# ==================================================================== # # 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} #' #' Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal \code{\link[ggplot2]{ggplot}} functions. #' @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"} #' @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}} #' @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. #' #' \code{facet_rsi} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2]{facet_wrap}}. #' #' \code{scale_y_percent} transforms the y axis to a 0 to 100\% range. #' #' \code{scale_rsi_colours} sets colours to the bars: green for S, yellow for I and red for R. #' #' \code{theme_rsi} is a \code{\link[ggplot2]{theme}} with minimal distraction. #' #' \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() #' #' # prettify the plot using some additional functions: #' df <- septic_patients[, c("amox", "nitr", "fosf", "trim", "cipr")] #' ggplot(df) + #' geom_rsi() + #' facet_rsi() + #' 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() #' \donttest{ #' # it also supports groups (don't forget to use the group on `x` or `facet`): #' septic_patients %>% #' 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") #' #' # genuine analysis: check 2 most prevalent microorganisms #' septic_patients %>% #' # 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") #' } ggplot_rsi <- function(data, position = "stack", x = "Antibiotic", fill = "Interpretation", facet = NULL, translate_ab = "official", ...) { if (!"ggplot2" %in% rownames(installed.packages())) { stop('this function requires the ggplot2 package.', call. = FALSE) } p <- ggplot2::ggplot(data = data) + geom_rsi(position = position, x = x, fill = fill, translate_ab = translate_ab) + scale_y_percent() + theme_rsi() if (fill == "Interpretation") { # set RSI colours p <- p + scale_rsi_colours() } if (!is.null(facet)) { p <- p + facet_rsi(facet = facet, ...) } p } #' @rdname ggplot_rsi #' @export geom_rsi <- function(position = "stack", x = c("Antibiotic", "Interpretation"), fill = "Interpretation", translate_ab = "official") { x <- x[1] if (x %in% tolower(c('ab', 'antibiotic', 'abx', 'antibiotics'))) { x <- "Antibiotic" } else if (x %in% tolower(c('SIR', 'RSI', 'interpretation', 'interpretations', 'result'))) { x <- "Interpretation" } options(get_antibiotic_names = translate_ab) ggplot2::layer(geom = "bar", stat = "identity", position = position, mapping = ggplot2::aes_string(x = x, y = "Percentage", fill = fill), data = AMR::portion_df, params = list()) } #' @rdname ggplot_rsi #' @export facet_rsi <- function(facet = c("Interpretation", "Antibiotic"), ...) { facet <- facet[1] if (facet %in% tolower(c('SIR', 'RSI', 'interpretation', 'interpretations', 'result'))) { facet <- "Interpretation" } else if (facet %in% tolower(c('ab', 'antibiotic', 'abx', 'antibiotics'))) { facet <- "Antibiotic" } ggplot2::facet_wrap(facets = facet, scales = "free", ...) } #' @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")) }