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#' Compares viabilities at a given dose over different experimental durations
#'
#' This function generates a plot visualizing the relationship between gene
#' expression, time and dose level for the selected tSet. The plot is generated
#' with ggplot2 and can be customized using ggplot plot + function() syntax.
#'
#' @examples
#' library(ggplot2)
#'
#' # Default settings
#' plot <- drugTimeResponseCurve(TGGATESsmall, cell_lines = "Hepatocyte",
#' dose = c("Control", "Low", "Middle"), drugs = drugNames(TGGATESsmall)[6],
#' duration = c("2", "8", "24"))
#'
#' # Customize title, x/y labels, x/y limits, colour palette and define
#' # custom ticks for x axis using the function argument ggplot2_args
#' customizations <- list(labs(title= 'My Custom Title', ylab = 'The y-axis'),
#' xlim(c(2, 24)), ylim(c(99,105)),
#' scale_color_brewer(palette="Set1"),
#' scale_x_continuous(breaks=c(2, 8, 24),
#' labels = c("Two", "Eight", "Twenty-Four"))
#' )
#'
#' if(interactive()) {
#' drugTimeResponseCurve(TGGATESsmall, cell_lines = "Hepatocyte",
#' dose = c("Control", "Low", "Middle"),
#' drugs = drugNames(TGGATESsmall)[6], duration = c("2", "8", "24"),
#' ggplot_args = customizations)
#' }
#'
#' # Customize the plot using standard ggplot2 syntax
#' if(interactive()) {
#' plot + labs(title= 'My Custom Title', ylab = 'The y-axis') +
#' xlim(c(2, 24)) + ylim(c(99,105)) + scale_color_brewer(palette="Set1")
#' }
#'
#' @param tSet \code{ToxicoSet} A ToxicoSet to be plotted in
#' this figure
#' @param dose \code{character} A vector of dose levels to be included in the
#' plot. Default to include all dose levels available for a drug. Must include
#' at minimum two dose levels, one of witch is "Control".
#' @param drugs \code{character} A drugs or pair of drugs to be plotted.
#' @param duration \code{character} A vector of durations to include in the plot.
#' @param summarize_replicates \code{logical} If TRUE will average viability
#' across replicates for each unique drug-dose-duration combination.
#' @param cell_lines \code{character} A vector of cell lines to include in the
#' plot.
#' @param line_width \code{numeric} A number specifying the thickness of lines
#' in the plot, as passed to size in geom_line(). Defaults to 1.
#' @param point_size \code{numeric} A number specifying how large points should
#' be in the plot, as passed to size in geom_point(). Defaults to 2.5.
#' @param verbose \code{boolean} Should warning messages about the data passed
#' in be printed?
#' @param ggplot_args \code{list} A list of ggplot2 functions which can be
#' called using the plot + function() syntax. This allows arbitrary
#' customization of the plot including changing the title, axis labels,
#' colours, etc. Please see the included examples for basic usage or ggplot2
#' documentation for advanced customization. Alternatively, you could assign
#' the return value to a variable and add the customization yourself using
#' plot + function().
#'
#' @return Plot of the viabilities for each drugs vs time of exposure
#'
#' @import ggplot2
#' @importFrom magrittr %<>%
#' @importFrom dplyr %>% filter group_by mutate
#' @importFrom tidyr gather
#'
#' @export
drugTimeResponseCurve <- function(
tSet,
duration = NULL,
cell_lines = NULL,
dose = NULL,
drugs = NULL,
summarize_replicates = TRUE,
line_width = 1,
point_size = 2.5,
verbose=TRUE,
ggplot_args=NULL
) {
# Place tSet in a list if not already
if (!is(tSet, "list")) {
tSet <- list(tSet)
}
paramErrorChecker("drugTimeResponseCurve",
tSets = tSet, drugs = drugs, duration = duration,
cell_lines = cell_lines, dose = dose)
## TODO:: Throw warning if a dose level or time point is not available for
# a specific drug
# Subsetting the tSet based on parameter arguments
tSet <- lapply(tSet, function(tSet) {
suppressWarnings({subsetTo(tSet, mDataType = "rna", drugs = drugs,
duration = duration, cells = cell_lines)})
})
# Gather data for the plot
plotData <- lapply(tSet, function(tSet) {
sInfo <- sensitivityInfo(tSet)[, seq_len(4)]
sValues <- sensitivityRaw(tSet)[,,2]
plotData <- cbind(sInfo, sValues)
cols <- c('Low', 'Middle', 'High')
colnames(plotData)[which(colnames(plotData) %in% c('doses1', 'doses2', 'doses3'))] <-
cols[which(c('doses1', 'doses2', 'doses3') %in% colnames(plotData))]
plotData %<>% gather('dose_level', 'viability', Control, Low, Middle, High)
})
for (data in plotData) {
if (summarize_replicates) {
data %<>% group_by(dose_level, duration_h) %>% mutate(viability = mean(viability))
plot <- ggplot(as_tibble(data) %>% filter(replicate == 1),
aes(as.numeric(duration_h), viability, color = dose_level)) +
geom_point(size = point_size) +
geom_line(size = line_width)
} else {
plot <- ggplot(as_tibble(data), aes(as.numeric(duration_h), viability,
color = dose_level,
shape = as.factor(replicate),
linetype = as.factor(replicate))) +
geom_point(size = point_size) +
geom_line(size = line_width)
}
}
plot <- plot + labs(
title = paste0("Drug Response Curve for ",
paste(drugs, collapse = " & "), " in ",
paste(cell_lines, collapse = " & "), collapse = " & "),
color = "Dose Level",
shape = "Replicate"
) +
theme(
plot.title = element_text(hjust = 0.5, size = 14)
) +
xlab("Duration (hrs)") +
ylab("Viability (%)") +
scale_x_continuous(breaks=as.numeric(duration), labels = duration)
# Pass in any additional ggplot2 customizations
if (!(is.null(ggplot_args))) {
plot <- plot + ggplot_args
}
plot
}
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