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#' @title Plot Variance of Expression Profiles
#' @description This function computes for each age category the corresponding variance expression profile.
#' @param ExpressionSet a standard PhyloExpressionSet or DivergenceExpressionSet object.
#' @param Groups a list containing the age categories for which variance expression levels shall be drawn.
#' For ex. evolutionary users can compare old phylostrata: PS1-3 (Class 1) and evolutionary young phylostrata: PS4-12 (Class 2).
#' In this example, the list could be assigned as, \code{Groups = list(c(1:3), c(4:12))}.
#' The group options is limited to 2 Groups.
#' @param legendName a character string specifying the legend title.
#' @param xlab label of x-axis.
#' @param ylab label of y-axis.
#' @param main main text.
#' @param y.ticks number of ticks that shall be drawn on the y-axis.
#' @param adjust.range logical indicating whether or not the y-axis scale shall be adjusted to the same range in case two groups are specified. Default is \code{adjust.range = TRUE}.
#' @details
#'
#' This plot may be useful to compare the absolute variance expression
#' levels of each age category across stages.
#'
#'In different developmental processes different phylostratum or divergence-stratum
#' classes might be more expressed than others, hence contributing more to the overall
#' phylotranscriptomics pattern (\code{\link{TAI}} or \code{\link{TDI}}).
#' This plot can help to identify the phylostratum or divergence-stratum classes
#' that contributes most to the overall transcriptome of the given developmental process.
#' @return a plot showing variance expression profiles of each age category.
#' @author Hajk-Georg Drost
#' @seealso \code{\link{PlotBarRE}}, \code{\link{RE}}, \code{\link{REMatrix}}, \code{\link{PlotRE}}
#' @examples
#' ### Example using a PhyloExpressionSet
#' ### and DivergenceExpressionSet
#' # load PhyloExpressionSet
#' data(PhyloExpressionSetExample)
#'
#' # load PhyloExpressionSet
#' data(DivergenceExpressionSetExample)
#'
#' # plot evolutionary old PS (PS1-3) vs evolutionary young PS (PS4-12)
#' PlotVars(PhyloExpressionSetExample,
#' Groups = list(c(1:3), c(4:12)),
#' legendName = "PS",
#' adjust.range = TRUE)
#'
#' # if users wish to not adjust the y-axis scale when
#' # 2 groups are selected they can specify: adjust.range = FALSE
#' PlotVars(PhyloExpressionSetExample,
#' Groups = list(c(1:3), c(4:12)),
#' legendName = "PS",
#' adjust.range = FALSE)
#'
#'
#' # plot conserved DS (DS1-5) vs divergent DS (PS6-10)
#' # NOTE: DS are always defined in the range 1, 2, ... , 10.
#' # Hence, make sure that your groups are within this range!
#' PlotVars(DivergenceExpressionSetExample,
#' Groups = list(c(1:5), c(6:10)),
#' legendName = "DS",
#' adjust.range = TRUE)
#'
#' @export
PlotVars <- function(ExpressionSet,
Groups = NULL,
legendName = "age",
xlab = "Ontogeny",
ylab = "Variance(Expression Level)",
main = "",
y.ticks = 10,
adjust.range = TRUE)
{
ExpressionSet <- as.data.frame(ExpressionSet)
is.ExpressionSet(ExpressionSet)
stage <- expr <- age <- NULL
if(is.null(Groups))
stop("Your Groups list does not store any items.", call. = FALSE)
### getting the PS names available in the given expression set
age_names <- as.character(names(table(ExpressionSet[ , 1])))
# test whether all group elements are available in the age vector
# ra <- range(ExpressionSet[ , 1])
if(!all(unlist(Groups) %in% as.numeric(age_names)))
stop("There are items in your Group elements that are not available in the age column of your ExpressionSet.", call. = FALSE)
if (length(Groups) > 2)
stop("Please specify at maximum 2 groups that shall be compared.", call. = FALSE)
### getting the PS names available in the given expression set
nPS <- length(age_names)
nCols <- dim(ExpressionSet)[2]
### define and label the REmatrix that holds the rel. exp. profiles
### for the available PS
MeanValsMatrix <- matrix(NA_real_,nPS,nCols-2)
rownames(MeanValsMatrix) <- age_names
colnames(MeanValsMatrix) <- names(ExpressionSet)[3:nCols]
MeanValsMatrix <- age.apply(ExpressionSet, function(x) apply(x, 2, stats::var))
mean.age <- data.frame(age = age_names, MeanValsMatrix, stringsAsFactors = FALSE)
mMatrix <- tibble::as_tibble(reshape2::melt(mean.age, id.vars = "age"))
colnames(mMatrix)[2:3] <- c("stage", "expr")
if (length(Groups) == 1) {
p <- ggplot2::ggplot(mMatrix, ggplot2::aes( factor(stage, levels = unique(stage)), expr, group = age, fill = factor(age, levels = age_names))) +
ggplot2::geom_line(ggplot2::aes(color = factor(age, levels = age_names)), size = 3) +
ggplot2::labs(x = xlab, y = ylab, title = main, colour = legendName) +
ggplot2::theme_minimal() +
ggplot2::theme(
title = ggplot2::element_text(size = 18, face = "bold"),
legend.title = ggplot2::element_text(size = 14, face = "bold"),
legend.text = ggplot2::element_text(size = 18, face = "bold"),
axis.title = ggplot2::element_text(size = 18, face = "bold"),
axis.text.y = ggplot2::element_text(size = 18, face = "bold"),
axis.text.x = ggplot2::element_text(size = 18, face = "bold"),
panel.background = ggplot2::element_blank(),
strip.text.x = ggplot2::element_text(
size = 18,
colour = "black",
face = "bold"
)
) +
ggplot2::scale_y_continuous(breaks = scales::pretty_breaks(n = y.ticks)) +
ggplot2::scale_colour_manual(values = custom.myTAI.cols(nrow(mMatrix)))
p <- p + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 1,hjust = 1))
return(p)
}
if (length(Groups) == 2) {
mMatrixGroup1 <- dplyr::filter(mMatrix, age %in% Groups[[1]])
mMatrixGroup2 <- dplyr::filter(mMatrix, age %in% Groups[[2]])
p1 <- ggplot2::ggplot(mMatrixGroup1, ggplot2::aes( factor(stage, levels = unique(stage)), expr, group = age, fill = factor(age, levels = age_names[Groups[[1]]]))) +
ggplot2::geom_line(ggplot2::aes(color = factor(age, levels = age_names[Groups[[1]]])), size = 3) +
ggplot2::labs(x = xlab, y = ylab, title = main, colour = legendName) +
ggplot2::theme_minimal() +
ggplot2::theme(
title = ggplot2::element_text(size = 18, face = "bold"),
legend.title = ggplot2::element_text(size = 14, face = "bold"),
legend.text = ggplot2::element_text(size = 18, face = "bold"),
axis.title = ggplot2::element_text(size = 18, face = "bold"),
axis.text.y = ggplot2::element_text(size = 18, face = "bold"),
axis.text.x = ggplot2::element_text(size = 18, face = "bold"),
panel.background = ggplot2::element_blank(),
strip.text.x = ggplot2::element_text(
size = 18,
colour = "black",
face = "bold"
)
) +
ggplot2::scale_colour_manual(values = custom.myTAI.cols(nrow(mMatrix))[Groups[[1]]]) +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = -90, hjust = 0))
if (!adjust.range) {
p1 <- p1 + ggplot2::scale_y_continuous(breaks = scales::pretty_breaks(n = y.ticks))
}
p2 <- ggplot2::ggplot(mMatrixGroup2, ggplot2::aes( factor(stage, levels = unique(stage)), expr, group = age, fill = factor(age, levels = age_names[Groups[[2]]]))) +
ggplot2::geom_line(ggplot2::aes(color = factor(age, levels = age_names[Groups[[2]]])), size = 3) +
ggplot2::labs(x = xlab, y = ylab, title = main, colour = legendName) +
ggplot2::theme_minimal() +
ggplot2::theme(
title = ggplot2::element_text(size = 18, face = "bold"),
legend.title = ggplot2::element_text(size = 14, face = "bold"),
legend.text = ggplot2::element_text(size = 18, face = "bold"),
axis.title = ggplot2::element_text(size = 18, face = "bold"),
axis.text.y = ggplot2::element_text(size = 18, face = "bold"),
axis.text.x = ggplot2::element_text(size = 18, face = "bold"),
panel.background = ggplot2::element_blank(),
strip.text.x = ggplot2::element_text(
size = 18,
colour = "black",
face = "bold"
)
) +
ggplot2::scale_colour_manual(values = custom.myTAI.cols(nrow(mMatrix))[Groups[[2]]]) +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = -90, hjust = 0))
if (!adjust.range) {
p2 <- p2 + ggplot2::scale_y_continuous(breaks = scales::pretty_breaks(n = y.ticks))
}
if (adjust.range){
p1 <- p1 + ggplot2::scale_y_continuous(limits = c(min(MeanValsMatrix), max(MeanValsMatrix)), breaks = scales::pretty_breaks(n = y.ticks))
p2 <- p2 + ggplot2::scale_y_continuous(limits = c(min(MeanValsMatrix), max(MeanValsMatrix)), breaks = scales::pretty_breaks(n = y.ticks))
}
p1 <- p1 + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 1,hjust = 1))
p2 <- p2 + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 1,hjust = 1))
return(gridExtra::grid.arrange(p1, p2, ncol = 2))
}
}
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