italicise antibiogram

This commit is contained in:
dr. M.S. (Matthijs) Berends 2023-02-17 09:42:51 +01:00
parent db2830124f
commit 714a048fa9
5 changed files with 80 additions and 41 deletions

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@ -1,6 +1,6 @@
Package: AMR Package: AMR
Version: 1.8.2.9131 Version: 1.8.2.9132
Date: 2023-02-15 Date: 2023-02-17
Title: Antimicrobial Resistance Data Analysis Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) Description: Functions to simplify and standardise antimicrobial resistance (AMR)
data analysis and to work with microbial and antimicrobial properties by data analysis and to work with microbial and antimicrobial properties by

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@ -1,4 +1,4 @@
# AMR 1.8.2.9131 # AMR 1.8.2.9132
*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)* *(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*

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@ -44,7 +44,7 @@
#' @param combine_SI a [logical] to indicate whether all susceptibility should be determined by results of either S or I, instead of only S (defaults to `TRUE`) #' @param combine_SI a [logical] to indicate whether all susceptibility should be determined by results of either S or I, instead of only S (defaults to `TRUE`)
#' @param sep a separating character for antibiotic columns in combination antibiograms #' @param sep a separating character for antibiotic columns in combination antibiograms
#' @param object an [antibiogram()] object #' @param object an [antibiogram()] object
#' @param ... method extensions #' @param ... when used in [print()]: arguments passed on to [knitr::kable()] (otherwise, has no use)
#' @details This function returns a table with values between 0 and 100 for *susceptibility*, not resistance. #' @details This function returns a table with values between 0 and 100 for *susceptibility*, not resistance.
#' #'
#' **Remember that you should filter your data to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set with one of the four available algorithms. #' **Remember that you should filter your data to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set with one of the four available algorithms.
@ -208,7 +208,16 @@
#' ) #' )
#' ) #' )
#' #'
#' #' # Print the output for R Markdown / Quarto -----------------------------
#'
#' ureido <- antibiogram(example_isolates,
#' antibiotics = ureidopenicillins(),
#' ab_transform = "name")
#'
#' # in an Rmd file, you would just need print(ureido), but to be explicit:
#' print(ureido, as_kable = TRUE, format = "markdown", italicise = TRUE)
#'
#'
#' # Generate plots with ggplot2 or base R -------------------------------- #' # Generate plots with ggplot2 or base R --------------------------------
#' #'
#' ab1 <- antibiogram(example_isolates, #' ab1 <- antibiogram(example_isolates,
@ -221,17 +230,16 @@
#' syndromic_group = "ward" #' syndromic_group = "ward"
#' ) #' )
#' #'
#' plot(ab1)
#'
#' if (requireNamespace("ggplot2")) { #' if (requireNamespace("ggplot2")) {
#' ggplot2::autoplot(ab1) #' ggplot2::autoplot(ab1)
#' } #' }
#'
#' plot(ab2)
#'
#' if (requireNamespace("ggplot2")) { #' if (requireNamespace("ggplot2")) {
#' ggplot2::autoplot(ab2) #' ggplot2::autoplot(ab2)
#' } #' }
#'
#' plot(ab1)
#' plot(ab2)
#'
#' } #' }
antibiogram <- function(x, antibiogram <- function(x,
antibiotics = where(is.sir), antibiotics = where(is.sir),
@ -540,18 +548,37 @@ autoplot.antibiogram <- function(object, ...) {
#' @export #' @export
#' @param as_kable a [logical] to indicate whether the printing should be done using [knitr::kable()] (which is the default in non-interactive sessions) #' @param as_kable a [logical] to indicate whether the printing should be done using [knitr::kable()] (which is the default in non-interactive sessions)
#' @param italicise a [logical] to indicate whether the microorganism names in the output table should be made italic, using [italicise_taxonomy()]. This only works when the output format is markdown, such as in HTML output.
#' @details Printing the antibiogram in non-interactive sessions will be done by [knitr::kable()], with support for [all their implemented formats][knitr::kable()], such as "markdown". The knitr format will be automatically determined if printed inside a knitr document (LaTeX, HTML, etc.). #' @details Printing the antibiogram in non-interactive sessions will be done by [knitr::kable()], with support for [all their implemented formats][knitr::kable()], such as "markdown". The knitr format will be automatically determined if printed inside a knitr document (LaTeX, HTML, etc.).
#' @rdname antibiogram #' @rdname antibiogram
print.antibiogram <- function(x, as_kable = !interactive(), ...) { print.antibiogram <- function(x, as_kable = !interactive(), italicise = TRUE, ...) {
meet_criteria(as_kable, allow_class = "logical", has_length = 1) meet_criteria(as_kable, allow_class = "logical", has_length = 1)
meet_criteria(italicise, allow_class = "logical", has_length = 1)
kable <- import_fn("kable", "knitr", error_on_fail = FALSE)
if (!is.null(kable) && if (isTRUE(as_kable) &&
isTRUE(as_kable) &&
# be sure not to run kable in pkgdown for our website generation # be sure not to run kable in pkgdown for our website generation
!identical(Sys.getenv("IN_PKGDOWN"), "true")) { !(missing(as_kable) && identical(Sys.getenv("IN_PKGDOWN"), "true"))) {
kable(x, ...) out <- knitr::kable(x, ...)
format <- attributes(out)$format
if (!is.null(format) && format %in% c("markdown", "pipe")) {
# try to italicise the output
rows_with_txt <- which(out %like% "[a-z]")
rows_without_txt <- setdiff(seq_len(length(out)), rows_with_txt)
out[rows_with_txt] <- gsub("^[|]", "| ", out[rows_with_txt])
# put hyphen directly after second character
out[rows_without_txt] <- gsub("^[|](.)", "|\\1-", out[rows_without_txt])
out_ita <- italicise_taxonomy(as.character(out), type = "markdown")
if (length(unique(nchar(out_ita))) != 1) {
# so there has been alterations done by italicise_taxonomy()
to_fill <- which(nchar(out_ita) < max(nchar(out_ita)))
out_ita[intersect(to_fill, rows_with_txt)] <- gsub("(^[|].*?)([|])(.*)", "\\1 \\2\\3", out_ita[intersect(to_fill, rows_with_txt)], perl = TRUE)
out_ita[intersect(to_fill, rows_without_txt)] <- gsub("(^[|].*?)([|])(.*)", "\\1--\\2\\3", out_ita[intersect(to_fill, rows_without_txt)], perl = TRUE)
}
attributes(out_ita) <- attributes(out)
out <- out_ita
}
out
} else { } else {
# remove 'antibiogram' class and print with default method # remove 'antibiogram' class and print with default method
class(x) <- class(x)[class(x) != "antibiogram"] class(x) <- class(x)[class(x) != "antibiogram"]

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@ -85,18 +85,18 @@ antibiogram(example_isolates,
antibiotics = c(aminoglycosides(), carbapenems())) antibiotics = c(aminoglycosides(), carbapenems()))
``` ```
|Pathogen (N min-max) | AMK| GEN| IPM| KAN| MEM| TOB| |Pathogen (N min-max) | AMK| GEN| IPM| KAN| MEM| TOB|
|:----------------------|---:|---:|---:|---:|---:|---:| |:------------------------|---:|---:|---:|---:|---:|---:|
|CoNS (43-309) | 0| 86| 52| 0| 52| 22| |CoNS (43-309) | 0| 86| 52| 0| 52| 22|
|E. coli (0-462) | 100| 98| 100| NA| 100| 97| |*E. coli* (0-462) | 100| 98| 100| | 100| 97|
|E. faecalis (0-39) | 0| 0| 100| 0| NA| 0| |*E. faecalis* (0-39) | 0| 0| 100| 0| | 0|
|K. pneumoniae (0-58) | NA| 90| 100| NA| 100| 90| |*K. pneumoniae* (0-58) | | 90| 100| | 100| 90|
|P. aeruginosa (17-30) | NA| 100| NA| 0| NA| 100| |*P. aeruginosa* (17-30) | | 100| | 0| | 100|
|P. mirabilis (0-34) | NA| 94| 94| NA| NA| 94| |*P. mirabilis* (0-34) | | 94| 94| | | 94|
|S. aureus (2-233) | NA| 99| NA| NA| NA| 98| |*S. aureus* (2-233) | | 99| | | | 98|
|S. epidermidis (8-163) | 0| 79| NA| 0| NA| 51| |*S. epidermidis* (8-163) | 0| 79| | 0| | 51|
|S. hominis (3-80) | NA| 92| NA| NA| NA| 85| |*S. hominis* (3-80) | | 92| | | | 85|
|S. pneumoniae (11-117) | 0| 0| NA| 0| NA| 0| |*S. pneumoniae* (11-117) | 0| 0| | 0| | 0|
In combination antibiograms, it is clear that combined antibiotics yield higher empiric coverage: In combination antibiograms, it is clear that combined antibiotics yield higher empiric coverage:
@ -111,7 +111,7 @@ antibiogram(example_isolates,
|Gram-negative (641-693) | 88| 99| 98| |Gram-negative (641-693) | 88| 99| 98|
|Gram-positive (345-1044) | 86| 98| 95| |Gram-positive (345-1044) | 86| 98| 95|
Like many other functions in this package, `antibiograms()` comes with support for 20 languages that are often detected automatically based on system language: Like many other functions in this package, `antibiogram()` comes with support for 20 languages that are often detected automatically based on system language:
```r ```r
antibiogram(example_isolates, antibiogram(example_isolates,
@ -129,6 +129,8 @@ antibiogram(example_isolates,
#### Calculating resistance per group #### Calculating resistance per group
For a manual approach, you can use the `resistance` or `susceptibility()` function:
```r ```r
library(AMR) library(AMR)
library(dplyr) library(dplyr)
@ -147,7 +149,7 @@ out
|:-----------|------:|------:|------:|------:|------:| |:-----------|------:|------:|------:|------:|------:|
| Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 | | Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 |
| ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 | | ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 |
| Outpatient | 0.200 | 0.368 | 0.605 | NA | 0.889 | | Outpatient | 0.200 | 0.368 | 0.605 | | 0.889 |
```r ```r
# transform the antibiotic columns to names: # transform the antibiotic columns to names:
@ -158,7 +160,7 @@ out %>% set_ab_names()
|:-----------|-----------:|-----------:|----------|----------:|----------:| |:-----------|-----------:|-----------:|----------|----------:|----------:|
| Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 | | Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 |
| ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 | | ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 |
| Outpatient | 0.200 | 0.368 | 0.605 | NA | 0.889 | | Outpatient | 0.200 | 0.368 | 0.605 | | 0.889 |
```r ```r
# transform the antibiotic column to ATC codes: # transform the antibiotic column to ATC codes:
@ -169,7 +171,7 @@ out %>% set_ab_names(property = "atc")
|:-----------|-----------:|-----------:|----------|----------:|----------:| |:-----------|-----------:|-----------:|----------|----------:|----------:|
| Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 | | Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 |
| ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 | | ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 |
| Outpatient | 0.200 | 0.368 | 0.605 | NA | 0.889 | | Outpatient | 0.200 | 0.368 | 0.605 | | 0.889 |
### What else can you do with this package? ### What else can you do with this package?

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@ -34,7 +34,7 @@ antibiogram(
\method{autoplot}{antibiogram}(object, ...) \method{autoplot}{antibiogram}(object, ...)
\method{print}{antibiogram}(x, as_kable = !interactive(), ...) \method{print}{antibiogram}(x, as_kable = !interactive(), italicise = TRUE, ...)
} }
\arguments{ \arguments{
\item{x}{a \link{data.frame} containing at least a column with microorganisms and columns with antibiotic results (class 'sir', see \code{\link[=as.sir]{as.sir()}})} \item{x}{a \link{data.frame} containing at least a column with microorganisms and columns with antibiotic results (class 'sir', see \code{\link[=as.sir]{as.sir()}})}
@ -63,11 +63,13 @@ antibiogram(
\item{sep}{a separating character for antibiotic columns in combination antibiograms} \item{sep}{a separating character for antibiotic columns in combination antibiograms}
\item{...}{method extensions} \item{...}{when used in \code{\link[=print]{print()}}: arguments passed on to \code{\link[knitr:kable]{knitr::kable()}} (otherwise, has no use)}
\item{object}{an \code{\link[=antibiogram]{antibiogram()}} object} \item{object}{an \code{\link[=antibiogram]{antibiogram()}} object}
\item{as_kable}{a \link{logical} to indicate whether the printing should be done using \code{\link[knitr:kable]{knitr::kable()}} (which is the default in non-interactive sessions)} \item{as_kable}{a \link{logical} to indicate whether the printing should be done using \code{\link[knitr:kable]{knitr::kable()}} (which is the default in non-interactive sessions)}
\item{italicise}{a \link{logical} to indicate whether the microorganism names in the output table should be made italic, using \code{\link[=italicise_taxonomy]{italicise_taxonomy()}}. This only works when the output format is markdown, such as in HTML output.}
} }
\description{ \description{
Generate an antibiogram, and communicate the results in plots or tables. These functions follow the logic of Klinker \emph{et al.} and Barbieri \emph{et al.} (see \emph{Source}), and allow reporting in e.g. R Markdown and Quarto as well. Generate an antibiogram, and communicate the results in plots or tables. These functions follow the logic of Klinker \emph{et al.} and Barbieri \emph{et al.} (see \emph{Source}), and allow reporting in e.g. R Markdown and Quarto as well.
@ -225,6 +227,15 @@ antibiogram(example_isolates,
) )
) )
# Print the output for R Markdown / Quarto -----------------------------
ureido <- antibiogram(example_isolates,
antibiotics = ureidopenicillins(),
ab_transform = "name")
# in an Rmd file, you would just need print(ureido), but to be explicit:
print(ureido, as_kable = TRUE, format = "markdown", italicise = TRUE)
# Generate plots with ggplot2 or base R -------------------------------- # Generate plots with ggplot2 or base R --------------------------------
@ -238,16 +249,15 @@ ab2 <- antibiogram(example_isolates,
syndromic_group = "ward" syndromic_group = "ward"
) )
plot(ab1)
if (requireNamespace("ggplot2")) { if (requireNamespace("ggplot2")) {
ggplot2::autoplot(ab1) ggplot2::autoplot(ab1)
} }
plot(ab2)
if (requireNamespace("ggplot2")) { if (requireNamespace("ggplot2")) {
ggplot2::autoplot(ab2) ggplot2::autoplot(ab2)
} }
plot(ab1)
plot(ab2)
} }
} }