRUE]
x$newvar_patient_id <- x[, col_patient_id, drop = TRUE]

4
R/g.test.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' *G*-test for Count Data

4
R/ggplot_pca.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' PCA Biplot with `ggplot2`

6
R/ggplot_rsi.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,12 +20,12 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' AMR Plots with `ggplot2`
#'
#' Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on [ggplot2][ggplot2::ggplot()] functions.
#' Use these functions to create bar plots for AMR data analysis. All functions rely on [ggplot2][ggplot2::ggplot()] functions.
#' @inheritSection lifecycle Maturing 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"`

4
R/globals.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
globalVariables(c(".rowid",

66
R/guess_ab_col.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Guess Antibiotic Column
@ -30,6 +30,7 @@
#' @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
#' @param only_rsi_columns a logical to indicate whether only antibiotic columns must be detected that were [transformed to class `<rsi>`]([rsi]) on beforehand. Defaults to `TRUE` if any column of `x` is of class `<rsi>`.
#' @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
@ -62,35 +63,20 @@
#' AMP_ED20 = "S")
#' guess_ab_col(df, "ampicillin")
#' # [1] "AMP_ED20"
guess_ab_col <- function(x = NULL, search_string = NULL, verbose = FALSE) {
guess_ab_col <- function(x = NULL, search_string = NULL, verbose = FALSE, only_rsi_columns = any(is.rsi(x))) {
meet_criteria(x, allow_class = "data.frame", allow_NULL = TRUE)
meet_criteria(search_string, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(verbose, allow_class = "logical", has_length = 1)
if (is.null(x) & is.null(search_string)) {
return(as.name("guess_ab_col"))
} else {
meet_criteria(search_string, allow_class = "character", has_length = 1, allow_NULL = FALSE)
}
if (search_string %in% colnames(x)) {
ab_result <- search_string
} else {
search_string.ab <- suppressWarnings(as.ab(search_string))
if (search_string.ab %in% colnames(x)) {
ab_result <- colnames(x)[colnames(x) == search_string.ab][1L]
} else if (any(tolower(colnames(x)) %in% tolower(unlist(ab_property(search_string.ab, "abbreviations", language = NULL))))) {
ab_result <- colnames(x)[tolower(colnames(x)) %in% tolower(unlist(ab_property(search_string.ab, "abbreviations", language = NULL)))][1L]
} else {
# sort colnames on length - longest first
cols <- colnames(x[, x %pm>% colnames() %pm>% nchar() %pm>% order() %pm>% rev()])
df_trans <- data.frame(cols = cols,
abs = suppressWarnings(as.ab(cols)),
stringsAsFactors = FALSE)
ab_result <- df_trans[which(df_trans$abs == search_string.ab), "cols"]
ab_result <- ab_result[!is.na(ab_result)][1L]
}
}
all_found <- get_column_abx(x, info = verbose, only_rsi_columns = only_rsi_columns, verbose = verbose)
search_string.ab <- suppressWarnings(as.ab(search_string))
ab_result <- unname(all_found[names(all_found) == search_string.ab])
if (length(ab_result) == 0) {
if (verbose == TRUE) {
@ -114,18 +100,24 @@ get_column_abx <- function(x,
hard_dependencies = NULL,
verbose = FALSE,
info = TRUE,
only_rsi_columns = FALSE,
...) {
meet_criteria(x, allow_class = "data.frame")
meet_criteria(soft_dependencies, allow_class = "character", allow_NULL = TRUE)
meet_criteria(hard_dependencies, allow_class = "character", allow_NULL = TRUE)
meet_criteria(verbose, allow_class = "logical", has_length = 1)
meet_criteria(info, allow_class = "logical", has_length = 1)
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
if (info == TRUE) {
message_("Auto-guessing columns suitable for analysis", appendLF = FALSE, as_note = FALSE)
}
x <- as.data.frame(x, stringsAsFactors = FALSE)
if (only_rsi_columns == TRUE) {
x <- x[, which(is.rsi(x)), drop = FALSE]
}
if (NROW(x) > 10000) {
# only test maximum of 10,000 values per column
if (info == TRUE) {
@ -141,21 +133,23 @@ get_column_abx <- function(x,
# only check columns that are a valid AB code, ATC code, name, abbreviation or synonym,
# or already have the <rsi> class (as.rsi)
# and that they have no more than 50% invalid values
vectr_antibiotics <- unique(toupper(unlist(antibiotics[, c("ab", "atc", "name", "abbreviations", "synonyms")])))
vectr_antibiotics <- unlist(AB_lookup$generalised_all)
vectr_antibiotics <- vectr_antibiotics[!is.na(vectr_antibiotics) & nchar(vectr_antibiotics) >= 3]
x_columns <- vapply(FUN.VALUE = character(1), colnames(x), function(col, df = x) {
if (toupper(col) %in% vectr_antibiotics ||
is.rsi(x[, col, drop = TRUE]) ||
is.rsi.eligible(x[, col, drop = TRUE], threshold = 0.5)
) {
return(col)
} else {
return(NA_character_)
}
})
x_columns <- vapply(FUN.VALUE = character(1),
colnames(x),
function(col, df = x) {
if (generalise_antibiotic_name(col) %in% vectr_antibiotics ||
is.rsi(x[, col, drop = TRUE]) ||
is.rsi.eligible(x[, col, drop = TRUE], threshold = 0.5)
) {
return(col)
} else {
return(NA_character_)
}
})
x_columns <- x_columns[!is.na(x_columns)]
x <- x[, x_columns, drop = FALSE] # without drop = TRUE, x will become a vector when x_columns is length 1
x <- x[, x_columns, drop = FALSE] # without drop = FALSE, x will become a vector when x_columns is length 1
df_trans <- data.frame(colnames = colnames(x),
abcode = suppressWarnings(as.ab(colnames(x), info = FALSE)),
stringsAsFactors = FALSE)
@ -164,7 +158,7 @@ get_column_abx <- function(x,
names(x) <- df_trans$abcode
# add from self-defined dots (...):
# such as get_column_abx(example_isolates %pm>% rename(thisone = AMX), amox = "thisone")
# such as get_column_abx(example_isolates %>% rename(thisone = AMX), amox = "thisone")
dots <- list(...)
if (length(dots) > 0) {
newnames <- suppressWarnings(as.ab(names(dots), info = FALSE))

4
R/isolate_identifier.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Create Identifier of an Isolate

4
R/join_microorganisms.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Join [microorganisms] to a Data Set

10
R/key_antibiotics.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Key Antibiotics for First (Weighted) Isolates
@ -234,8 +234,9 @@ key_antibiotics <- function(x,
GramPos_4, GramPos_5, GramPos_6)
gram_positive <- gram_positive[!is.null(gram_positive)]
gram_positive <- gram_positive[!is.na(gram_positive)]
if (length(gram_positive) < 12) {
if (length(gram_positive) < 12 & message_not_thrown_before("key_antibiotics.grampos")) {
warning_("Only using ", length(gram_positive), " different antibiotics as key antibiotics for Gram-positives. See ?key_antibiotics.", call = FALSE)
remember_thrown_message("key_antibiotics.grampos")
}
gram_negative <- c(universal,
@ -243,8 +244,9 @@ key_antibiotics <- function(x,
GramNeg_4, GramNeg_5, GramNeg_6)
gram_negative <- gram_negative[!is.null(gram_negative)]
gram_negative <- gram_negative[!is.na(gram_negative)]
if (length(gram_negative) < 12) {
if (length(gram_negative) < 12 & message_not_thrown_before("key_antibiotics.gramneg")) {
warning_("Only using ", length(gram_negative), " different antibiotics as key antibiotics for Gram-negatives. See ?key_antibiotics.", call = FALSE)
remember_thrown_message("key_antibiotics.gramneg")
}
x <- as.data.frame(x, stringsAsFactors = FALSE)

4
R/kurtosis.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Kurtosis of the Sample

4
R/lifecycle.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
###############

4
R/like.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Pattern Matching with Keyboard Shortcut

34
R/mdro.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Determine Multidrug-Resistant Organisms (MDRO)
@ -153,6 +153,7 @@ mdro <- function(x,
pct_required_classes = 0.5,
combine_SI = TRUE,
verbose = FALSE,
only_rsi_columns = any(is.rsi(x)),
...) {
if (missing(x)) {
x <- get_current_data(arg_name = "x", call = -2)
@ -432,6 +433,7 @@ mdro <- function(x,
"MNO"),
verbose = verbose,
info = info,
only_rsi_columns = only_rsi_columns,
...)
} else if (guideline$code == "eucast3.2") {
cols_ab <- get_column_abx(x = x,
@ -457,8 +459,9 @@ mdro <- function(x,
"TOB",
"TZD",
"VAN"),
info = info,
verbose = verbose,
info = info,
only_rsi_columns = only_rsi_columns,
...)
} else if (guideline$code == "tb") {
cols_ab <- get_column_abx(x = x,
@ -470,8 +473,9 @@ mdro <- function(x,
"RIF",
"RIB",
"RFP"),
info = info,
verbose = verbose,
info = info,
only_rsi_columns = only_rsi_columns,
...)
} else if (guideline$code == "mrgn") {
cols_ab <- get_column_abx(x = x,
@ -483,11 +487,13 @@ mdro <- function(x,
"CIP"),
verbose = verbose,
info = info,
only_rsi_columns = only_rsi_columns,
...)
} else {
cols_ab <- get_column_abx(x = x,
verbose = verbose,
info = info,
only_rsi_columns = only_rsi_columns,
...)
}
@ -1509,55 +1515,55 @@ run_custom_mdro_guideline <- function(df, guideline) {
#' @rdname mdro
#' @export
brmo <- function(x, guideline = "BRMO", ...) {
brmo <- function(x, guideline = "BRMO", only_rsi_columns = any(is.rsi(x)), ...) {
if (missing(x)) {
x <- get_current_data(arg_name = "x", call = -2)
}
meet_criteria(x, allow_class = "data.frame")
meet_criteria(guideline, allow_class = "character", has_length = 1)
mdro(x, guideline = "BRMO", ...)
mdro(x, guideline = "BRMO", only_rsi_columns = only_rsi_columns, ...)
}
#' @rdname mdro
#' @export
mrgn <- function(x, guideline = "MRGN", ...) {
mrgn <- function(x, guideline = "MRGN", only_rsi_columns = any(is.rsi(x)), ...) {
if (missing(x)) {
x <- get_current_data(arg_name = "x", call = -2)
}
meet_criteria(x, allow_class = "data.frame")
meet_criteria(guideline, allow_class = "character", has_length = 1)
mdro(x = x, guideline = "MRGN", ...)
mdro(x = x, guideline = "MRGN", only_rsi_columns = only_rsi_columns, ...)
}
#' @rdname mdro
#' @export
mdr_tb <- function(x, guideline = "TB", ...) {
mdr_tb <- function(x, guideline = "TB", only_rsi_columns = any(is.rsi(x)), ...) {
if (missing(x)) {
x <- get_current_data(arg_name = "x", call = -2)
}
meet_criteria(x, allow_class = "data.frame")
meet_criteria(guideline, allow_class = "character", has_length = 1)
mdro(x = x, guideline = "TB", ...)
mdro(x = x, guideline = "TB", only_rsi_columns = only_rsi_columns, ...)
}
#' @rdname mdro
#' @export
mdr_cmi2012 <- function(x, guideline = "CMI2012", ...) {
mdr_cmi2012 <- function(x, guideline = "CMI2012", only_rsi_columns = any(is.rsi(x)), ...) {
if (missing(x)) {
x <- get_current_data(arg_name = "x", call = -2)
}
meet_criteria(x, allow_class = "data.frame")
meet_criteria(guideline, allow_class = "character", has_length = 1)
mdro(x = x, guideline = "CMI2012", ...)
mdro(x = x, guideline = "CMI2012", only_rsi_columns = only_rsi_columns, ...)
}
#' @rdname mdro
#' @export
eucast_exceptional_phenotypes <- function(x, guideline = "EUCAST", ...) {
eucast_exceptional_phenotypes <- function(x, guideline = "EUCAST", only_rsi_columns = any(is.rsi(x)), ...) {
if (missing(x)) {
x <- get_current_data(arg_name = "x", call = -2)
}
meet_criteria(x, allow_class = "data.frame")
meet_criteria(guideline, allow_class = "character", has_length = 1)
mdro(x = x, guideline = "EUCAST", ...)
mdro(x = x, guideline = "EUCAST", only_rsi_columns = only_rsi_columns, ...)
}

4
R/mic.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Transform Input to Minimum Inhibitory Concentrations (MIC)

4
R/mo.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Transform Input to a Microorganism ID

4
R/mo_matching_score.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Calculate the Matching Score for Microorganisms

4
R/mo_property.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Get Properties of a Microorganism

4
R/mo_source.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' User-Defined Reference Data Set for Microorganisms

4
R/pca.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Principal Component Analysis (for AMR)

4
R/proportion.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Calculate Microbial Resistance

6
R/random.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,12 +20,12 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Random MIC Values/Disk Zones/RSI Generation
#'
#' These functions can be used for generating random MIC values and disk diffusion diameters, for AMR analysis practice.
#' These functions can be used for generating random MIC values and disk diffusion diameters, for AMR data analysis practice.
#' @inheritSection lifecycle Maturing Lifecycle
#' @param size desired size of the returned vector
#' @param mo any character that can be coerced to a valid microorganism code with [as.mo()]

4
R/resistance_predict.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Predict antimicrobial resistance

34
R/rsi.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Interpret MIC and Disk Values, or Clean Raw R/SI Data
@ -78,6 +78,8 @@
#' The repository of this package [contains a machine-readable version](https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt) of all guidelines. This is a CSV file consisting of `r format(nrow(AMR::rsi_translation), big.mark = ",")` rows and `r ncol(AMR::rsi_translation)` 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. **This allows for easy implementation of these rules in laboratory information systems (LIS)**. Note that it only contains interpretation guidelines for humans - interpretation guidelines from CLSI for animals were removed.
#'
#' ## Other
#'
#' The function [is.rsi()] detects if the input contains class `<rsi>`. If the input is a data.frame, it returns a vector in which all columns are checked for this class.
#'
#' The function [is.rsi.eligible()] returns `TRUE` when a columns contains at most 5% invalid antimicrobial interpretations (not S and/or I and/or R), and `FALSE` otherwise. The threshold of 5% can be set with the `threshold` argument.
#' @section Interpretation of R and S/I:
@ -91,7 +93,7 @@
#' A microorganism is categorised as *Susceptible, Increased exposure* 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.
#'
#' This AMR package honours this new insight. Use [susceptibility()] (equal to [proportion_SI()]) to determine antimicrobial susceptibility and [count_susceptible()] (equal to [count_SI()]) to count susceptible isolates.
#' @return Ordered [factor] with new class [`rsi`]
#' @return Ordered factor with new class `<rsi>`
#' @aliases rsi
#' @export
#' @seealso [as.mic()], [as.disk()], [as.mo()]
@ -189,7 +191,11 @@ as.rsi <- function(x, ...) {
#' @rdname as.rsi
#' @export
is.rsi <- function(x) {
inherits(x, "rsi")
if (inherits(x, "data.frame")) {
unname(vapply(FUN.VALUE = logical(1), x, is.rsi))
} else {
inherits(x, "rsi")
}
}
#' @rdname as.rsi
@ -198,8 +204,7 @@ is.rsi.eligible <- function(x, threshold = 0.05) {
meet_criteria(threshold, allow_class = "numeric", has_length = 1)
stop_if(NCOL(x) > 1, "`x` must be a one-dimensional vector.")
if (any(c("logical",
"numeric",
if (any(c("numeric",
"integer",
"mo",
"ab",
@ -213,13 +218,26 @@ is.rsi.eligible <- function(x, threshold = 0.05) {
%in% class(x))) {
# no transformation needed
return(FALSE)
} else if (!any(c("R", "S", "I") %in% x, na.rm = TRUE)) {
} else if (all(x %in% c("R", "S", "I", NA)) & !all(is.na(x))) {
return(TRUE)
} else if (!any(c("R", "S", "I") %in% x, na.rm = TRUE) & !all(is.na(x))) {
return(FALSE)
} else {
x <- x[!is.na(x) & !is.null(x) & !identical(x, "")]
x <- x[!is.na(x) & !is.null(x) & x != ""]
if (length(x) == 0) {
# no other values than NA or ""
cur_col <- get_current_column()
if (!is.null(cur_col)) {
ab <- suppressWarnings(as.ab(cur_col, fast_mode = TRUE, info = FALSE))
if (!is.na(ab)) {
# this is a valid antibiotic code
return(TRUE)
}
}
# all values empty and no antibiotic col name - return FALSE
return(FALSE)
}
# transform all values and see if it meets the set threshold
checked <- suppressWarnings(as.rsi(x))
outcome <- sum(is.na(checked)) / length(x)
outcome <= threshold

4
R/rsi_calc.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
dots2vars <- function(...) {

4
R/rsi_df.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' @rdname proportion

4
R/skewness.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Skewness of the Sample

BIN
R/sysdata.rda
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Binary file not shown.

4
R/translate.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Translate Strings from AMR Package

4
R/whocc.R
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@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' WHOCC: WHO Collaborating Centre for Drug Statistics Methodology

4
R/zzz.R
View File

@ -1,6 +1,6 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis for R #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
@ -20,7 +20,7 @@
# 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 analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
# set up package environment, used by numerous AMR functions