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knitr format

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dr. M.S. (Matthijs) Berends committed 2023-02-23 16:27:40 +01:00
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DESCRIPTION
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@@ -1,6 +1,6 @@
Package: AMR Package: AMR
Version: 1.8.2.9141 Version: 1.8.2.9142
Date: 2023-02-22 Date: 2023-02-23
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
NAMESPACE
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@@ -131,7 +131,6 @@ S3method(plot,resistance_predict)
S3method(plot,rsi) S3method(plot,rsi)
S3method(plot,sir) S3method(plot,sir)
S3method(print,ab) S3method(print,ab)
S3method(print,antibiogram)
S3method(print,av) S3method(print,av)
S3method(print,bug_drug_combinations) S3method(print,bug_drug_combinations)
S3method(print,custom_eucast_rules) S3method(print,custom_eucast_rules)
NEWS.md
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@@ -1,4 +1,4 @@
# AMR 1.8.2.9141 # AMR 1.8.2.9142
*(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!)*
R/antibiogram.R
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@@ -45,7 +45,7 @@
#' @param sep a separating character for antibiotic columns in combination antibiograms #' @param sep a separating character for antibiotic columns in combination antibiograms
#' @param info a [logical] to indicate info should be printed - the default is `TRUE` only in interactive mode #' @param info a [logical] to indicate info should be printed - the default is `TRUE` only in interactive mode
#' @param object an [antibiogram()] object #' @param object an [antibiogram()] object
#' @param ... when used in [print()]: arguments passed on to [knitr::kable()] (otherwise, has no use) #' @param ... when used in [R Markdown or Quarto][knitr::kable()]: 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.
@@ -103,7 +103,7 @@
#' "Study Group", "Control Group")) #' "Study Group", "Control Group"))
#' ``` #' ```
#' #'
#' All types of antibiograms can be generated with the functions as described on this page, and can be plotted (using [ggplot2::autoplot()] or base \R [plot()]/[barplot()]) or printed into R Markdown / Quarto formats for reports using `print()`. Use functions from specific 'table reporting' packages to transform the output of [antibiogram()] to your needs, e.g. `flextable::as_flextable()` or `gt::gt()`. #' All types of antibiograms can be generated with the functions as described on this page, and can be plotted (using [ggplot2::autoplot()] or base \R [plot()]/[barplot()]) or directly used into R Markdown / Quarto formats for reports (in the last case, [knitr::kable()] will be applied automatically). Use functions from specific 'table reporting' packages to transform the output of [antibiogram()] to your needs, e.g. `flextable::as_flextable()` or `gt::gt()`.
#' #'
#' Note that for combination antibiograms, it is important to realise that susceptibility can be calculated in two ways, which can be set with the `only_all_tested` argument (default is `FALSE`). See this example for two antibiotics, Drug A and Drug B, about how [antibiogram()] works to calculate the %SI: #' Note that for combination antibiograms, it is important to realise that susceptibility can be calculated in two ways, which can be set with the `only_all_tested` argument (default is `FALSE`). See this example for two antibiotics, Drug A and Drug B, about how [antibiogram()] works to calculate the %SI:
#' #'
@@ -215,8 +215,11 @@
#' antibiotics = ureidopenicillins(), #' antibiotics = ureidopenicillins(),
#' ab_transform = "name") #' ab_transform = "name")
#' #'
#' # in an Rmd file, you would just need print(ureido), but to be explicit: #' # in an Rmd file, you would just need to return `ureido` in a chunk,
#' print(ureido, as_kable = TRUE, format = "markdown", italicise = TRUE) #' # but to be explicit here:
#' if (requireNamespace("knitr")) {
#' knitr::knit_print(ureido)
#' }
#' #'
#' #'
#' # Generate plots with ggplot2 or base R -------------------------------- #' # Generate plots with ggplot2 or base R --------------------------------
@@ -489,7 +492,7 @@ antibiogram <- function(x,
} }
if (NCOL(new_df) == edit_col + 1) { if (NCOL(new_df) == edit_col + 1) {
# only 1 antibiotic # only 1 antibiotic
new_df[[edit_col]] <- paste0(new_df[[edit_col]], " (", unlist(lapply(strsplit(count_group, "-"), function(x) x[1])), ")") new_df[[edit_col]] <- paste0(new_df[[edit_col]], " (", unlist(lapply(strsplit(x = count_group, split = "-", fixed = TRUE), function(x) x[1])), ")")
colnames(new_df)[edit_col] <- paste(colnames(new_df)[edit_col], "(N)") colnames(new_df)[edit_col] <- paste(colnames(new_df)[edit_col], "(N)")
} else { } else {
# more than 1 antibiotic # more than 1 antibiotic
@@ -574,48 +577,40 @@ autoplot.antibiogram <- function(object, ...) {
) )
} }
#' @export # will be exported in zzz.R
#' @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 [knitr][knitr::kable()] table should be made italic, using [italicise_taxonomy()]. This only works when the output format is markdown, such as in HTML output.
#' @param italicise (only when `as_kable = TRUE`) 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. #' @param na character to use for showing `NA` values
#' @param na (only when `as_kable = TRUE`) character to use for showing `NA` values
#' @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(), italicise = TRUE, na = getOption("knitr.kable.NA", default = ""), ...) { knit_print.antibiogram <- function(x, italicise = TRUE, na = getOption("knitr.kable.NA", default = ""), ...) {
meet_criteria(as_kable, allow_class = "logical", has_length = 1) stop_ifnot_installed("knitr")
meet_criteria(italicise, allow_class = "logical", has_length = 1) meet_criteria(italicise, allow_class = "logical", has_length = 1)
meet_criteria(na, allow_class = "character", has_length = 1, allow_NA = TRUE) meet_criteria(na, allow_class = "character", has_length = 1, allow_NA = TRUE)
if (isTRUE(as_kable) && old_option <- getOption("knitr.kable.NA")
pkg_is_available("knitr") && options(knitr.kable.NA = na)
# be sure not to run kable in pkgdown for our website generation on.exit(options(knitr.kable.NA = old_option))
!(missing(as_kable) && identical(Sys.getenv("IN_PKGDOWN"), "true"))) { out <- knitr::kable(x, ..., output = FALSE)
old_option <- getOption("knitr.kable.NA")
options(knitr.kable.NA = na)
on.exit(options(knitr.kable.NA = old_option))
out <- knitr::kable(x, ...)
format <- attributes(out)$format
if (!is.null(format) && format %in% c("markdown", "pipe")) {
# try to italicise the output
rows_with_txt <- which(out %like% "[a-z]")
rows_without_txt <- setdiff(seq_len(length(out)), rows_with_txt)
out[rows_with_txt] <- gsub("^[|]", "| ", out[rows_with_txt])
# put hyphen directly after second character
out[rows_without_txt] <- gsub("^[|](.)", "|\\1-", out[rows_without_txt])
out_ita <- italicise_taxonomy(as.character(out), type = "markdown")
if (length(unique(nchar(out_ita))) != 1) {
# so there has been alterations done by italicise_taxonomy()
to_fill <- which(nchar(out_ita) < max(nchar(out_ita)))
out_ita[intersect(to_fill, rows_with_txt)] <- gsub("(^[|].*?)([|])(.*)", "\\1 \\2\\3", out_ita[intersect(to_fill, rows_with_txt)], perl = TRUE)
out_ita[intersect(to_fill, rows_without_txt)] <- gsub("(^[|].*?)([|])(.*)", "\\1--\\2\\3", out_ita[intersect(to_fill, rows_without_txt)], perl = TRUE)
}
attributes(out_ita) <- attributes(out)
out <- out_ita
}
out
} else { format <- attributes(out)$format
# remove 'antibiogram' class and print with default method if (isTRUE(italicise) &&
class(x) <- class(x)[class(x) != "antibiogram"] !is.null(format) &&
print(x, ...) 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
} }
res <- paste(c("", "", out), collapse = "\n")
knitr::asis_output(res)
} }
R/plot.R
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@@ -146,15 +146,15 @@ plot.mic <- function(x,
legend_txt <- character(0) legend_txt <- character(0)
legend_col <- character(0) legend_col <- character(0)
if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) { if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) {
legend_txt <- "Susceptible" legend_txt <- c(legend_txt, "(S) Susceptible")
legend_col <- colours_SIR[1] legend_col <- colours_SIR[1]
} }
if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) { if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
legend_txt <- c(legend_txt, plot_name_of_I(cols_sub$guideline)) legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
legend_col <- c(legend_col, colours_SIR[2]) legend_col <- c(legend_col, colours_SIR[2])
} }
if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) { if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
legend_txt <- c(legend_txt, "Resistant") legend_txt <- c(legend_txt, "(R) Resistant")
legend_col <- c(legend_col, colours_SIR[3]) legend_col <- c(legend_col, colours_SIR[3])
} }
@@ -272,23 +272,25 @@ autoplot.mic <- function(object,
df <- as.data.frame(x, stringsAsFactors = TRUE) df <- as.data.frame(x, stringsAsFactors = TRUE)
colnames(df) <- c("mic", "count") colnames(df) <- c("mic", "count")
df$cols <- cols_sub$cols df$cols <- cols_sub$cols
df$cols[df$cols == colours_SIR[1]] <- "Susceptible" df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
df$cols[df$cols == colours_SIR[2]] <- plot_name_of_I(cols_sub$guideline) df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
df$cols[df$cols == colours_SIR[3]] <- "Resistant" df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
df$cols <- factor(translate_into_language(df$cols, language = language), df$cols <- factor(translate_into_language(df$cols, language = language),
levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"), levels = translate_into_language(c("(S) Susceptible",
language = language paste("(I)", plot_name_of_I(cols_sub$guideline)),
), "(R) Resistant"),
ordered = TRUE language = language
),
ordered = TRUE
) )
p <- ggplot2::ggplot(df) p <- ggplot2::ggplot(df)
if (any(colours_SIR %in% cols_sub$cols)) { if (any(colours_SIR %in% cols_sub$cols)) {
vals <- c( vals <- c(
"Susceptible" = colours_SIR[1], "(S) Susceptible" = colours_SIR[1],
"Susceptible, incr. exp." = colours_SIR[2], "(I) Susceptible, incr. exp." = colours_SIR[2],
"Intermediate" = colours_SIR[2], "(I) Intermediate" = colours_SIR[2],
"Resistant" = colours_SIR[3] "(R) Resistant" = colours_SIR[3]
) )
names(vals) <- translate_into_language(names(vals), language = language) names(vals) <- translate_into_language(names(vals), language = language)
p <- p + p <- p +
@@ -386,15 +388,15 @@ plot.disk <- function(x,
legend_txt <- character(0) legend_txt <- character(0)
legend_col <- character(0) legend_col <- character(0)
if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) { if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
legend_txt <- "Resistant" legend_txt <- "(R) Resistant"
legend_col <- colours_SIR[3] legend_col <- colours_SIR[3]
} }
if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) { if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
legend_txt <- c(legend_txt, plot_name_of_I(cols_sub$guideline)) legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
legend_col <- c(legend_col, colours_SIR[2]) legend_col <- c(legend_col, colours_SIR[2])
} }
if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) { if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) {
legend_txt <- c(legend_txt, "Susceptible") legend_txt <- c(legend_txt, "(S) Susceptible")
legend_col <- c(legend_col, colours_SIR[1]) legend_col <- c(legend_col, colours_SIR[1])
} }
legend("top", legend("top",
@@ -512,11 +514,13 @@ autoplot.disk <- function(object,
colnames(df) <- c("disk", "count") colnames(df) <- c("disk", "count")
df$cols <- cols_sub$cols df$cols <- cols_sub$cols
df$cols[df$cols == colours_SIR[1]] <- "Susceptible" df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
df$cols[df$cols == colours_SIR[2]] <- plot_name_of_I(cols_sub$guideline) df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
df$cols[df$cols == colours_SIR[3]] <- "Resistant" df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
df$cols <- factor(translate_into_language(df$cols, language = language), df$cols <- factor(translate_into_language(df$cols, language = language),
levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"), levels = translate_into_language(c("(S) Susceptible",
paste("(I)", plot_name_of_I(cols_sub$guideline)),
"(R) Resistant"),
language = language language = language
), ),
ordered = TRUE ordered = TRUE
@@ -525,10 +529,10 @@ autoplot.disk <- function(object,
if (any(colours_SIR %in% cols_sub$cols)) { if (any(colours_SIR %in% cols_sub$cols)) {
vals <- c( vals <- c(
"Susceptible" = colours_SIR[1], "(S) Susceptible" = colours_SIR[1],
"Susceptible, incr. exp." = colours_SIR[2], "(I) Susceptible, incr. exp." = colours_SIR[2],
"Intermediate" = colours_SIR[2], "(I) Intermediate" = colours_SIR[2],
"Resistant" = colours_SIR[3] "(R) Resistant" = colours_SIR[3]
) )
names(vals) <- translate_into_language(names(vals), language = language) names(vals) <- translate_into_language(names(vals), language = language)
p <- p + p <- p +
R/sysdata.rda
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R/zzz.R
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@@ -128,6 +128,8 @@ if (utf8_supported && !is_latex) {
s3_register("ggplot2::fortify", "sir") s3_register("ggplot2::fortify", "sir")
s3_register("ggplot2::fortify", "mic") s3_register("ggplot2::fortify", "mic")
s3_register("ggplot2::fortify", "disk") s3_register("ggplot2::fortify", "disk")
# Support for knitr / R Markdown
s3_register("knitr::knit_print", "antibiogram")
# Support vctrs package for use in e.g. dplyr verbs # Support vctrs package for use in e.g. dplyr verbs
# S3: ab_selector # S3: ab_selector
s3_register("vctrs::vec_ptype2", "character.ab_selector") s3_register("vctrs::vec_ptype2", "character.ab_selector")
data-raw/antibiograms.Rmd
+14 -22
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@@ -22,41 +22,33 @@ example_isolates
### Traditional Antibiogram ### Traditional Antibiogram
```{r trad} ```{r trad}
print( antibiogram(example_isolates,
antibiogram(example_isolates, antibiotics = c(aminoglycosides(), carbapenems()))
antibiotics = c(aminoglycosides(), carbapenems()))
)
``` ```
### Combined Antibiogram ### Combined Antibiogram
```{r comb} ```{r comb}
print( antibiogram(example_isolates,
antibiogram(example_isolates, antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
)
``` ```
### Syndromic Antibiogram ### Syndromic Antibiogram
```{r synd} ```{r synd}
print( antibiogram(example_isolates,
antibiogram(example_isolates, antibiotics = c(aminoglycosides(), carbapenems()),
antibiotics = c(aminoglycosides(), carbapenems()), syndromic_group = "ward")
syndromic_group = "ward")
)
``` ```
### Weighted-Incidence Syndromic Combination Antibiogram (WISCA) ### Weighted-Incidence Syndromic Combination Antibiogram (WISCA)
```{r wisca} ```{r wisca}
print( antibiogram(example_isolates,
antibiogram(example_isolates, antibiotics = c("AMC", "AMC+CIP", "TZP", "TZP+TOB"),
antibiotics = c("AMC", "AMC+CIP", "TZP", "TZP+TOB"), mo_transform = "gramstain",
mo_transform = "gramstain", minimum = 10, # this should be >= 30, but now just as example
minimum = 10, # this should be >= 30, but now just as example syndromic_group = ifelse(example_isolates$age >= 65 &
syndromic_group = ifelse(example_isolates$age >= 65 & example_isolates$gender == "M",
example_isolates$gender == "M", "WISCA Group 1", "WISCA Group 2"))
"WISCA Group 1", "WISCA Group 2"))
)
``` ```
data-raw/antibiograms.html
+137 -148
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@@ -11,7 +11,7 @@
<meta name="author" content="AMR package developers" /> <meta name="author" content="AMR package developers" />
<meta name="date" content="2023-02-18" /> <meta name="date" content="2023-02-23" />
<title>Generating antibiograms with the AMR package</title> <title>Generating antibiograms with the AMR package</title>
@@ -299,18 +299,24 @@ overflow-y: auto;
border: 1px solid #ddd; border: 1px solid #ddd;
border-radius: 4px; border-radius: 4px;
} }
.tabset-dropdown > .nav-tabs > li.active:before, .tabset-dropdown > .nav-tabs.nav-tabs-open:before { .tabset-dropdown > .nav-tabs > li.active:before {
content: "\e259"; content: "";
font-family: 'Glyphicons Halflings'; font-family: 'Glyphicons Halflings';
display: inline-block; display: inline-block;
padding: 10px; padding: 10px;
border-right: 1px solid #ddd; border-right: 1px solid #ddd;
} }
.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before { .tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before {
content: "\e258"; content: "";
font-family: 'Glyphicons Halflings';
border: none; border: none;
} }
.tabset-dropdown > .nav-tabs.nav-tabs-open:before {
content: "";
font-family: 'Glyphicons Halflings';
display: inline-block;
padding: 10px;
border-right: 1px solid #ddd;
}
.tabset-dropdown > .nav-tabs > li.active { .tabset-dropdown > .nav-tabs > li.active {
display: block; display: block;
} }
@@ -353,7 +359,7 @@ display: none;
<h1 class="title toc-ignore">Generating antibiograms with the AMR <h1 class="title toc-ignore">Generating antibiograms with the AMR
package</h1> package</h1>
<h4 class="author">AMR package developers</h4> <h4 class="author">AMR package developers</h4>
<h4 class="date">2023-02-18</h4> <h4 class="date">2023-02-23</h4>
</div> </div>
@@ -364,35 +370,34 @@ package</h1>
looks like:</p> looks like:</p>
<pre class="r"><code>example_isolates</code></pre> <pre class="r"><code>example_isolates</code></pre>
<pre><code>## # A tibble: 2,000 × 46 <pre><code>## # A tibble: 2,000 × 46
## date patient age gender ward mo PEN OXA FLC AMX ## date patient age gender ward mo PEN
## &lt;date&gt; &lt;chr&gt; &lt;dbl&gt; &lt;chr&gt; &lt;chr&gt; &lt;mo&gt; &lt;sir&gt; &lt;sir&gt; &lt;sir&gt; &lt;sir&gt; ## &lt;date&gt; &lt;chr&gt; &lt;dbl&gt; &lt;chr&gt; &lt;chr&gt; &lt;mo&gt; &lt;sir&gt;
## 1 2002-01-02 A77334 65 F Clinical B_ESCHR_COLI R NA NA NA ## 1 2002-01-02 A77334 65 F Clini… B_ESCHR_COLI R
## 2 2002-01-03 A77334 65 F Clinical B_ESCHR_COLI R NA NA NA ## 2 2002-01-03 A77334 65 F Clini… B_ESCHR_COLI R
## 3 2002-01-07 067927 45 F ICU B_STPHY_EPDR R NA R NA ## 3 2002-01-07 067927 45 F ICU B_STPHY_EPDR R
## 4 2002-01-07 067927 45 F ICU B_STPHY_EPDR R NA R NA ## 4 2002-01-07 067927 45 F ICU B_STPHY_EPDR R
## 5 2002-01-13 067927 45 F ICU B_STPHY_EPDR R NA R NA ## 5 2002-01-13 067927 45 F ICU B_STPHY_EPDR R
## 6 2002-01-13 067927 45 F ICU B_STPHY_EPDR R NA R NA ## 6 2002-01-13 067927 45 F ICU B_STPHY_EPDR R
## 7 2002-01-14 462729 78 M Clinical B_STPHY_AURS R NA S R ## 7 2002-01-14 462729 78 M Clini… B_STPHY_AURS R
## 8 2002-01-14 462729 78 M Clinical B_STPHY_AURS R NA S R ## 8 2002-01-14 462729 78 M Clini… B_STPHY_AURS R
## 9 2002-01-16 067927 45 F ICU B_STPHY_EPDR R NA R NA ## 9 2002-01-16 067927 45 F ICU B_STPHY_EPDR R
## 10 2002-01-17 858515 79 F ICU B_STPHY_EPDR R NA S NA ## 10 2002-01-17 858515 79 F ICU B_STPHY_EPDR R
## # … with 1,990 more rows, and 36 more variables: AMC &lt;sir&gt;, AMP &lt;sir&gt;, ## # … with 1,990 more rows, and 39 more variables: OXA &lt;sir&gt;,
## # TZP &lt;sir&gt;, CZO &lt;sir&gt;, FEP &lt;sir&gt;, CXM &lt;sir&gt;, FOX &lt;sir&gt;, CTX &lt;sir&gt;, ## # FLC &lt;sir&gt;, AMX &lt;sir&gt;, AMC &lt;sir&gt;, AMP &lt;sir&gt;, TZP &lt;sir&gt;,
## # CAZ &lt;sir&gt;, CRO &lt;sir&gt;, GEN &lt;sir&gt;, TOB &lt;sir&gt;, AMK &lt;sir&gt;, KAN &lt;sir&gt;, ## # CZO &lt;sir&gt;, FEP &lt;sir&gt;, CXM &lt;sir&gt;, FOX &lt;sir&gt;, CTX &lt;sir&gt;,
## # TMP &lt;sir&gt;, SXT &lt;sir&gt;, NIT &lt;sir&gt;, FOS &lt;sir&gt;, LNZ &lt;sir&gt;, CIP &lt;sir&gt;, ## # CAZ &lt;sir&gt;, CRO &lt;sir&gt;, GEN &lt;sir&gt;, TOB &lt;sir&gt;, AMK &lt;sir&gt;,
## # MFX &lt;sir&gt;, VAN &lt;sir&gt;, TEC &lt;sir&gt;, TCY &lt;sir&gt;, TGC &lt;sir&gt;, DOX &lt;sir&gt;, ## # KAN &lt;sir&gt;, TMP &lt;sir&gt;, SXT &lt;sir&gt;, NIT &lt;sir&gt;, FOS &lt;sir&gt;,
## # ERY &lt;sir&gt;, CLI &lt;sir&gt;, AZM &lt;sir&gt;, IPM &lt;sir&gt;, MEM &lt;sir&gt;, MTR &lt;sir&gt;, ## # LNZ &lt;sir&gt;, CIP &lt;sir&gt;, MFX &lt;sir&gt;, VAN &lt;sir&gt;, TEC &lt;sir&gt;,
## # CHL &lt;sir&gt;, COL &lt;sir&gt;, MUP &lt;sir&gt;, RIF &lt;sir&gt;</code></pre> ## # TCY &lt;sir&gt;, TGC &lt;sir&gt;, DOX &lt;sir&gt;, ERY &lt;sir&gt;, …
## # ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names</code></pre>
<div id="traditional-antibiogram" class="section level3"> <div id="traditional-antibiogram" class="section level3">
<h3>Traditional Antibiogram</h3> <h3>Traditional Antibiogram</h3>
<pre class="r"><code>print( <pre class="r"><code>antibiogram(example_isolates,
antibiogram(example_isolates, antibiotics = c(aminoglycosides(), carbapenems()))</code></pre>
antibiotics = c(aminoglycosides(), carbapenems()))
)</code></pre>
<table> <table>
<thead> <thead>
<tr class="header"> <tr class="header">
<th align="left">Pathogen (N min-max)</th> <th align="left">Pathogeen (N min-max)</th>
<th align="right">AMK</th> <th align="right">AMK</th>
<th align="right">GEN</th> <th align="right">GEN</th>
<th align="right">IPM</th> <th align="right">IPM</th>
@@ -403,7 +408,7 @@ looks like:</p>
</thead> </thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="left">CoNS (43-309)</td> <td align="left">CNS (43-309)</td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">86</td> <td align="right">86</td>
<td align="right">52</td> <td align="right">52</td>
@@ -416,7 +421,7 @@ looks like:</p>
<td align="right">100</td> <td align="right">100</td>
<td align="right">98</td> <td align="right">98</td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">97</td> <td align="right">97</td>
</tr> </tr>
@@ -426,70 +431,70 @@ looks like:</p>
<td align="right">0</td> <td align="right">0</td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">0</td> <td align="right">0</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left"><em>K. pneumoniae</em> (0-58)</td> <td align="left"><em>K. pneumoniae</em> (0-58)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">90</td> <td align="right">90</td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">90</td> <td align="right">90</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left"><em>P. aeruginosa</em> (17-30)</td> <td align="left"><em>P. aeruginosa</em> (17-30)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left"><em>P. mirabilis</em> (0-34)</td> <td align="left"><em>P. mirabilis</em> (0-34)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">94</td> <td align="right">94</td>
<td align="right">94</td> <td align="right">94</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">94</td> <td align="right">94</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left"><em>S. aureus</em> (2-233)</td> <td align="left"><em>S. aureus</em> (2-233)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">99</td> <td align="right">99</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">98</td> <td align="right">98</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left"><em>S. epidermidis</em> (8-163)</td> <td align="left"><em>S. epidermidis</em> (8-163)</td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">79</td> <td align="right">79</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">51</td> <td align="right">51</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left"><em>S. hominis</em> (3-80)</td> <td align="left"><em>S. hominis</em> (3-80)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">92</td> <td align="right">92</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">85</td> <td align="right">85</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left"><em>S. pneumoniae</em> (11-117)</td> <td align="left"><em>S. pneumoniae</em> (11-117)</td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">0</td> <td align="right">0</td>
</tr> </tr>
</tbody> </tbody>
@@ -497,14 +502,12 @@ looks like:</p>
</div> </div>
<div id="combined-antibiogram" class="section level3"> <div id="combined-antibiogram" class="section level3">
<h3>Combined Antibiogram</h3> <h3>Combined Antibiogram</h3>
<pre class="r"><code>print( <pre class="r"><code>antibiogram(example_isolates,
antibiogram(example_isolates, antibiotics = c(&quot;TZP&quot;, &quot;TZP+TOB&quot;, &quot;TZP+GEN&quot;))</code></pre>
antibiotics = c(&quot;TZP&quot;, &quot;TZP+TOB&quot;, &quot;TZP+GEN&quot;))
)</code></pre>
<table> <table>
<thead> <thead>
<tr class="header"> <tr class="header">
<th align="left">Pathogen (N min-max)</th> <th align="left">Pathogeen (N min-max)</th>
<th align="right">TZP</th> <th align="right">TZP</th>
<th align="right">TZP + GEN</th> <th align="right">TZP + GEN</th>
<th align="right">TZP + TOB</th> <th align="right">TZP + TOB</th>
@@ -512,10 +515,10 @@ looks like:</p>
</thead> </thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="left">CoNS (29-274)</td> <td align="left">CNS (29-274)</td>
<td align="right">30</td> <td align="right">30</td>
<td align="right">97</td> <td align="right">97</td>
<td align="right">NA</td> <td align="right"></td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left"><em>E. coli</em> (416-461)</td> <td align="left"><em>E. coli</em> (416-461)</td>
@@ -531,31 +534,31 @@ looks like:</p>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left"><em>P. aeruginosa</em> (27-30)</td> <td align="left"><em>P. aeruginosa</em> (27-30)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">100</td> <td align="right">100</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left"><em>P. mirabilis</em> (27-34)</td> <td align="left"><em>P. mirabilis</em> (27-34)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">100</td> <td align="right">100</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left"><em>S. aureus</em> (7-231)</td> <td align="left"><em>S. aureus</em> (7-231)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">100</td> <td align="right">100</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left"><em>S. epidermidis</em> (5-128)</td> <td align="left"><em>S. epidermidis</em> (5-128)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">100</td> <td align="right">100</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left"><em>S. hominis</em> (0-74)</td> <td align="left"><em>S. hominis</em> (0-74)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">100</td> <td align="right">100</td>
</tr> </tr>
@@ -570,26 +573,14 @@ looks like:</p>
</div> </div>
<div id="syndromic-antibiogram" class="section level3"> <div id="syndromic-antibiogram" class="section level3">
<h3>Syndromic Antibiogram</h3> <h3>Syndromic Antibiogram</h3>
<pre class="r"><code>print( <pre class="r"><code>antibiogram(example_isolates,
antibiogram(example_isolates, antibiotics = c(aminoglycosides(), carbapenems()),
antibiotics = c(aminoglycosides(), carbapenems()), syndromic_group = &quot;ward&quot;)</code></pre>
syndromic_group = &quot;ward&quot;)
)</code></pre>
<table> <table>
<colgroup>
<col width="29%" />
<col width="33%" />
<col width="6%" />
<col width="6%" />
<col width="6%" />
<col width="6%" />
<col width="6%" />
<col width="6%" />
</colgroup>
<thead> <thead>
<tr class="header"> <tr class="header">
<th align="left">Syndromic Group</th> <th align="left">Syndroomgroep</th>
<th align="left">Pathogen (N min-max)</th> <th align="left">Pathogeen (N min-max)</th>
<th align="right">AMK</th> <th align="right">AMK</th>
<th align="right">GEN</th> <th align="right">GEN</th>
<th align="right">IPM</th> <th align="right">IPM</th>
@@ -601,33 +592,33 @@ looks like:</p>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="left">Clinical</td> <td align="left">Clinical</td>
<td align="left">CoNS (23-205)</td> <td align="left">CNS (23-205)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">89</td> <td align="right">89</td>
<td align="right">57</td> <td align="right">57</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">57</td> <td align="right">57</td>
<td align="right">26</td> <td align="right">26</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">ICU</td> <td align="left">ICU</td>
<td align="left">CoNS (10-73)</td> <td align="left">CNS (10-73)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">79</td> <td align="right">79</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">Outpatient</td> <td align="left">Outpatient</td>
<td align="left">CoNS (3-31)</td> <td align="left">CNS (3-31)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">84</td> <td align="right">84</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">Clinical</td> <td align="left">Clinical</td>
@@ -635,7 +626,7 @@ looks like:</p>
<td align="right">100</td> <td align="right">100</td>
<td align="right">98</td> <td align="right">98</td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">98</td> <td align="right">98</td>
</tr> </tr>
@@ -645,78 +636,78 @@ looks like:</p>
<td align="right">100</td> <td align="right">100</td>
<td align="right">99</td> <td align="right">99</td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">96</td> <td align="right">96</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">Clinical</td> <td align="left">Clinical</td>
<td align="left">K. <em>pneumoniae</em> (0-51)</td> <td align="left">K. <em>pneumoniae</em> (0-51)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">92</td> <td align="right">92</td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">92</td> <td align="right">92</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">Clinical</td> <td align="left">Clinical</td>
<td align="left">P. <em>mirabilis</em> (0-30)</td> <td align="left">P. <em>mirabilis</em> (0-30)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">Clinical</td> <td align="left">Clinical</td>
<td align="left">S. <em>aureus</em> (2-150)</td> <td align="left">S. <em>aureus</em> (2-150)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">99</td> <td align="right">99</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">97</td> <td align="right">97</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">ICU</td> <td align="left">ICU</td>
<td align="left">S. <em>aureus</em> (0-66)</td> <td align="left">S. <em>aureus</em> (0-66)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">100</td> <td align="right">100</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">Clinical</td> <td align="left">Clinical</td>
<td align="left">S. <em>epidermidis</em> (4-79)</td> <td align="left">S. <em>epidermidis</em> (4-79)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">82</td> <td align="right">82</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">55</td> <td align="right">55</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">ICU</td> <td align="left">ICU</td>
<td align="left">S. <em>epidermidis</em> (4-75)</td> <td align="left">S. <em>epidermidis</em> (4-75)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">72</td> <td align="right">72</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">41</td> <td align="right">41</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">Clinical</td> <td align="left">Clinical</td>
<td align="left">S. <em>hominis</em> (1-45)</td> <td align="left">S. <em>hominis</em> (1-45)</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">96</td> <td align="right">96</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">94</td> <td align="right">94</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
@@ -724,9 +715,9 @@ looks like:</p>
<td align="left">S. <em>pneumoniae</em> (5-78)</td> <td align="left">S. <em>pneumoniae</em> (5-78)</td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">0</td> <td align="right">0</td>
</tr> </tr>
<tr class="even"> <tr class="even">
@@ -734,9 +725,9 @@ looks like:</p>
<td align="left">S. <em>pneumoniae</em> (5-30)</td> <td align="left">S. <em>pneumoniae</em> (5-30)</td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">0</td> <td align="right">0</td>
<td align="right">NA</td> <td align="right"></td>
<td align="right">0</td> <td align="right">0</td>
</tr> </tr>
</tbody> </tbody>
@@ -744,19 +735,17 @@ looks like:</p>
</div> </div>
<div id="weighted-incidence-syndromic-combination-antibiogram-wisca" class="section level3"> <div id="weighted-incidence-syndromic-combination-antibiogram-wisca" class="section level3">
<h3>Weighted-Incidence Syndromic Combination Antibiogram (WISCA)</h3> <h3>Weighted-Incidence Syndromic Combination Antibiogram (WISCA)</h3>
<pre class="r"><code>print( <pre class="r"><code>antibiogram(example_isolates,
antibiogram(example_isolates, antibiotics = c(&quot;AMC&quot;, &quot;AMC+CIP&quot;, &quot;TZP&quot;, &quot;TZP+TOB&quot;),
antibiotics = c(&quot;AMC&quot;, &quot;AMC+CIP&quot;, &quot;TZP&quot;, &quot;TZP+TOB&quot;), mo_transform = &quot;gramstain&quot;,
mo_transform = &quot;gramstain&quot;, minimum = 10, # this should be &gt;= 30, but now just as example
minimum = 10, # this should be &gt;= 30, but now just as example syndromic_group = ifelse(example_isolates$age &gt;= 65 &amp;
syndromic_group = ifelse(example_isolates$age &gt;= 65 &amp; example_isolates$gender == &quot;M&quot;,
example_isolates$gender == &quot;M&quot;, &quot;WISCA Group 1&quot;, &quot;WISCA Group 2&quot;))</code></pre>
&quot;WISCA Group 1&quot;, &quot;WISCA Group 2&quot;)) <table style="width:100%;">
)</code></pre>
<table>
<colgroup> <colgroup>
<col width="24%" /> <col width="22%" />
<col width="34%" /> <col width="35%" />
<col width="5%" /> <col width="5%" />
<col width="14%" /> <col width="14%" />
<col width="5%" /> <col width="5%" />
@@ -764,8 +753,8 @@ looks like:</p>
</colgroup> </colgroup>
<thead> <thead>
<tr class="header"> <tr class="header">
<th align="left">Syndromic Group</th> <th align="left">Syndroomgroep</th>
<th align="left">Pathogen (N min-max)</th> <th align="left">Pathogeen (N min-max)</th>
<th align="right">AMC</th> <th align="right">AMC</th>
<th align="right">AMC + CIP</th> <th align="right">AMC + CIP</th>
<th align="right">TZP</th> <th align="right">TZP</th>
@@ -775,7 +764,7 @@ looks like:</p>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="left">WISCA Group 1</td> <td align="left">WISCA Group 1</td>
<td align="left">Gram-negative (261-285)</td> <td align="left">Gram-negatief (261-285)</td>
<td align="right">76</td> <td align="right">76</td>
<td align="right">95</td> <td align="right">95</td>
<td align="right">89</td> <td align="right">89</td>
@@ -783,7 +772,7 @@ looks like:</p>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">WISCA Group 2</td> <td align="left">WISCA Group 2</td>
<td align="left">Gram-negative (380-442)</td> <td align="left">Gram-negatief (380-442)</td>
<td align="right">76</td> <td align="right">76</td>
<td align="right">98</td> <td align="right">98</td>
<td align="right">88</td> <td align="right">88</td>
@@ -791,7 +780,7 @@ looks like:</p>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">WISCA Group 1</td> <td align="left">WISCA Group 1</td>
<td align="left">Gram-positive (123-406)</td> <td align="left">Gram-positief (123-406)</td>
<td align="right">76</td> <td align="right">76</td>
<td align="right">89</td> <td align="right">89</td>
<td align="right">81</td> <td align="right">81</td>
@@ -799,7 +788,7 @@ looks like:</p>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">WISCA Group 2</td> <td align="left">WISCA Group 2</td>
<td align="left">Gram-positive (222-732)</td> <td align="left">Gram-positief (222-732)</td>
<td align="right">76</td> <td align="right">76</td>
<td align="right">89</td> <td align="right">89</td>
<td align="right">88</td> <td align="right">88</td>
man/antibiogram.Rd
+11 -13
View File
@@ -4,7 +4,7 @@
\alias{antibiogram} \alias{antibiogram}
\alias{plot.antibiogram} \alias{plot.antibiogram}
\alias{autoplot.antibiogram} \alias{autoplot.antibiogram}
\alias{print.antibiogram} \alias{knit_print.antibiogram}
\title{Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA)} \title{Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA)}
\source{ \source{
\itemize{ \itemize{
@@ -35,9 +35,8 @@ antibiogram(
\method{autoplot}{antibiogram}(object, ...) \method{autoplot}{antibiogram}(object, ...)
\method{print}{antibiogram}( knit_print.antibiogram(
x, x,
as_kable = !interactive(),
italicise = TRUE, italicise = TRUE,
na = getOption("knitr.kable.NA", default = ""), na = getOption("knitr.kable.NA", default = ""),
... ...
@@ -72,15 +71,13 @@ antibiogram(
\item{info}{a \link{logical} to indicate info should be printed - the default is \code{TRUE} only in interactive mode} \item{info}{a \link{logical} to indicate info should be printed - the default is \code{TRUE} only in interactive mode}
\item{...}{when used in \code{\link[=print]{print()}}: arguments passed on to \code{\link[knitr:kable]{knitr::kable()}} (otherwise, has no use)} \item{...}{when used in \link[knitr:kable]{R Markdown or Quarto}: 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{italicise}{a \link{logical} to indicate whether the microorganism names in the \link[knitr:kable]{knitr} 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.}
\item{italicise}{(only when \code{as_kable = TRUE}) 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.} \item{na}{character to use for showing \code{NA} values}
\item{na}{(only when \code{as_kable = TRUE}) character to use for showing \code{NA} values}
} }
\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.
@@ -137,7 +134,7 @@ your_data \%>\%
}\if{html}{\out{</div>}} }\if{html}{\out{</div>}}
} }
All types of antibiograms can be generated with the functions as described on this page, and can be plotted (using \code{\link[ggplot2:autoplot]{ggplot2::autoplot()}} or base \R \code{\link[=plot]{plot()}}/\code{\link[=barplot]{barplot()}}) or printed into R Markdown / Quarto formats for reports using \code{print()}. Use functions from specific 'table reporting' packages to transform the output of \code{\link[=antibiogram]{antibiogram()}} to your needs, e.g. \code{flextable::as_flextable()} or \code{gt::gt()}. All types of antibiograms can be generated with the functions as described on this page, and can be plotted (using \code{\link[ggplot2:autoplot]{ggplot2::autoplot()}} or base \R \code{\link[=plot]{plot()}}/\code{\link[=barplot]{barplot()}}) or directly used into R Markdown / Quarto formats for reports (in the last case, \code{\link[knitr:kable]{knitr::kable()}} will be applied automatically). Use functions from specific 'table reporting' packages to transform the output of \code{\link[=antibiogram]{antibiogram()}} to your needs, e.g. \code{flextable::as_flextable()} or \code{gt::gt()}.
Note that for combination antibiograms, it is important to realise that susceptibility can be calculated in two ways, which can be set with the \code{only_all_tested} argument (default is \code{FALSE}). See this example for two antibiotics, Drug A and Drug B, about how \code{\link[=antibiogram]{antibiogram()}} works to calculate the \%SI: Note that for combination antibiograms, it is important to realise that susceptibility can be calculated in two ways, which can be set with the \code{only_all_tested} argument (default is \code{FALSE}). See this example for two antibiotics, Drug A and Drug B, about how \code{\link[=antibiogram]{antibiogram()}} works to calculate the \%SI:
@@ -158,8 +155,6 @@ Note that for combination antibiograms, it is important to realise that suscepti
<NA> <NA> - - - - <NA> <NA> - - - -
-------------------------------------------------------------------- --------------------------------------------------------------------
}\if{html}{\out{</div>}} }\if{html}{\out{</div>}}
Printing the antibiogram in non-interactive sessions will be done by \code{\link[knitr:kable]{knitr::kable()}}, with support for \link[knitr:kable]{all their implemented formats}, such as "markdown". The knitr format will be automatically determined if printed inside a knitr document (LaTeX, HTML, etc.).
} }
\examples{ \examples{
# example_isolates is a data set available in the AMR package. # example_isolates is a data set available in the AMR package.
@@ -244,8 +239,11 @@ ureido <- antibiogram(example_isolates,
antibiotics = ureidopenicillins(), antibiotics = ureidopenicillins(),
ab_transform = "name") ab_transform = "name")
# in an Rmd file, you would just need print(ureido), but to be explicit: # in an Rmd file, you would just need to return `ureido` in a chunk,
print(ureido, as_kable = TRUE, format = "markdown", italicise = TRUE) # but to be explicit here:
if (requireNamespace("knitr")) {
knitr::knit_print(ureido)
}
# Generate plots with ggplot2 or base R -------------------------------- # Generate plots with ggplot2 or base R --------------------------------