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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
# AUTHORS #
# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
# #
# LICENCE #
# This program is free software; you can redistribute it and/or modify #
# it under the terms of the GNU General Public License version 2.0, #
# as published by the Free Software Foundation. #
# #
# This program is distributed in the hope that it will be useful, #
# but WITHOUT ANY WARRANTY; without even the implied warranty of #
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
# GNU General Public License for more details. #
# ==================================================================== #
#' AMR bar plots with \code{ggplot}
#'
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#' Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal \code{\link[ggplot2]{ggplot}} functions.
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#' @param data a \code{data.frame} with column(s) of class \code{"rsi"} (see \code{\link{as.rsi}})
#' @param position position adjustment of bars, either \code{"stack"} (default) or \code{"dodge"}
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#' @param x variable to show on x axis, either \code{"Antibiotic"} (default) or \code{"Interpretation"} or a grouping variable
#' @param fill variable to categorise using the plots legend, either \code{"Antibiotic"} (default) or \code{"Interpretation"} or a grouping variable
#' @param facet variable to split plots by, either \code{"Interpretation"} (default) or \code{"Antibiotic"} or a grouping variable
#' @param translate_ab a column name of the \code{\link{antibiotics}} data set to translate the antibiotic abbreviations into, using \code{\link{abname}}. Default behaviour is to translate to official names according to the WHO. Use \code{translate_ab = FALSE} to disable translation.
#' @param ... other parameters passed on to \code{\link[ggplot2]{facet_wrap}}
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#' @details At default, the names of antibiotics will be shown on the plots using \code{\link{abname}}. This can be set with the option \code{get_antibiotic_names} (a logical value), so change it e.g. to \code{FALSE} with \code{options(get_antibiotic_names = FALSE)}.
#'
#' \strong{The functions}\cr
#' \code{geom_rsi} will take any variable from the data that has an \code{rsi} class (created with \code{\link{as.rsi}}) using \code{\link{portion_df}} and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.
#'
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#' \code{facet_rsi} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2]{facet_wrap}}.
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#'
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#' \code{scale_y_percent} transforms the y axis to a 0 to 100\% range.
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#'
#' \code{scale_rsi_colours} sets colours to the bars: green for S, yellow for I and red for R.
#'
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#' \code{theme_rsi} is a \code{\link[ggplot2]{theme}} with minimal distraction.
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#'
#' \code{ggplot_rsi} is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (\code{\%>\%}). See Examples.
#' @rdname ggplot_rsi
#' @export
#' @examples
#' library(dplyr)
#' library(ggplot2)
#'
#' # get antimicrobial results for drugs against a UTI:
#' ggplot(septic_patients %>% select(amox, nitr, fosf, trim, cipr)) +
#' geom_rsi()
#'
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#' # prettify the plot using some additional functions:
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#' df <- septic_patients[, c("amox", "nitr", "fosf", "trim", "cipr")]
#' ggplot(df) +
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#' geom_rsi() +
#' facet_rsi() +
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#' scale_y_percent() +
#' scale_rsi_colours() +
#' theme_rsi()
#'
#' # or better yet, simplify this using the wrapper function - a single command:
#' septic_patients %>%
#' select(amox, nitr, fosf, trim, cipr) %>%
#' ggplot_rsi()
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#' \donttest{
#' # it also supports groups (don't forget to use the group on `x` or `facet`):
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#' septic_patients %>%
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#' select(hospital_id, amox, nitr, fosf, trim, cipr) %>%
#' group_by(hospital_id) %>%
#' ggplot_rsi(x = "hospital_id",
#' facet = "Antibiotic",
#' nrow = 1) +
#' labs(title = "AMR of Anti-UTI Drugs Per Hospital",
#' x = "Hospital")
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#'
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#' # genuine analysis: check 2 most prevalent microorganisms
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#' septic_patients %>%
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#' # create new bacterial ID's, with all CoNS under the same group (Becker et al.)
#' mutate(bactid = as.bactid(bactid, Becker = TRUE)) %>%
#' # filter on top 2 bacterial ID's
#' filter(bactid %in% top_freq(freq(.$bactid), 2)) %>%
#' # determine first isolates
#' mutate(first_isolate = first_isolate(.,
#' col_date = "date",
#' col_patient_id = "patient_id",
#' col_bactid = "bactid")) %>%
#' # filter on first isolates
#' filter(first_isolate == TRUE) %>%
#' # join the `microorganisms` data set
#' left_join_microorganisms() %>%
#' # select full name and some antiseptic drugs
#' select(mo = fullname,
#' cfur, gent, cipr) %>%
#' # group by MO
#' group_by(mo) %>%
#' # plot the thing, putting MOs on the facet
#' ggplot_rsi(x = "Antibiotic",
#' facet = "mo") +
#' labs(title = "AMR of Top Two Microorganisms In Blood Culture Isolates",
#' subtitle = "Only First Isolates, CoNS grouped according to Becker et al.",
#' x = "Microorganisms")
#' }
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ggplot_rsi <- function ( data ,
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position = " stack" ,
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x = " Antibiotic" ,
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fill = " Interpretation" ,
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facet = NULL ,
translate_ab = " official" ,
... ) {
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if ( ! " ggplot2" %in% rownames ( installed.packages ( ) ) ) {
stop ( ' this function requires the ggplot2 package.' , call. = FALSE )
}
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p <- ggplot2 :: ggplot ( data = data ) +
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geom_rsi ( position = position , x = x , fill = fill , translate_ab = translate_ab ) +
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scale_y_percent ( ) +
theme_rsi ( )
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if ( fill == " Interpretation" ) {
# set RSI colours
p <- p + scale_rsi_colours ( )
}
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if ( ! is.null ( facet ) ) {
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p <- p + facet_rsi ( facet = facet , ... )
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}
p
}
#' @rdname ggplot_rsi
#' @export
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geom_rsi <- function ( position = " stack" ,
x = c ( " Antibiotic" , " Interpretation" ) ,
fill = " Interpretation" ,
translate_ab = " official" ) {
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x <- x [1 ]
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if ( x %in% tolower ( c ( ' ab' , ' antibiotic' , ' abx' , ' antibiotics' ) ) ) {
x <- " Antibiotic"
} else if ( x %in% tolower ( c ( ' SIR' , ' RSI' , ' interpretation' , ' interpretations' , ' result' ) ) ) {
x <- " Interpretation"
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}
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options ( get_antibiotic_names = translate_ab )
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ggplot2 :: layer ( geom = " bar" , stat = " identity" , position = position ,
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mapping = ggplot2 :: aes_string ( x = x , y = " Percentage" , fill = fill ) ,
data = AMR :: portion_df , params = list ( ) )
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}
#' @rdname ggplot_rsi
#' @export
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facet_rsi <- function ( facet = c ( " Interpretation" , " Antibiotic" ) , ... ) {
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facet <- facet [1 ]
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if ( facet %in% tolower ( c ( ' SIR' , ' RSI' , ' interpretation' , ' interpretations' , ' result' ) ) ) {
facet <- " Interpretation"
} else if ( facet %in% tolower ( c ( ' ab' , ' antibiotic' , ' abx' , ' antibiotics' ) ) ) {
facet <- " Antibiotic"
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}
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ggplot2 :: facet_wrap ( facets = facet , scales = " free" , ... )
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}
#' @rdname ggplot_rsi
#' @export
scale_y_percent <- function ( ) {
ggplot2 :: scale_y_continuous ( name = " Percentage" ,
breaks = seq ( 0 , 1 , 0.1 ) ,
limits = c ( 0 , 1 ) ,
labels = percent ( seq ( 0 , 1 , 0.1 ) ) )
}
#' @rdname ggplot_rsi
#' @export
scale_rsi_colours <- function ( ) {
ggplot2 :: scale_fill_brewer ( palette = " RdYlGn" )
}
#' @rdname ggplot_rsi
#' @export
theme_rsi <- function ( ) {
theme_minimal ( ) +
theme ( panel.grid.major.x = element_blank ( ) ,
panel.grid.minor = element_blank ( ) ,
panel.grid.major.y = element_line ( colour = " grey75" ) )
}