Nothing
R/ggPlotting.R
In singleCellTK: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data
Defines functions
.ggSCTKTheme
.ggSCTKCombinePlots
.binSCTK
plotSCEBarAssayData
plotSCEBarColData
.ggBar
plotBarcodeRankScatter
plotEmptyDropsScatter
plotSCEDensity
plotSCEDensityAssayData
plotSCEDensityColData
.ggDensity
plotSCEViolin
plotSCEViolinAssayData
plotSCEViolinColData
.ggViolin
plotSCEScatter
plotSCEDimReduceFeatures
plotSCEDimReduceColData
.ggScatter
Documented in
.ggBar
.ggDensity
.ggScatter
.ggViolin
plotBarcodeRankScatter
plotEmptyDropsScatter
plotSCEBarAssayData
plotSCEBarColData
plotSCEDensity
plotSCEDensityAssayData
plotSCEDensityColData
plotSCEDimReduceColData
plotSCEDimReduceFeatures
plotSCEScatter
plotSCEViolin
plotSCEViolinAssayData
plotSCEViolinColData
#' @title Plot results of reduced dimensions data.
#' @description Plot results of reduced dimensions data and colors the plots by
#' the input vector.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param colorBy If provided, colors dots in the scatterplot based on value.
#' @param groupBy If provided, facet wrap the scatterplot based on value.
#' @param conditionClass class of the annotation data used in colorBy. Options
#' are NULL, "factor" or "numeric". If NULL, class will default to the original
#' class. Default NULL.
#' @param shape If provided, add shapes based on the value.
#' @param reducedDimName Saved dimension reduction name in the
#' \linkS4class{SingleCellExperiment} object. Required.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dim1 1st dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param dim2 2nd dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param bin Numeric vector. If single value, will divide the numeric values into the `bin` groups.
#' If more than one value, will bin numeric values using values as a cut point.
#' @param binLabel Character vector. Labels for the bins created by the `bin` parameter.
#' Default NULL.
#' @param dotSize Size of dots. Default 2.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param colorScale Vector. Needs to be same length as the
#' number of unique levels of `colorBy`. Will be used only if
#' conditionClass = "factor" or "character". Default NULL.
#' @param colorLow Character. A color available from `colors()`.
#' The color will be used to signify the lowest values on the scale.
#' Default 'white'. Will be used only if conditionClass = "numeric".
#' @param colorMid Character. A color available from `colors()`.
#' The color will be used to signify the midpoint on the scale.
#' Default 'gray'. Will be used only if conditionClass = "numeric".
#' @param colorHigh Character. A color available from `colors()`.
#' The color will be used to signify the highest values on the scale.
#' Default 'blue'. Will be used only if conditionClass = "numeric".
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param labelClusters Logical. Whether the cluster labels are plotted.
#' Default FALSE.
#' @param legendTitle title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the reduced dimensions.
.ggScatter <- function(inSCE,
sample = NULL,
colorBy = NULL,
groupBy = NULL,
shape = NULL,
reducedDimName,
conditionClass = NULL,
labelClusters = FALSE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dim1 = NULL,
dim2 = NULL,
bin = NULL,
binLabel = NULL,
dotSize = 2,
transparency = 1,
colorScale = NULL,
colorLow = "white",
colorMid = "gray",
colorHigh = "blue",
defaultTheme = TRUE,
title = NULL,
titleSize = 15,
legendTitle = NULL,
legendTitleSize = 12,
legendSize = 10,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x){
sceSampleInd <- which(sample == x)
inSCESub <- inSCE[, sceSampleInd]
colorBySub <- colorBy[sceSampleInd]
dataframe <- data.frame(SingleCellExperiment::reducedDim(
inSCESub,
reducedDimName
))
# If dim1 and dim2 are specified
if (!is.null(dim1) & !is.null(dim2)) {
if (is.character(dim1) & is.character(dim2)) {
if (!(dim1 %in% colnames(dataframe))) {
stop("X dimension ", dim1, " is not in the reducedDim data")
}
if (!(dim2 %in% colnames(dataframe))) {
stop("Y dimension ", dim2, " is not in the reducedDim data")
}
dataframe <- dataframe[, c(dim1, dim2)]
} else if (is.numeric(dim1) && is.numeric(dim2)) {
dataframe <- dataframe[, c(dim1, dim2)]
}
} else if (ncol(dataframe) > 2) {
warning("More than two dimensions supplied in reducedDims.
Using the first two.")
}
# If xlab and ylab are specified
if (!is.null(xlab) & !is.null(ylab)) {
colnames(dataframe) <- c(xlab, ylab)
# If reduced dimension matrix didnt have colnames
} else {
colnames(dataframe) <- c(paste0(reducedDimName, "_1"),
paste0(reducedDimName, "_2"))
}
xdim <- colnames(dataframe)[1]
ydim <- colnames(dataframe)[2]
if (!is.null(conditionClass) & !is.null(colorBySub)) {
if (conditionClass %in% c("character", "factor", "numeric")) {
if (conditionClass == "character") {
colorBySub <- as.character(colorBySub)
} else if (conditionClass == "factor") {
colorBySub <- as.factor(colorBySub)
} else if (conditionClass == "numeric") {
colorBySub <- as.numeric(colorBySub)
}
}
}
if (!is.null(bin) & !is.null(colorBySub)) {
colorBySub <- .binSCTK(
value = colorBySub,
bin = bin,
binLabel = binLabel
)
}
if (!is.null(colorBySub)) {
dataframe$color <- colorBySub
}
if (!is.null(groupBy)){
dataframe$groups <- factor(SingleCellExperiment::colData(inSCE)@listData[[groupBy]])
}
if (!is.null(shape)) {
dataframe$shape <- factor(SingleCellExperiment::colData(inSCESub)[, shape])
}
dataframe$Sample <- colnames(inSCESub)
g <- ggplot2::ggplot(dataframe, ggplot2::aes_string(xdim, ydim,
label = "Sample")) + ggplot2::geom_point(size = dotSize,
alpha = transparency)
if (!is.null(colorBySub)) {
g <- g + ggplot2::aes_string(color = "color")
}
if (inherits(colorBySub, "numeric")){
g <- g + ggplot2::scale_color_gradient2(
low = colorLow,
mid = colorMid,
high = colorHigh,
aesthetics = "colour",
midpoint = mean(colorBySub))
}else if (inherits(colorBySub, "character") | inherits(colorBySub, "factor")){
g <- g +
ggplot2::guides(colour = ggplot2::guide_legend(override.aes = list(size = 2)))
if(all(!is.null(colorScale))){
g <- g+ ggplot2::scale_color_manual(values=c(colorScale))
}
}
if (!is.null(shape)) {
g <- g + ggplot2::aes_string(shape = "shape") +
ggplot2::labs(shape = shape)
}
if (defaultTheme == TRUE) {
g <- .ggSCTKTheme(g)
}
g <- g + ggplot2::theme(axis.title =
ggplot2::element_text(size = axisLabelSize),
axis.text =
ggplot2::element_text(size = axisSize))
if (!is.null(title)) {
if (length(samples) > 1) {
title <- paste(title, x, sep = "_")
}
g <- g + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
if (!is.null(legendTitle)) {
g <- g + ggplot2::labs(color = legendTitle) +
ggplot2::theme(legend.title=ggplot2::element_text(size=legendTitleSize),
legend.text=ggplot2::element_text(size=legendSize))
} else {
g <- g + ggplot2::labs(color = "") +
ggplot2::theme(legend.text=ggplot2::element_text(size=legendSize))
}
if (!is.null(groupBy)){
g <- g + ggplot2::facet_wrap(~groups)
}
if (isTRUE(labelClusters) && class(colorBySub) %in% c("character", "factor")) {
centroidList <- lapply(unique(colorBySub), function(x) {
dataframe.sub <- dataframe[dataframe$color == x, ]
median.1 <- stats::median(dataframe.sub[, 1])
median.2 <- stats::median(dataframe.sub[, 2])
cbind(median.1, median.2, as.character(x))
})
centroid <- do.call(rbind, centroidList)
centroid <- data.frame(
Dimension_1 = as.numeric(centroid[, 1]),
Dimension_2 = as.numeric(centroid[, 2]),
color = centroid[, 3],
Sample = rep(1, length(unique(colorBySub)))
)
if (!is.null(shape)) {
centroid$shape <- dataframe$shape[1]
}
if (!is.null(groupBy)){
g <- g + ggplot2::facet_wrap(~groups)
}
colnames(centroid)[seq_len(2)] <- c(xdim, ydim)
g <- g + ggplot2::geom_point(
data = centroid,
mapping = ggplot2::aes_string(x = xdim, y = ydim),
size = 0,
alpha = 0
) +
ggrepel::geom_text_repel(
data = centroid,
mapping = ggplot2::aes_string(label = "color"),
show.legend = FALSE,
color = "black"
)
}
return(g)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
plotlist <- list(Sample = plotlist)
}
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}else if(combinePlot == "none" && length(plotlist) == 1){
plotlist <- plotlist[[1]]
}
return(plotlist)
}
#' @title Dimension reduction plot tool for colData
#' @description Plot results of reduced dimensions data and
#' colors by annotation data stored in the colData slot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param colorBy Color by a condition(any column of the annotation data).
#' Required.
#' @param groupBy Group by a condition(any column of the annotation data).
#' Default NULL.
#' @param conditionClass Class of the annotation data used in colorBy.
#' Options are NULL, "factor" or "numeric". If NULL, class will default to the
#' original class. Default NULL.
#' @param shape Add shapes to each condition.
#' @param reducedDimName Saved dimension reduction matrix name in the
#' \linkS4class{SingleCellExperiment} object. Required.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param dim1 1st dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param dim2 2nd dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param bin Numeric vector. If single value, will divide the numeric values into the `bin` groups.
#' If more than one value, will bin numeric values using values as a cut point.
#' @param binLabel Character vector. Labels for the bins created by the `bin` parameter.
#' Default NULL.
#' @param dotSize Size of dots. Default 2.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param colorScale Vector. Needs to be same length as the
#' number of unique levels of colorBy. Will be used only if
#' conditionClass = "factor" or "character". Default NULL.
#' @param colorLow Character. A color available from `colors()`.
#' The color will be used to signify the lowest values on the scale.
#' Default 'white'.
#' @param colorMid Character. A color available from `colors()`.
#' The color will be used to signify the midpoint on the scale.
#' Default 'gray'.
#' @param colorHigh Character. A color available from `colors()`.
#' The color will be used to signify the highest values on the scale.
#' Default 'blue'.
#' @param defaultTheme adds grid to plot when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param labelClusters Logical. Whether the cluster labels are plotted.
#' @param legendTitle title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' Default FALSE.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the reduced dimension plot of coldata.
#' @examples
#' plotSCEDimReduceColData(
#' inSCE = mouseBrainSubsetSCE, colorBy = "tissue",
#' shape = NULL, conditionClass = "factor",
#' reducedDimName = "TSNE_counts",
#' xlab = "tSNE1", ylab = "tSNE2", labelClusters = TRUE
#' )
#'
#' plotSCEDimReduceColData(
#' inSCE = mouseBrainSubsetSCE, colorBy = "age",
#' shape = NULL, conditionClass = "numeric",
#' reducedDimName = "TSNE_counts", bin = c(-Inf, 20, 25, +Inf),
#' xlab = "tSNE1", ylab = "tSNE2", labelClusters = FALSE
#' )
#' @export
plotSCEDimReduceColData <- function(inSCE,
sample = NULL,
colorBy,
groupBy = NULL,
conditionClass = NULL,
shape = NULL,
reducedDimName = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dim1 = NULL,
dim2 = NULL,
bin = NULL,
binLabel = NULL,
dotSize = 2,
transparency = 1,
colorScale = NULL,
colorLow = "white",
colorMid = "gray",
colorHigh = "blue",
defaultTheme = TRUE,
title = NULL,
titleSize = 15,
labelClusters = TRUE,
legendTitle = NULL,
legendTitleSize = 12,
legendSize = 10,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
colorPlot <- SingleCellExperiment::colData(inSCE)[, colorBy]
g <- .ggScatter(
inSCE = inSCE,
sample = sample,
colorBy = colorPlot,
groupBy = groupBy,
conditionClass = conditionClass,
shape = shape,
reducedDimName = reducedDimName,
xlab = xlab,
ylab = ylab,
dim1 = dim1,
dim2 = dim2,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
bin = bin,
binLabel = binLabel,
dotSize = dotSize,
transparency = transparency,
colorScale = colorScale,
colorLow = colorLow,
colorMid = colorMid,
colorHigh = colorHigh,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize,
labelClusters = labelClusters,
legendTitle = legendTitle,
legendTitleSize = legendTitleSize,
legendSize = legendSize,
combinePlot = combinePlot,
plotLabels = plotLabels
)
return(g)
}
#' @title Dimension reduction plot tool for assay data
#' @description Plot results of reduced dimensions data and
#' colors by feature data stored in the assays slot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param feature name of feature stored in assay of singleCellExperiment
#' object. Plot will be colored based on feature value.
#' @param shape add shapes to each condition. Default NULL.
#' @param reducedDimName saved dimension reduction name in the
#' \linkS4class{SingleCellExperiment} object. Required.
#' @param useAssay Indicate which assay to use. The default is "logcounts"
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dim1 1st dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param dim2 2nd dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' Default is second PCA component for PCA data and NULL otherwise.
#' @param bin Numeric vector. If single value, will divide the numeric values into the `bin` groups.
#' If more than one value, will bin numeric values using values as a cut point.
#' @param binLabel Character vector. Labels for the bins created by the `bin` parameter.
#' Default NULL.
#' @param dotSize Size of dots. Default 2.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param colorLow Character. A color available from `colors()`.
#' The color will be used to signify the lowest values on the scale.
#' Default 'white'.
#' @param colorMid Character. A color available from `colors()`.
#' The color will be used to signify the midpoint on the scale.
#' Default 'gray'.
#' @param colorHigh Character. A color available from `colors()`.
#' The color will be used to signify the highest values on the scale.
#' Default 'blue'.
#' @param defaultTheme adds grid to plot when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param legendTitle title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' @param groupBy Facet wrap the scatterplot based on value.
#' Default \code{NULL}.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the reduced dimension plot of feature data.
#' @examples
#' plotSCEDimReduceFeatures(
#' inSCE = mouseBrainSubsetSCE, feature = "Apoe",
#' shape = NULL, reducedDimName = "TSNE_counts",
#' useAssay = "counts", xlab = "tSNE1", ylab = "tSNE2"
#' )
#' @export
plotSCEDimReduceFeatures <- function(inSCE,
sample = NULL,
feature,
shape = NULL,
reducedDimName,
useAssay = "logcounts",
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dim1 = NULL,
dim2 = NULL,
bin = NULL,
binLabel = NULL,
dotSize = 2,
transparency = 1,
colorLow = "white",
colorMid = "gray",
colorHigh = "blue",
defaultTheme = TRUE,
title = NULL,
titleSize = 15,
legendTitle = NULL,
legendSize = 10,
legendTitleSize = 12,
groupBy = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
mat <- getBiomarker(
inSCE = inSCE,
useAssay = useAssay,
gene = feature,
binary = "Continuous"
)
counts <- mat[, 2]
g <- .ggScatter(
inSCE = inSCE,
sample = sample,
conditionClass = "numeric",
colorBy = counts,
shape = shape,
transparency = 1,
colorLow = colorLow,
colorMid = colorMid,
colorHigh = colorHigh,
reducedDimName = reducedDimName,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dim1 = dim1,
dim2 = dim2,
bin = bin,
binLabel = binLabel,
defaultTheme = defaultTheme,
dotSize = dotSize,
title = title,
titleSize = titleSize,
legendTitle = legendTitle,
legendTitleSize = legendTitleSize,
legendSize = legendSize,
groupBy = groupBy,
combinePlot = combinePlot,
plotLabels = plotLabels
)
return(g)
}
#' @title Dimension reduction plot tool for all types of data
#' @description Plot results of reduced dimensions data of counts stored in any
#' slot in the SingleCellExperiment object.
#' @param inSCE Input SingleCellExperiment object with saved dimension reduction
#' components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param slot Desired slot of SingleCellExperiment used for plotting. Possible
#' options: "assays", "colData", "metadata", "reducedDims". Default NULL.
#' @param annotation Desired vector within the slot used for plotting. Default NULL.
#' @param feature name of feature stored in assay of SingleCellExperiment
#' object. Will be used only if "assays" slot is chosen. Default NULL.
#' @param groupBy Group by a condition(any column of the annotation data).
#' Default NULL.
#' @param shape add shapes to each condition.
#' @param reducedDimName saved dimension reduction name in the
#' \linkS4class{SingleCellExperiment} object. Required.
#' @param conditionClass class of the annotation data used in colorBy. Options
#' are NULL, "factor" or "numeric". If NULL, class will default to the original
#' class. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dim1 1st dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param dim2 2nd dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' Default is second PCA component for PCA data and NULL otherwise.
#' @param bin Numeric vector. If single value, will divide the numeric values into the `bin` groups.
#' If more than one value, will bin numeric values using values as a cut point.
#' @param binLabel Character vector. Labels for the bins created by the `bin` parameter.
#' Default NULL.
#' @param dotSize Size of dots. Default 2.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param colorLow Character. A color available from `colors()`.
#' The color will be used to signify the lowest values on the scale.
#' Default 'white'.
#' @param colorMid Character. A color available from `colors()`.
#' The color will be used to signify the midpoint on the scale.
#' Default 'gray'.
#' @param colorHigh Character. A color available from `colors()`.
#' The color will be used to signify the highest values on the scale.
#' Default 'blue'.
#' @param defaultTheme adds grid to plot when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param labelClusters Logical. Whether the cluster labels are plotted.
#' @param legendTitle title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the reduced dimensions.
#' @examples
#' plotSCEScatter(
#' inSCE = mouseBrainSubsetSCE, legendTitle = NULL,
#' slot = "assays", annotation = "counts", feature = "Apoe",
#' reducedDimName = "TSNE_counts", labelClusters = FALSE
#' )
#' @export
#' @import SingleCellExperiment
plotSCEScatter <- function(inSCE,
slot = NULL,
sample = NULL,
annotation,
feature = NULL,
groupBy = NULL,
shape = NULL,
reducedDimName = NULL,
conditionClass = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dim1 = NULL,
dim2 = NULL,
bin = NULL,
binLabel = NULL,
dotSize = 2,
transparency = 1,
colorLow = "white",
colorMid = "gray",
colorHigh = "blue",
defaultTheme = TRUE,
title = NULL,
titleSize = 15,
labelClusters = TRUE,
legendTitle = NULL,
legendTitleSize = 12,
legendSize = 10,
combinePlot = "none",
plotLabels = NULL){
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!is.null(slot)){
if (slot == "reducedDims"){
annotation_clm <- substr(annotation, stringr::str_length(annotation), stringr::str_length(annotation))
annotation <- substr(annotation, 1, stringr::str_length(annotation) - 2)
}else if (!slot %in% methods::slotNames(inSCE)) {
stop("'slot' must be a slot within the SingleCellExperiment object.
Please run 'methods::slotNames' if you are unsure the
specified slot exists.")
}
sceSubset <- do.call(slot, args = list(inSCE))
if (!annotation %in% names(sceSubset)) {
stop("'annotation' must be an annotation stored within the specified
slot of the SingleCellExperiment object.")
}
annotation.ix <- match(annotation, c(names(sceSubset)))
}
if (is.null(slot)){
colorPlot <- NULL
}else if (slot == "assays" && !is.null(feature)) {
counts <- sceSubset[[annotation.ix]]
if (feature %in% rownames(counts)) {
colorPlot <- counts[feature, ]
}
} else if (slot == "colData") {
colorPlot <- sceSubset[, annotation.ix]
} else if (slot == "metadata") {
colorPlot <- sceSubset[[annotation.ix]]
} else if (slot == "reducedDims") {
colorPlot <- sceSubset[[annotation.ix]][, as.numeric(annotation_clm)]
}
g <- .ggScatter(
inSCE = inSCE,
sample = sample,
colorBy = colorPlot,
groupBy = groupBy,
conditionClass = conditionClass,
shape = shape,
reducedDimName = reducedDimName,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dim1 = dim1,
dim2 = dim2,
bin = bin,
binLabel = binLabel,
dotSize = dotSize,
transparency = transparency,
colorLow = colorLow,
colorMid = colorMid,
colorHigh = colorHigh,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize,
labelClusters = labelClusters,
legendTitle = legendTitle,
legendTitleSize = legendTitleSize,
legendSize = legendSize,
combinePlot = combinePlot
)
return(g)
}
#' @title Violin plot plotting tool.
#' @description Visualizes specified values via a violin plot.
#' @param y Numeric values to be plotted on y-axis.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param violin Boolean. If TRUE, will plot the violin plot. Default TRUE.
#' @param boxplot Boolean. If TRUE, will plot boxplots for each violin plot.
#' Default TRUE.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @return a ggplot of the reduced dimensions.
#' @importFrom dplyr group_by
#' @importFrom dplyr summarize
#' @importFrom dplyr %>%
.ggViolin <- function(y,
groupBy = NULL,
violin = TRUE,
boxplot = TRUE,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = 15) {
if (is.null(groupBy)) {
groupBy <- rep("Sample", length(y))
}
df <- data.frame(groupBy = groupBy, y = y)
p <- ggplot2::ggplot(df) +
ggplot2::aes_string(
x = "groupBy",
y = "y"
)
if (dots == TRUE) {
p <- p + ggplot2::geom_jitter(
color = "blue",
width = 0.2,
height = 0,
size = dotSize,
alpha = transparency
)
}
if (boxplot == TRUE) {
p <- p + ggplot2::geom_boxplot(width = 0.5,
alpha = 0)
}
if (violin == TRUE) {
p <- p + ggplot2::geom_violin(trim = TRUE,
scale = "width",
size = 1,
fill = "grey",
alpha = 0.75)
}
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p)
}
if (!is.null(title)) {
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
###
p <- p + ggplot2::theme(axis.text.y = ggplot2::element_text(size = axisSize))
###
if(length(unique(df$groupBy)) > 1){
p <- p + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 45,
hjust = 1,
size = axisSize))
}else{
p <- p + ggplot2::theme(axis.text.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
axis.title.x = ggplot2::element_blank())
}
if (gridLine == TRUE){
p <- p + ggplot2::theme(panel.grid.major.y = ggplot2::element_line("grey"))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(summary)){
if(summary == "mean"){
summ <- df %>% dplyr::group_by(groupBy) %>% dplyr::summarize(value = base::mean(y))
fun <- base::mean
}else if(summary == "median"){
summ <- df %>% dplyr::group_by(groupBy) %>% dplyr::summarize(value = stats::median(y))
fun <- stats::median
}else{
stop("`summary`` must be either `mean` or `median`.")
}
summ$statY <- max(df$y) + (max(df$y) - min(df$y)) * 0.1
summary <- paste(toupper(substr(summary, 1, 1)),
substr(summary, 2, nchar(summary)), sep="")
summ$label <- paste0(summary,": ", round(summ$value, 5))
p <- p + ggplot2::geom_text(data = summ,
ggplot2::aes_string(x = "groupBy",
y = "statY",
label = "label"),
size = 5)
p <- p + ggplot2::stat_summary(fun = fun, fun.min = fun,
fun.max = fun,
geom = "crossbar",
color = "red",
linetype = "dashed")
}
return(p)
}
#' @title Violin plot of colData.
#' @description Visualizes values stored in the colData slot of a
#' SingleCellExperiment object via a violin plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param coldata colData value that will be plotted.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param violin Boolean. If TRUE, will plot the violin plot. Default TRUE.
#' @param boxplot Boolean. If TRUE, will plot boxplots for each violin plot.
#' Default TRUE.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the violin plot of coldata.
#' @examples
#' plotSCEViolinColData(
#' inSCE = mouseBrainSubsetSCE,
#' coldata = "age", groupBy = "sex"
#' )
#' @export
plotSCEViolinColData <- function(inSCE,
sample = NULL,
coldata,
groupBy = NULL,
violin = TRUE,
boxplot = TRUE,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!is.null(coldata)) {
if (!coldata %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(coldata), "' is not found in ColData.")
}
coldata <- SummarizedExperiment::colData(inSCE)[, coldata]
} else {
stop("You must define the desired colData to plot.")
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(coldata)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop("'sample' must be the same length as the number",
" of columns in 'inSCE'")
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
coldataSub <- coldata[sampleInd]
if(!is.null(groupBy)){
groupbySub <- groupBy[sampleInd]
}else{
groupbySub <- NULL
}
if(!is.null(title) && length(samples) > 1){
title = paste(title, x, sep = "_")
}
p <- .ggViolin(
y = coldataSub,
groupBy = groupbySub,
violin = violin,
boxplot = boxplot,
dots = dots,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
gridLine = gridLine,
summary = summary,
title = title,
titleSize = titleSize
)
return(p)
})
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}else if(combinePlot == "none" && length(plotlist) == 1){
plotlist <- plotlist[[1]]
}
return(plotlist)
}
#' @title Violin plot of assay data.
#' @description Visualizes values stored in the assay slot of a
#' SingleCellExperiment object via a violin plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param useAssay Indicate which assay to use. Default "counts".
#' @param feature Name of feature stored in assay of SingleCellExperiment
#' object.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param violin Boolean. If TRUE, will plot the violin plot. Default TRUE.
#' @param boxplot Boolean. If TRUE, will plot boxplots for each violin plot.
#' Default TRUE.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the violin plot of assay data.
#' @examples
#' plotSCEViolinAssayData(
#' inSCE = mouseBrainSubsetSCE,
#' feature = "Apoe", groupBy = "sex"
#' )
#' @export
plotSCEViolinAssayData <- function(inSCE,
sample = NULL,
useAssay = "counts",
feature,
groupBy = NULL,
violin = TRUE,
boxplot = TRUE,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
mat <- getBiomarker(
inSCE = inSCE,
useAssay = useAssay,
gene = feature,
binary = "Continuous"
)
counts <- mat[, 2]
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop("'sample' must be the same length as the number",
" of columns in 'inSCE'")
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
countSub <- counts[sampleInd]
if(!is.null(groupBy)){
groupbySub <- groupBy[sampleInd]
}else{
groupbySub <- NULL
}
p <- .ggViolin(
y = countSub,
groupBy = groupbySub,
violin = violin,
boxplot = boxplot,
dots = dots,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
gridLine = gridLine,
summary = summary,
title = title,
titleSize = titleSize
)
return(p)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
if(combinePlot == "sample"){
plotlist <- c(list(Sample = plotlist))
}
} else {
plotlist <- plotlist[[1]]
}
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}else if(combinePlot == "none" && length(plotlist) == 1){
plotlist <- plotlist[[1]]
}
return(plotlist)
}
#' @title Violin plot of any data stored in the SingleCellExperiment object.
#' @description Visualizes values stored in any slot of a
#' SingleCellExperiment object via a violin plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param slot Desired slot of SingleCellExperiment used for plotting. Possible
#' options: "assays", "colData", "metadata"
#' @param annotation Desired vector within the slot used for plotting.
#' @param feature name of feature stored in assay of SingleCellExperiment
#' object.
#' Will be used only if "assays" slot is chosen. Default NULL.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param violin Boolean. If TRUE, will plot the violin plot. Default TRUE.
#' @param boxplot Boolean. If TRUE, will plot boxplots for each violin plot.
#' Default TRUE.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the violin plot.
#' @examples
#' plotSCEViolin(
#' inSCE = mouseBrainSubsetSCE, slot = "assays",
#' annotation = "counts", feature = "Apoe", groupBy = "sex"
#' )
#' @export
plotSCEViolin <- function(inSCE,
sample = NULL,
slot,
annotation,
feature,
groupBy = NULL,
violin = TRUE,
boxplot = TRUE,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!slot %in% methods::slotNames(inSCE)) {
stop("'slot' must be a slot within the SingleCellExperiment object.
Please run 'methods::slotNames' if you are unsure the
specified slot exists.")
}
sceSubset <- do.call(slot, args = list(inSCE))
if (!annotation %in% names(sceSubset)) {
stop("'annotation' must be an annotation stored within the specified
slot of the SingleCellExperiment object.")
}
annotation.ix <- match(annotation, names(sceSubset))
if (slot == "assays" && !is.null(feature)) {
counts <- sceSubset[[annotation.ix]]
if (feature %in% rownames(counts)) {
counts <- counts[feature, ]
}
} else if (slot == "colData") {
counts <- sceSubset[, annotation.ix]
} else if (slot == "metadata") {
counts <- sceSubset[[annotation.ix]]
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop("'sample' must be the same length as the number",
" of columns in 'inSCE'")
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
countSub <- counts[sampleInd]
if(!is.null(groupBy)){
groupbySub <- groupBy[sampleInd]
}else{
groupbySub <- NULL
}
p <- .ggViolin(
y = countSub,
groupBy = groupbySub,
violin = violin,
boxplot = boxplot,
dots = dots,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
gridLine = gridLine,
summary = summary,
title = title,
titleSize = titleSize
)
return(p)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
if(!is.null(combinePlot)){
if(combinePlot == "sample"){
plotlist <- c(list(Sample = plotlist))
}
}
} else {
plotlist <- plotlist[[1]]
# plotlist <- unlist(plotlist, recursive=F)
}
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample") &&
length(unique(samples)) > 1){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}else if(combinePlot == "none" && length(plotlist) == 1){
plotlist <- plotlist[[1]]
}
return(plotlist)
}
#' @title Density plot plotting tool.
#' @description Visualizes values stored in the specified slot of a
#' SingleCellExperiment object via a density plot.
#' @param value Numeric value that will be plotted via density plot.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param cutoff Numeric value. The plot will be annotated with a vertical line
#' if set. Default NULL.
#' @return density plot, in .ggplot.
.ggDensity <- function(value,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
defaultTheme = TRUE,
title = NULL,
titleSize = 18,
cutoff = NULL) {
if (is.null(groupBy)) {
groupBy <- rep("Sample", length(value))
}
df <- data.frame(x = groupBy, y = value)
p <- ggplot2::ggplot(df, ggplot2::aes_string(x = value)) +
ggplot2::geom_density() +
ggplot2::facet_grid(. ~ x)
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p) +
ggplot2::theme(strip.background = ggplot2::element_blank())
}
if (all(unique(groupBy) == "Sample")) {
p <- p + ggplot2::theme(strip.text.x = ggplot2::element_blank())
}
if (!is.null(title)) {
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize))
}
p <- p + ggplot2::theme(axis.text = ggplot2::element_text(size = axisSize))
if (!is.null(cutoff)) {
p <- p + ggplot2::geom_vline(xintercept = cutoff, color = "red")
}
return(p)
}
#' @title Density plot of colData.
#' @description Visualizes values stored in the colData slot of a
#' SingleCellExperiment object via a density plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param coldata colData value that will be plotted.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param cutoff Numeric value. The plot will be annotated with a vertical line
#' if set. Default NULL.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the density plot of colData.
#' @examples
#' plotSCEDensityColData(
#' inSCE = mouseBrainSubsetSCE,
#' coldata = "age", groupBy = "sex"
#' )
#' @export
plotSCEDensityColData <- function(inSCE,
sample = NULL,
coldata,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
defaultTheme = TRUE,
title = NULL,
titleSize = 18,
cutoff = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!is.null(coldata)) {
if (!coldata %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(coldata), "' is not found in ColData.")
}
coldata <- SummarizedExperiment::colData(inSCE)[, coldata]
} else {
stop("You must define the desired colData to plot.")
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(coldata)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
coldataSub <- coldata[sampleInd]
if (!is.null(groupBy)) {
groupbySub <- groupBy[sampleInd]
} else {
groupbySub <- NULL
}
if (!is.null(title) && length(samples) > 1) {
title <- paste(title, x, sep = "_")
}
p <- .ggDensity(
value = coldataSub,
groupBy = groupbySub,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize,
cutoff = cutoff
)
return(p)
})
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}
return(plotlist)
}
#' @title Density plot of assay data.
#' @description Visualizes values stored in the assay slot of a
#' SingleCellExperiment object via a density plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param useAssay Indicate which assay to use. Default "counts".
#' @param feature Name of feature stored in assay of SingleCellExperiment
#' object.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param cutoff Numeric value. The plot will be annotated with a vertical line
#' if set. Default NULL.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the density plot of assay data.
#' @examples
#' plotSCEDensityAssayData(
#' inSCE = mouseBrainSubsetSCE,
#' feature = "Apoe"
#' )
#' @export
plotSCEDensityAssayData <- function(inSCE,
sample = NULL,
useAssay = "counts",
feature,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
defaultTheme = TRUE,
cutoff = NULL,
title = NULL,
titleSize = 18,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
mat <- getBiomarker(
inSCE = inSCE,
useAssay = useAssay,
gene = feature,
binary = "Continuous"
)
counts <- mat[, 2]
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
countsSub <- counts[sampleInd]
if (!is.null(groupBy)) {
groupbySub <- groupBy[sampleInd]
} else {
groupbySub <- NULL
}
if (!is.null(title) && length(samples) > 1) {
title <- paste(title, x, sep = "_")
}
p <- .ggDensity(
value = countsSub,
groupBy = groupbySub,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize,
cutoff = cutoff
)
return(p)
})
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}
return(plotlist)
}
#' @title Density plot of any data stored in the SingleCellExperiment object.
#' @description Visualizes values stored in any slot of a
#' SingleCellExperiment object via a densityn plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param slot Desired slot of SingleCellExperiment used for plotting. Possible
#' options: "assays", "colData", "metadata"
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param annotation Desired vector within the slot used for plotting.
#' @param useAssay Indicate which assay to use. Default "counts".
#' @param feature name of feature stored in assay of SingleCellExperiment
#' object. Will be used only if "assays" slot is chosen. Default NULL.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param cutoff Numeric value. The plot will be annotated with a vertical line
#' if set. Default NULL.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot object of the density plot.
#' @examples
#' plotSCEDensity(
#' inSCE = mouseBrainSubsetSCE, slot = "assays",
#' annotation = "counts", feature = "Apoe", groupBy = "sex"
#' )
#' @export
plotSCEDensity <- function(inSCE,
slot,
annotation,
sample = NULL,
useAssay = "counts",
feature = NULL,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
defaultTheme = TRUE,
title = NULL,
titleSize = 18,
cutoff = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!slot %in% methods::slotNames(inSCE)) {
stop("'slot' must be a slot within the SingleCellExperiment object.
Please run 'methods::slotNames' if you are unsure the
specified slot exists.")
}
sceSubset <- do.call(slot, args = list(inSCE))
if (!annotation %in% names(sceSubset)) {
stop("'annotation' must be an annotation stored within the specified
slot of the SingleCellExperiment object.")
}
annotation.ix <- match(annotation, names(sceSubset))
if (slot == "assays" && !is.null(feature)) {
counts <- sceSubset[[annotation.ix]]
if (feature %in% rownames(counts)) {
counts <- counts[feature, ]
}
} else if (slot == "colData") {
counts <- sceSubset[, annotation.ix]
} else if (slot == "metadata") {
counts <- sceSubset[[annotation.ix]]
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
countsSub <- counts[sampleInd]
if (!is.null(groupBy)) {
groupbySub <- groupBy[sampleInd]
} else {
groupbySub <- NULL
}
if (!is.null(title) && length(samples) > 1) {
title <- paste(title, x, sep = "_")
}
p <- .ggDensity(
value = countsSub,
groupBy = groupbySub,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize
)
return(p)
})
if(!is.null(feature)){
names(plotlist) <- feature
}
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}
return(plotlist)
}
#' @title Plots for runEmptyDrops outputs.
#' @description A plotting function which visualizes outputs from the
#' runEmptyDrops function stored in the colData slot of the SingleCellExperiment
#' object via scatterplot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results from
#' \link{runEmptyDrops}. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' Default NULL.
#' @param fdrCutoff Numeric. Thresholds barcodes based on the FDR values from
#' runEmptyDrops as "Empty Droplet" or "Putative Cell". Default 0.01.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param dotSize Size of dots. Default 1.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 18.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 12.
#' @param axisLabelSize Size of x/y-axis labels. Default 15.
#' @param legendTitle Title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' @param combinePlot Boolean. If multiple plots are generated (multiple
#' samples, etc.), will combined plots using `cowplot::plot_grid`.
#' Default TRUE.
#' @param relHeights Relative heights of plots when combine is set.
#' @param relWidths Relative widths of plots when combine is set.
#' @param samplePerColumn If TRUE, when there are multiple samples and combining by "all",
#' the output .ggplot will have plots from each sample on a single column. Default TRUE.
#' @param sampleRelHeights If there are multiple samples and combining by "all",
#' the relative heights for each plot.
#' @param sampleRelWidths If there are multiple samples and combining by "all",
#' the relative widths for each plot.
#' @return a ggplot object of the scatter plot.
#' @examples
#' data(scExample, package="singleCellTK")
#' sce <- runEmptyDrops(inSCE=sce)
#' plotEmptyDropsScatter(inSCE=sce)
#' @export
plotEmptyDropsScatter <- function(inSCE,
sample = NULL,
fdrCutoff = 0.01,
defaultTheme = TRUE,
dotSize = 1,
title = NULL,
titleSize = 18,
xlab = NULL,
ylab = NULL,
axisSize = 12,
axisLabelSize = 15,
legendTitle = NULL,
legendTitleSize = 12,
legendSize = 10,
combinePlot = "none",
relHeights=1,
relWidths=1,
samplePerColumn = TRUE,
sampleRelHeights = 1,
sampleRelWidths = 1
){
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x){
sceSampleInd <- which(sample == x)
inSCESub <- inSCE[, sceSampleInd]
inSCESub = inSCESub[,!is.na(inSCESub$dropletUtils_emptyDrops_fdr)]
isCell <- unlist(lapply(inSCESub$dropletUtils_emptyDrops_fdr, function(x){
if(!is.na(x)){
if(x <= fdrCutoff){
return("Putative Cell")
}else{
return("Empty Droplet")
}
}
}))
df <- data.frame(x = inSCESub$dropletUtils_emptyDrops_total,
y = -(inSCESub$dropletUtils_emptyDrops_logprob),
isCell = isCell)
p <- ggplot2::ggplot(df, ggplot2::aes_string("x",
"y", color = "isCell")) +
ggplot2::geom_point(size = dotSize) +
ggplot2::guides(colour = ggplot2::guide_legend(override.aes = list(size=2))) +
ggplot2::scale_color_manual(values = c("gray", "red"))
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p)
}
if (!is.null(title)) {
if(length(samples) > 1){
title = paste(title, x, sep = "_")
}
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize),
axis.text.x = ggplot2::element_text(size = axisSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize),
axis.text.y = ggplot2::element_text(size = axisSize))
}
if (!is.null(legendTitle)) {
p <- p + ggplot2::labs(color = legendTitle) +
ggplot2::theme(legend.title=ggplot2::element_text(size=legendTitleSize),
legend.text=ggplot2::element_text(size=legendSize))
} else {
p <- p + ggplot2::labs(color = "") +
ggplot2::theme(legend.text=ggplot2::element_text(size=legendSize))
}
return(p)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
plotlist <- list(Sample = plotlist)
} else {
plotlist <- plotlist[[1]]
}
##Needs to be turned off for Shiny User Interface
if(!combinePlot == "none"){
if(combinePlot == "all" && length(unique(samples)) > 1){
return(cowplot::plot_grid(plotlist = unlist(plotlist,
recursive = FALSE),
align = "h",
vjust = 0,
rel_heights = sampleRelHeights,
rel_widths = sampleRelWidths))
}else{
return(plotlist)
}
}
return(plotlist)
}
#' @title Plots for runBarcodeRankDrops outputs.
#' @description A plotting function which visualizes outputs from the
#' runBarcodeRankDrops function stored in the colData slot of the SingleCellExperiment
#' object via scatterplot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results from
#' \link{runBarcodeRankDrops}. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' Default NULL.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param dotSize Size of dots. Default 1.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 18.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 12.
#' @param axisLabelSize Size of x/y-axis labels. Default 15.
#' @param legendSize size of legend. Default 10.
#' @param combinePlot Boolean. If multiple plots are generated (multiple
#' samples, etc.), will combined plots using `cowplot::plot_grid`.
#' @param sampleRelHeights If there are multiple samples and combining by "all",
#' the relative heights for each plot.
#' @param sampleRelWidths If there are multiple samples and combining by "all",
#' the relative widths for each plot.
#' Default TRUE.
#' @return a ggplot object of the scatter plot.
#' @examples
#' data(scExample, package="singleCellTK")
#' sce <- runBarcodeRankDrops(inSCE=sce)
#' plotBarcodeRankScatter(inSCE=sce)
#' @export
plotBarcodeRankScatter <- function(inSCE,
sample = NULL,
defaultTheme = TRUE,
dotSize = 1,
title = NULL,
titleSize = 18,
xlab = NULL,
ylab = NULL,
axisSize = 12,
axisLabelSize = 15,
legendSize = 10,
combinePlot = "none",
sampleRelHeights = 1,
sampleRelWidths = 1){
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
meta <- S4Vectors::metadata(inSCE)$runBarcodeRanksMetaOutput
plotlist <- lapply(samples, function(x){
sampleMeta <- meta[[x]]
knee <- sampleMeta$dropletUtils_barcodeRank_knee
inflection <- sampleMeta$dropletUtils_barcodeRank_inflection
df <- data.frame(rank = sampleMeta$dropletUtils_barcodeRank_rank,
umi = sampleMeta$dropletUtils_barcodeRank_total)
p <- ggplot2::ggplot(df, ggplot2::aes_string(x="rank", y="umi")) +
ggplot2::geom_point(size=dotSize, shape=20) +
ggplot2::scale_x_log10() +
ggplot2::scale_y_log10()
p <- p + ggplot2::geom_hline(ggplot2::aes(yintercept=knee, linetype = "Knee"), colour = 'red') +
ggplot2::geom_hline(ggplot2::aes(yintercept=inflection, linetype = "Inflection"), colour= 'blue') +
ggplot2::scale_linetype_manual(name = "", values = c(2, 2),
guide = ggplot2::guide_legend(label.theme = ggplot2::element_text(size = legendSize),
override.aes = list(color = c("blue", "red"))))
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p)
}
if (!is.null(title)) {
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize),
axis.text.x = ggplot2::element_text(size = axisSize))
}else{
p <- p + ggplot2::xlab("Rank") +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize),
axis.text.x = ggplot2::element_text(size = axisSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize),
axis.text.y = ggplot2::element_text(size = axisSize))
}else{
p <- p + ggplot2::ylab("Total UMI Counts") +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize),
axis.text.y = ggplot2::element_text(size = axisSize))
}
return(p)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
plotlist <- list(Sample = plotlist)
} else {
plotlist <- plotlist[[1]]
}
##Needs to be turned off for Shiny User Interface
if(!combinePlot == "none"){
if(combinePlot %in% c("all") && length(unique(sample)) > 1){
return(cowplot::plot_grid(plotlist = unlist(plotlist,
recursive = FALSE),
align = "h",
vjust = 0,
rel_heights = sampleRelHeights,
rel_widths = sampleRelWidths))
}else if(combinePlot == "sample"){
return(plotlist)
}
}
return(plotlist)
}
#' @title Bar plot plotting tool.
#' @description Visualizes specified values via a violin plot.
#' @param y Numeric values to be plotted on y-axis.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @return a ggplot of the reduced dimensions.
#' @importFrom dplyr group_by
#' @importFrom dplyr summarize
#' @importFrom dplyr %>%
.ggBar <- function(y,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = 15) {
if (is.null(groupBy)) {
groupBy <- rep("Sample", length(y))
}
df <- data.frame(x = groupBy, y = y)
p <- ggplot2::ggplot(df) +
ggplot2::aes_string(
x = "groupBy",
y = "y"
)
p <- p + ggplot2::geom_bar(stat = "identity")
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p)
}
if (!is.null(title)) {
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
###
p <- p + ggplot2::theme(axis.text.y = ggplot2::element_text(size = axisSize))
###
if(length(unique(df$groupBy)) > 1){
p <- p + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 45,
hjust = 1,
size = axisSize))
}else{
p <- p + ggplot2::theme(axis.text.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
axis.title.x = ggplot2::element_blank())
}
if (gridLine == TRUE){
p <- p + ggplot2::theme(panel.grid.major.y = ggplot2::element_line("grey"))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(summary)){
if(summary == "mean"){
summ <- df %>% dplyr::group_by(groupBy) %>% dplyr::summarize(value = base::mean(y))
fun <- base::mean
}else if(summary == "median"){
summ <- df %>% dplyr::group_by(groupBy) %>% dplyr::summarize(value = stats::median(y))
fun <- stats::median
}else{
stop("`summary`` must be either `mean` or `median`.")
}
summ$statY <- max(df$y) + (max(df$y) - min(df$y)) * 0.1
summary <- paste(toupper(substr(summary, 1, 1)),
substr(summary, 2, nchar(summary)), sep="")
summ$label <- paste0(summary,": ", round(summ$value, 5))
p <- p + ggplot2::geom_text(data = summ,
ggplot2::aes_string(x = "groupBy",
y = "statY",
label = "label"),
size = 5)
p <- p + ggplot2::stat_summary(fun = fun, fun.min = fun,
fun.max = fun,
geom = "crossbar",
color = "red",
linetype = "dashed")
}
return(p)
}
#' @title Bar plot of colData.
#' @description Visualizes values stored in the colData slot of a
#' SingleCellExperiment object via a bar plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param coldata colData value that will be plotted.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Boolean. If multiple plots are generated (multiple
#' samples, etc.), will combined plots using `cowplot::plot_grid`.
#' Default TRUE.
#' @return a ggplot of the barplot of coldata.
#' @examples
#' plotSCEBarColData(
#' inSCE = mouseBrainSubsetSCE,
#' coldata = "age", groupBy = "sex"
#' )
#' @export
plotSCEBarColData <- function(inSCE,
sample = NULL,
coldata,
groupBy = NULL,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = TRUE) {
if (!is.null(coldata)) {
if (!coldata %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(coldata), "' is not found in ColData.")
}
coldata <- SummarizedExperiment::colData(inSCE)[, coldata]
} else {
stop("You must define the desired colData to plot.")
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(coldata)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop("'sample' must be the same length as the number",
" of columns in 'inSCE'")
}
} else {
sample <- rep(1, ncol(inSCE))
}
p <- .ggBar(
y = coldata,
groupBy = groupBy,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize
)
return(p)
}
#' @title Bar plot of assay data.
#' @description Visualizes values stored in the assay slot of a
#' SingleCellExperiment object via a bar plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param useAssay Indicate which assay to use. Default "counts".
#' @param feature Name of feature stored in assay of SingleCellExperiment
#' object.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Boolean. If multiple plots are generated (multiple
#' samples, etc.), will combined plots using `cowplot::plot_grid`.
#' Default TRUE.
#' @return a ggplot of the barplot of assay data.
#' @examples
#' plotSCEBarAssayData(
#' inSCE = mouseBrainSubsetSCE,
#' feature = "Apoe", groupBy = "sex"
#' )
#' @export
plotSCEBarAssayData <- function(inSCE,
sample = NULL,
useAssay = "counts",
feature,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = TRUE) {
mat <- getBiomarker(
inSCE = inSCE,
useAssay = useAssay,
gene = feature,
binary = "Continuous"
)
counts <- mat[, 2]
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
p <- .ggBar(
y = counts,
groupBy = groupBy,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize
)
return(p)
}
.binSCTK <- function(value, bin, binLabel = NULL) {
if (!is.null(binLabel)) {
if (length(bin) == 1) {
if (bin != length(binLabel)) {
stop("'binLabel' must be equal to the bin length")
}
} else if (length(bin) > 1) {
if (bin != length(binLabel) + 1) {
stop("'binLabel' must be equal to the bin length")
}
}
}
value.bin <- cut(x = value, breaks = bin, labels = binLabel)
return(value.bin)
}
.ggSCTKCombinePlots <- function(plotlist,
ncols = NULL,
nrows = NULL,
combinePlot = "all",
relHeights = 1,
relWidths = 1,
labels = "default",
labelPositionX = NULL,
labelPositionY = NULL,
labelSize = 20,
samplePerColumn = TRUE,
sampleRelHeights = 1,
sampleRelWidths = 1) {
if ("Violin" %in% names(plotlist)) {
plotlistViolin <- plotlist$Violin
} else {
plotlistViolin <- NULL
}
if ("Sample" %in% names(plotlist)) {
plotlistSample <- plotlist$Sample
if (samplePerColumn) {
ncols <- 1
nrowSub <- 1
sampleRelHeights <- 1
}else{
nrowSub = NULL
}
plotlistSample <- lapply(plotlistSample, function(x) {
if(all(class(x) %in% c("gg","ggplot"))){
return(x)
}else if (inherits(x, "list")){
return(cowplot::plot_grid(
plotlist = x,
align = "h",
nrow = nrowSub,
vjust = 0,
rel_heights = sampleRelHeights,
rel_widths = sampleRelWidths
))
}
})
}else{
plotlistSample <- NULL
}
if(!is.null(plotlistViolin) | !is.null(plotlistSample)){
plotlist <- c(plotlistViolin, plotlistSample)
}
# To make the resulting plot close to a square as possible
if (is.null(ncols) && is.null(nrows)) {
ncols <- round(sqrt(length(plotlist)))
}
if (combinePlot == "all") {
if (!is.null(labels) && labels != "none") {
# If default, sample name will be used as labels
if(length(labels) == 1){
if (labels == "default") {
if(!is.null(names(plotlist))){
labels <- names(plotlist)
}
}
}
listNamePlot <- list()
if(is.null(labelPositionX)){
labelPositionX = rep(0, length(plotlist))
}
if(is.null(labelPositionY)){
labelPositionY = rep(1, length(plotlist))
}
for(x in seq_along(plotlist)){
labeled <- plotlist[[x]] + cowplot::draw_plot_label(
labels[x],
x = labelPositionX[x],
y = labelPositionY[x],
size = labelSize)
listNamePlot[[x]] <- labeled
}
plotlist <- listNamePlot
}
plotRes <- cowplot::plot_grid(
plotlist = plotlist,
ncol = ncols,
nrow = nrows,
rel_heights = relHeights,
rel_widths = relWidths
)
return(plotRes)
} else if (combinePlot == "sample") {
#Will happen if "sample" is chosen and multiple samples exist,
#whcih means there will be a plotlistViolin object
if (!is.null(plotlistViolin)) {
return(list(Violin = plotlistViolin, Sample = plotlistSample))
#Will happen when calling the non-QC plot fxns (ie, plotSCEScatter, plotSCEViolin)
#for multiple samples, meaning no merging has occurred across plots
}else if (!is.null(plotlistSample)){
return(plotlistSample)
# #Will happen when?
# }else if(length(plotlist) == 1) {
# return(plotlist[[1]])
#Will happen when sample = NULL, combinePlot = "sample", meaning up to this point
#the "plotlist" should be a list of individual plots for only one sample
} else{
return(cowplot::plot_grid(
plotlist = plotlist,
ncol = ncols,
nrow = nrows,
rel_heights = relHeights,
rel_widths = relWidths
))
}
}
}
.ggSCTKTheme <- function(gg) {
return(gg + ggplot2::theme_bw() +
ggplot2::theme(
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
axis.text = ggplot2::element_text(size = 10),
axis.title = ggplot2::element_text(size = 10)
))
}
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Defines functions .ggSCTKTheme .ggSCTKCombinePlots .binSCTK plotSCEBarAssayData plotSCEBarColData .ggBar plotBarcodeRankScatter plotEmptyDropsScatter plotSCEDensity plotSCEDensityAssayData plotSCEDensityColData .ggDensity plotSCEViolin plotSCEViolinAssayData plotSCEViolinColData .ggViolin plotSCEScatter plotSCEDimReduceFeatures plotSCEDimReduceColData .ggScatter
Documented in .ggBar .ggDensity .ggScatter .ggViolin plotBarcodeRankScatter plotEmptyDropsScatter plotSCEBarAssayData plotSCEBarColData plotSCEDensity plotSCEDensityAssayData plotSCEDensityColData plotSCEDimReduceColData plotSCEDimReduceFeatures plotSCEScatter plotSCEViolin plotSCEViolinAssayData plotSCEViolinColData
#' @title Plot results of reduced dimensions data.
#' @description Plot results of reduced dimensions data and colors the plots by
#' the input vector.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param colorBy If provided, colors dots in the scatterplot based on value.
#' @param groupBy If provided, facet wrap the scatterplot based on value.
#' @param conditionClass class of the annotation data used in colorBy. Options
#' are NULL, "factor" or "numeric". If NULL, class will default to the original
#' class. Default NULL.
#' @param shape If provided, add shapes based on the value.
#' @param reducedDimName Saved dimension reduction name in the
#' \linkS4class{SingleCellExperiment} object. Required.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dim1 1st dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param dim2 2nd dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param bin Numeric vector. If single value, will divide the numeric values into the `bin` groups.
#' If more than one value, will bin numeric values using values as a cut point.
#' @param binLabel Character vector. Labels for the bins created by the `bin` parameter.
#' Default NULL.
#' @param dotSize Size of dots. Default 2.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param colorScale Vector. Needs to be same length as the
#' number of unique levels of `colorBy`. Will be used only if
#' conditionClass = "factor" or "character". Default NULL.
#' @param colorLow Character. A color available from `colors()`.
#' The color will be used to signify the lowest values on the scale.
#' Default 'white'. Will be used only if conditionClass = "numeric".
#' @param colorMid Character. A color available from `colors()`.
#' The color will be used to signify the midpoint on the scale.
#' Default 'gray'. Will be used only if conditionClass = "numeric".
#' @param colorHigh Character. A color available from `colors()`.
#' The color will be used to signify the highest values on the scale.
#' Default 'blue'. Will be used only if conditionClass = "numeric".
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param labelClusters Logical. Whether the cluster labels are plotted.
#' Default FALSE.
#' @param legendTitle title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the reduced dimensions.
.ggScatter <- function(inSCE,
sample = NULL,
colorBy = NULL,
groupBy = NULL,
shape = NULL,
reducedDimName,
conditionClass = NULL,
labelClusters = FALSE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dim1 = NULL,
dim2 = NULL,
bin = NULL,
binLabel = NULL,
dotSize = 2,
transparency = 1,
colorScale = NULL,
colorLow = "white",
colorMid = "gray",
colorHigh = "blue",
defaultTheme = TRUE,
title = NULL,
titleSize = 15,
legendTitle = NULL,
legendTitleSize = 12,
legendSize = 10,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x){
sceSampleInd <- which(sample == x)
inSCESub <- inSCE[, sceSampleInd]
colorBySub <- colorBy[sceSampleInd]
dataframe <- data.frame(SingleCellExperiment::reducedDim(
inSCESub,
reducedDimName
))
# If dim1 and dim2 are specified
if (!is.null(dim1) & !is.null(dim2)) {
if (is.character(dim1) & is.character(dim2)) {
if (!(dim1 %in% colnames(dataframe))) {
stop("X dimension ", dim1, " is not in the reducedDim data")
}
if (!(dim2 %in% colnames(dataframe))) {
stop("Y dimension ", dim2, " is not in the reducedDim data")
}
dataframe <- dataframe[, c(dim1, dim2)]
} else if (is.numeric(dim1) && is.numeric(dim2)) {
dataframe <- dataframe[, c(dim1, dim2)]
}
} else if (ncol(dataframe) > 2) {
warning("More than two dimensions supplied in reducedDims.
Using the first two.")
}
# If xlab and ylab are specified
if (!is.null(xlab) & !is.null(ylab)) {
colnames(dataframe) <- c(xlab, ylab)
# If reduced dimension matrix didnt have colnames
} else {
colnames(dataframe) <- c(paste0(reducedDimName, "_1"),
paste0(reducedDimName, "_2"))
}
xdim <- colnames(dataframe)[1]
ydim <- colnames(dataframe)[2]
if (!is.null(conditionClass) & !is.null(colorBySub)) {
if (conditionClass %in% c("character", "factor", "numeric")) {
if (conditionClass == "character") {
colorBySub <- as.character(colorBySub)
} else if (conditionClass == "factor") {
colorBySub <- as.factor(colorBySub)
} else if (conditionClass == "numeric") {
colorBySub <- as.numeric(colorBySub)
}
}
}
if (!is.null(bin) & !is.null(colorBySub)) {
colorBySub <- .binSCTK(
value = colorBySub,
bin = bin,
binLabel = binLabel
)
}
if (!is.null(colorBySub)) {
dataframe$color <- colorBySub
}
if (!is.null(groupBy)){
dataframe$groups <- factor(SingleCellExperiment::colData(inSCE)@listData[[groupBy]])
}
if (!is.null(shape)) {
dataframe$shape <- factor(SingleCellExperiment::colData(inSCESub)[, shape])
}
dataframe$Sample <- colnames(inSCESub)
g <- ggplot2::ggplot(dataframe, ggplot2::aes_string(xdim, ydim,
label = "Sample")) + ggplot2::geom_point(size = dotSize,
alpha = transparency)
if (!is.null(colorBySub)) {
g <- g + ggplot2::aes_string(color = "color")
}
if (inherits(colorBySub, "numeric")){
g <- g + ggplot2::scale_color_gradient2(
low = colorLow,
mid = colorMid,
high = colorHigh,
aesthetics = "colour",
midpoint = mean(colorBySub))
}else if (inherits(colorBySub, "character") | inherits(colorBySub, "factor")){
g <- g +
ggplot2::guides(colour = ggplot2::guide_legend(override.aes = list(size = 2)))
if(all(!is.null(colorScale))){
g <- g+ ggplot2::scale_color_manual(values=c(colorScale))
}
}
if (!is.null(shape)) {
g <- g + ggplot2::aes_string(shape = "shape") +
ggplot2::labs(shape = shape)
}
if (defaultTheme == TRUE) {
g <- .ggSCTKTheme(g)
}
g <- g + ggplot2::theme(axis.title =
ggplot2::element_text(size = axisLabelSize),
axis.text =
ggplot2::element_text(size = axisSize))
if (!is.null(title)) {
if (length(samples) > 1) {
title <- paste(title, x, sep = "_")
}
g <- g + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
if (!is.null(legendTitle)) {
g <- g + ggplot2::labs(color = legendTitle) +
ggplot2::theme(legend.title=ggplot2::element_text(size=legendTitleSize),
legend.text=ggplot2::element_text(size=legendSize))
} else {
g <- g + ggplot2::labs(color = "") +
ggplot2::theme(legend.text=ggplot2::element_text(size=legendSize))
}
if (!is.null(groupBy)){
g <- g + ggplot2::facet_wrap(~groups)
}
if (isTRUE(labelClusters) && class(colorBySub) %in% c("character", "factor")) {
centroidList <- lapply(unique(colorBySub), function(x) {
dataframe.sub <- dataframe[dataframe$color == x, ]
median.1 <- stats::median(dataframe.sub[, 1])
median.2 <- stats::median(dataframe.sub[, 2])
cbind(median.1, median.2, as.character(x))
})
centroid <- do.call(rbind, centroidList)
centroid <- data.frame(
Dimension_1 = as.numeric(centroid[, 1]),
Dimension_2 = as.numeric(centroid[, 2]),
color = centroid[, 3],
Sample = rep(1, length(unique(colorBySub)))
)
if (!is.null(shape)) {
centroid$shape <- dataframe$shape[1]
}
if (!is.null(groupBy)){
g <- g + ggplot2::facet_wrap(~groups)
}
colnames(centroid)[seq_len(2)] <- c(xdim, ydim)
g <- g + ggplot2::geom_point(
data = centroid,
mapping = ggplot2::aes_string(x = xdim, y = ydim),
size = 0,
alpha = 0
) +
ggrepel::geom_text_repel(
data = centroid,
mapping = ggplot2::aes_string(label = "color"),
show.legend = FALSE,
color = "black"
)
}
return(g)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
plotlist <- list(Sample = plotlist)
}
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}else if(combinePlot == "none" && length(plotlist) == 1){
plotlist <- plotlist[[1]]
}
return(plotlist)
}
#' @title Dimension reduction plot tool for colData
#' @description Plot results of reduced dimensions data and
#' colors by annotation data stored in the colData slot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param colorBy Color by a condition(any column of the annotation data).
#' Required.
#' @param groupBy Group by a condition(any column of the annotation data).
#' Default NULL.
#' @param conditionClass Class of the annotation data used in colorBy.
#' Options are NULL, "factor" or "numeric". If NULL, class will default to the
#' original class. Default NULL.
#' @param shape Add shapes to each condition.
#' @param reducedDimName Saved dimension reduction matrix name in the
#' \linkS4class{SingleCellExperiment} object. Required.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param dim1 1st dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param dim2 2nd dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param bin Numeric vector. If single value, will divide the numeric values into the `bin` groups.
#' If more than one value, will bin numeric values using values as a cut point.
#' @param binLabel Character vector. Labels for the bins created by the `bin` parameter.
#' Default NULL.
#' @param dotSize Size of dots. Default 2.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param colorScale Vector. Needs to be same length as the
#' number of unique levels of colorBy. Will be used only if
#' conditionClass = "factor" or "character". Default NULL.
#' @param colorLow Character. A color available from `colors()`.
#' The color will be used to signify the lowest values on the scale.
#' Default 'white'.
#' @param colorMid Character. A color available from `colors()`.
#' The color will be used to signify the midpoint on the scale.
#' Default 'gray'.
#' @param colorHigh Character. A color available from `colors()`.
#' The color will be used to signify the highest values on the scale.
#' Default 'blue'.
#' @param defaultTheme adds grid to plot when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param labelClusters Logical. Whether the cluster labels are plotted.
#' @param legendTitle title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' Default FALSE.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the reduced dimension plot of coldata.
#' @examples
#' plotSCEDimReduceColData(
#' inSCE = mouseBrainSubsetSCE, colorBy = "tissue",
#' shape = NULL, conditionClass = "factor",
#' reducedDimName = "TSNE_counts",
#' xlab = "tSNE1", ylab = "tSNE2", labelClusters = TRUE
#' )
#'
#' plotSCEDimReduceColData(
#' inSCE = mouseBrainSubsetSCE, colorBy = "age",
#' shape = NULL, conditionClass = "numeric",
#' reducedDimName = "TSNE_counts", bin = c(-Inf, 20, 25, +Inf),
#' xlab = "tSNE1", ylab = "tSNE2", labelClusters = FALSE
#' )
#' @export
plotSCEDimReduceColData <- function(inSCE,
sample = NULL,
colorBy,
groupBy = NULL,
conditionClass = NULL,
shape = NULL,
reducedDimName = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dim1 = NULL,
dim2 = NULL,
bin = NULL,
binLabel = NULL,
dotSize = 2,
transparency = 1,
colorScale = NULL,
colorLow = "white",
colorMid = "gray",
colorHigh = "blue",
defaultTheme = TRUE,
title = NULL,
titleSize = 15,
labelClusters = TRUE,
legendTitle = NULL,
legendTitleSize = 12,
legendSize = 10,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
colorPlot <- SingleCellExperiment::colData(inSCE)[, colorBy]
g <- .ggScatter(
inSCE = inSCE,
sample = sample,
colorBy = colorPlot,
groupBy = groupBy,
conditionClass = conditionClass,
shape = shape,
reducedDimName = reducedDimName,
xlab = xlab,
ylab = ylab,
dim1 = dim1,
dim2 = dim2,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
bin = bin,
binLabel = binLabel,
dotSize = dotSize,
transparency = transparency,
colorScale = colorScale,
colorLow = colorLow,
colorMid = colorMid,
colorHigh = colorHigh,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize,
labelClusters = labelClusters,
legendTitle = legendTitle,
legendTitleSize = legendTitleSize,
legendSize = legendSize,
combinePlot = combinePlot,
plotLabels = plotLabels
)
return(g)
}
#' @title Dimension reduction plot tool for assay data
#' @description Plot results of reduced dimensions data and
#' colors by feature data stored in the assays slot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param feature name of feature stored in assay of singleCellExperiment
#' object. Plot will be colored based on feature value.
#' @param shape add shapes to each condition. Default NULL.
#' @param reducedDimName saved dimension reduction name in the
#' \linkS4class{SingleCellExperiment} object. Required.
#' @param useAssay Indicate which assay to use. The default is "logcounts"
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dim1 1st dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param dim2 2nd dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' Default is second PCA component for PCA data and NULL otherwise.
#' @param bin Numeric vector. If single value, will divide the numeric values into the `bin` groups.
#' If more than one value, will bin numeric values using values as a cut point.
#' @param binLabel Character vector. Labels for the bins created by the `bin` parameter.
#' Default NULL.
#' @param dotSize Size of dots. Default 2.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param colorLow Character. A color available from `colors()`.
#' The color will be used to signify the lowest values on the scale.
#' Default 'white'.
#' @param colorMid Character. A color available from `colors()`.
#' The color will be used to signify the midpoint on the scale.
#' Default 'gray'.
#' @param colorHigh Character. A color available from `colors()`.
#' The color will be used to signify the highest values on the scale.
#' Default 'blue'.
#' @param defaultTheme adds grid to plot when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param legendTitle title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' @param groupBy Facet wrap the scatterplot based on value.
#' Default \code{NULL}.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the reduced dimension plot of feature data.
#' @examples
#' plotSCEDimReduceFeatures(
#' inSCE = mouseBrainSubsetSCE, feature = "Apoe",
#' shape = NULL, reducedDimName = "TSNE_counts",
#' useAssay = "counts", xlab = "tSNE1", ylab = "tSNE2"
#' )
#' @export
plotSCEDimReduceFeatures <- function(inSCE,
sample = NULL,
feature,
shape = NULL,
reducedDimName,
useAssay = "logcounts",
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dim1 = NULL,
dim2 = NULL,
bin = NULL,
binLabel = NULL,
dotSize = 2,
transparency = 1,
colorLow = "white",
colorMid = "gray",
colorHigh = "blue",
defaultTheme = TRUE,
title = NULL,
titleSize = 15,
legendTitle = NULL,
legendSize = 10,
legendTitleSize = 12,
groupBy = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
mat <- getBiomarker(
inSCE = inSCE,
useAssay = useAssay,
gene = feature,
binary = "Continuous"
)
counts <- mat[, 2]
g <- .ggScatter(
inSCE = inSCE,
sample = sample,
conditionClass = "numeric",
colorBy = counts,
shape = shape,
transparency = 1,
colorLow = colorLow,
colorMid = colorMid,
colorHigh = colorHigh,
reducedDimName = reducedDimName,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dim1 = dim1,
dim2 = dim2,
bin = bin,
binLabel = binLabel,
defaultTheme = defaultTheme,
dotSize = dotSize,
title = title,
titleSize = titleSize,
legendTitle = legendTitle,
legendTitleSize = legendTitleSize,
legendSize = legendSize,
groupBy = groupBy,
combinePlot = combinePlot,
plotLabels = plotLabels
)
return(g)
}
#' @title Dimension reduction plot tool for all types of data
#' @description Plot results of reduced dimensions data of counts stored in any
#' slot in the SingleCellExperiment object.
#' @param inSCE Input SingleCellExperiment object with saved dimension reduction
#' components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param slot Desired slot of SingleCellExperiment used for plotting. Possible
#' options: "assays", "colData", "metadata", "reducedDims". Default NULL.
#' @param annotation Desired vector within the slot used for plotting. Default NULL.
#' @param feature name of feature stored in assay of SingleCellExperiment
#' object. Will be used only if "assays" slot is chosen. Default NULL.
#' @param groupBy Group by a condition(any column of the annotation data).
#' Default NULL.
#' @param shape add shapes to each condition.
#' @param reducedDimName saved dimension reduction name in the
#' \linkS4class{SingleCellExperiment} object. Required.
#' @param conditionClass class of the annotation data used in colorBy. Options
#' are NULL, "factor" or "numeric". If NULL, class will default to the original
#' class. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dim1 1st dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' @param dim2 2nd dimension to be used for plotting. Can either be a string which specifies
#' the name of the dimension to be plotted from reducedDims, or a numeric value which specifies
#' the index of the dimension to be plotted. Default is NULL.
#' Default is second PCA component for PCA data and NULL otherwise.
#' @param bin Numeric vector. If single value, will divide the numeric values into the `bin` groups.
#' If more than one value, will bin numeric values using values as a cut point.
#' @param binLabel Character vector. Labels for the bins created by the `bin` parameter.
#' Default NULL.
#' @param dotSize Size of dots. Default 2.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param colorLow Character. A color available from `colors()`.
#' The color will be used to signify the lowest values on the scale.
#' Default 'white'.
#' @param colorMid Character. A color available from `colors()`.
#' The color will be used to signify the midpoint on the scale.
#' Default 'gray'.
#' @param colorHigh Character. A color available from `colors()`.
#' The color will be used to signify the highest values on the scale.
#' Default 'blue'.
#' @param defaultTheme adds grid to plot when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param labelClusters Logical. Whether the cluster labels are plotted.
#' @param legendTitle title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the reduced dimensions.
#' @examples
#' plotSCEScatter(
#' inSCE = mouseBrainSubsetSCE, legendTitle = NULL,
#' slot = "assays", annotation = "counts", feature = "Apoe",
#' reducedDimName = "TSNE_counts", labelClusters = FALSE
#' )
#' @export
#' @import SingleCellExperiment
plotSCEScatter <- function(inSCE,
slot = NULL,
sample = NULL,
annotation,
feature = NULL,
groupBy = NULL,
shape = NULL,
reducedDimName = NULL,
conditionClass = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dim1 = NULL,
dim2 = NULL,
bin = NULL,
binLabel = NULL,
dotSize = 2,
transparency = 1,
colorLow = "white",
colorMid = "gray",
colorHigh = "blue",
defaultTheme = TRUE,
title = NULL,
titleSize = 15,
labelClusters = TRUE,
legendTitle = NULL,
legendTitleSize = 12,
legendSize = 10,
combinePlot = "none",
plotLabels = NULL){
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!is.null(slot)){
if (slot == "reducedDims"){
annotation_clm <- substr(annotation, stringr::str_length(annotation), stringr::str_length(annotation))
annotation <- substr(annotation, 1, stringr::str_length(annotation) - 2)
}else if (!slot %in% methods::slotNames(inSCE)) {
stop("'slot' must be a slot within the SingleCellExperiment object.
Please run 'methods::slotNames' if you are unsure the
specified slot exists.")
}
sceSubset <- do.call(slot, args = list(inSCE))
if (!annotation %in% names(sceSubset)) {
stop("'annotation' must be an annotation stored within the specified
slot of the SingleCellExperiment object.")
}
annotation.ix <- match(annotation, c(names(sceSubset)))
}
if (is.null(slot)){
colorPlot <- NULL
}else if (slot == "assays" && !is.null(feature)) {
counts <- sceSubset[[annotation.ix]]
if (feature %in% rownames(counts)) {
colorPlot <- counts[feature, ]
}
} else if (slot == "colData") {
colorPlot <- sceSubset[, annotation.ix]
} else if (slot == "metadata") {
colorPlot <- sceSubset[[annotation.ix]]
} else if (slot == "reducedDims") {
colorPlot <- sceSubset[[annotation.ix]][, as.numeric(annotation_clm)]
}
g <- .ggScatter(
inSCE = inSCE,
sample = sample,
colorBy = colorPlot,
groupBy = groupBy,
conditionClass = conditionClass,
shape = shape,
reducedDimName = reducedDimName,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dim1 = dim1,
dim2 = dim2,
bin = bin,
binLabel = binLabel,
dotSize = dotSize,
transparency = transparency,
colorLow = colorLow,
colorMid = colorMid,
colorHigh = colorHigh,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize,
labelClusters = labelClusters,
legendTitle = legendTitle,
legendTitleSize = legendTitleSize,
legendSize = legendSize,
combinePlot = combinePlot
)
return(g)
}
#' @title Violin plot plotting tool.
#' @description Visualizes specified values via a violin plot.
#' @param y Numeric values to be plotted on y-axis.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param violin Boolean. If TRUE, will plot the violin plot. Default TRUE.
#' @param boxplot Boolean. If TRUE, will plot boxplots for each violin plot.
#' Default TRUE.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @return a ggplot of the reduced dimensions.
#' @importFrom dplyr group_by
#' @importFrom dplyr summarize
#' @importFrom dplyr %>%
.ggViolin <- function(y,
groupBy = NULL,
violin = TRUE,
boxplot = TRUE,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = 15) {
if (is.null(groupBy)) {
groupBy <- rep("Sample", length(y))
}
df <- data.frame(groupBy = groupBy, y = y)
p <- ggplot2::ggplot(df) +
ggplot2::aes_string(
x = "groupBy",
y = "y"
)
if (dots == TRUE) {
p <- p + ggplot2::geom_jitter(
color = "blue",
width = 0.2,
height = 0,
size = dotSize,
alpha = transparency
)
}
if (boxplot == TRUE) {
p <- p + ggplot2::geom_boxplot(width = 0.5,
alpha = 0)
}
if (violin == TRUE) {
p <- p + ggplot2::geom_violin(trim = TRUE,
scale = "width",
size = 1,
fill = "grey",
alpha = 0.75)
}
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p)
}
if (!is.null(title)) {
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
###
p <- p + ggplot2::theme(axis.text.y = ggplot2::element_text(size = axisSize))
###
if(length(unique(df$groupBy)) > 1){
p <- p + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 45,
hjust = 1,
size = axisSize))
}else{
p <- p + ggplot2::theme(axis.text.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
axis.title.x = ggplot2::element_blank())
}
if (gridLine == TRUE){
p <- p + ggplot2::theme(panel.grid.major.y = ggplot2::element_line("grey"))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(summary)){
if(summary == "mean"){
summ <- df %>% dplyr::group_by(groupBy) %>% dplyr::summarize(value = base::mean(y))
fun <- base::mean
}else if(summary == "median"){
summ <- df %>% dplyr::group_by(groupBy) %>% dplyr::summarize(value = stats::median(y))
fun <- stats::median
}else{
stop("`summary`` must be either `mean` or `median`.")
}
summ$statY <- max(df$y) + (max(df$y) - min(df$y)) * 0.1
summary <- paste(toupper(substr(summary, 1, 1)),
substr(summary, 2, nchar(summary)), sep="")
summ$label <- paste0(summary,": ", round(summ$value, 5))
p <- p + ggplot2::geom_text(data = summ,
ggplot2::aes_string(x = "groupBy",
y = "statY",
label = "label"),
size = 5)
p <- p + ggplot2::stat_summary(fun = fun, fun.min = fun,
fun.max = fun,
geom = "crossbar",
color = "red",
linetype = "dashed")
}
return(p)
}
#' @title Violin plot of colData.
#' @description Visualizes values stored in the colData slot of a
#' SingleCellExperiment object via a violin plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param coldata colData value that will be plotted.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param violin Boolean. If TRUE, will plot the violin plot. Default TRUE.
#' @param boxplot Boolean. If TRUE, will plot boxplots for each violin plot.
#' Default TRUE.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the violin plot of coldata.
#' @examples
#' plotSCEViolinColData(
#' inSCE = mouseBrainSubsetSCE,
#' coldata = "age", groupBy = "sex"
#' )
#' @export
plotSCEViolinColData <- function(inSCE,
sample = NULL,
coldata,
groupBy = NULL,
violin = TRUE,
boxplot = TRUE,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!is.null(coldata)) {
if (!coldata %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(coldata), "' is not found in ColData.")
}
coldata <- SummarizedExperiment::colData(inSCE)[, coldata]
} else {
stop("You must define the desired colData to plot.")
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(coldata)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop("'sample' must be the same length as the number",
" of columns in 'inSCE'")
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
coldataSub <- coldata[sampleInd]
if(!is.null(groupBy)){
groupbySub <- groupBy[sampleInd]
}else{
groupbySub <- NULL
}
if(!is.null(title) && length(samples) > 1){
title = paste(title, x, sep = "_")
}
p <- .ggViolin(
y = coldataSub,
groupBy = groupbySub,
violin = violin,
boxplot = boxplot,
dots = dots,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
gridLine = gridLine,
summary = summary,
title = title,
titleSize = titleSize
)
return(p)
})
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}else if(combinePlot == "none" && length(plotlist) == 1){
plotlist <- plotlist[[1]]
}
return(plotlist)
}
#' @title Violin plot of assay data.
#' @description Visualizes values stored in the assay slot of a
#' SingleCellExperiment object via a violin plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param useAssay Indicate which assay to use. Default "counts".
#' @param feature Name of feature stored in assay of SingleCellExperiment
#' object.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param violin Boolean. If TRUE, will plot the violin plot. Default TRUE.
#' @param boxplot Boolean. If TRUE, will plot boxplots for each violin plot.
#' Default TRUE.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the violin plot of assay data.
#' @examples
#' plotSCEViolinAssayData(
#' inSCE = mouseBrainSubsetSCE,
#' feature = "Apoe", groupBy = "sex"
#' )
#' @export
plotSCEViolinAssayData <- function(inSCE,
sample = NULL,
useAssay = "counts",
feature,
groupBy = NULL,
violin = TRUE,
boxplot = TRUE,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
mat <- getBiomarker(
inSCE = inSCE,
useAssay = useAssay,
gene = feature,
binary = "Continuous"
)
counts <- mat[, 2]
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop("'sample' must be the same length as the number",
" of columns in 'inSCE'")
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
countSub <- counts[sampleInd]
if(!is.null(groupBy)){
groupbySub <- groupBy[sampleInd]
}else{
groupbySub <- NULL
}
p <- .ggViolin(
y = countSub,
groupBy = groupbySub,
violin = violin,
boxplot = boxplot,
dots = dots,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
gridLine = gridLine,
summary = summary,
title = title,
titleSize = titleSize
)
return(p)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
if(combinePlot == "sample"){
plotlist <- c(list(Sample = plotlist))
}
} else {
plotlist <- plotlist[[1]]
}
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}else if(combinePlot == "none" && length(plotlist) == 1){
plotlist <- plotlist[[1]]
}
return(plotlist)
}
#' @title Violin plot of any data stored in the SingleCellExperiment object.
#' @description Visualizes values stored in any slot of a
#' SingleCellExperiment object via a violin plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param slot Desired slot of SingleCellExperiment used for plotting. Possible
#' options: "assays", "colData", "metadata"
#' @param annotation Desired vector within the slot used for plotting.
#' @param feature name of feature stored in assay of SingleCellExperiment
#' object.
#' Will be used only if "assays" slot is chosen. Default NULL.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param violin Boolean. If TRUE, will plot the violin plot. Default TRUE.
#' @param boxplot Boolean. If TRUE, will plot boxplots for each violin plot.
#' Default TRUE.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the violin plot.
#' @examples
#' plotSCEViolin(
#' inSCE = mouseBrainSubsetSCE, slot = "assays",
#' annotation = "counts", feature = "Apoe", groupBy = "sex"
#' )
#' @export
plotSCEViolin <- function(inSCE,
sample = NULL,
slot,
annotation,
feature,
groupBy = NULL,
violin = TRUE,
boxplot = TRUE,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!slot %in% methods::slotNames(inSCE)) {
stop("'slot' must be a slot within the SingleCellExperiment object.
Please run 'methods::slotNames' if you are unsure the
specified slot exists.")
}
sceSubset <- do.call(slot, args = list(inSCE))
if (!annotation %in% names(sceSubset)) {
stop("'annotation' must be an annotation stored within the specified
slot of the SingleCellExperiment object.")
}
annotation.ix <- match(annotation, names(sceSubset))
if (slot == "assays" && !is.null(feature)) {
counts <- sceSubset[[annotation.ix]]
if (feature %in% rownames(counts)) {
counts <- counts[feature, ]
}
} else if (slot == "colData") {
counts <- sceSubset[, annotation.ix]
} else if (slot == "metadata") {
counts <- sceSubset[[annotation.ix]]
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop("'sample' must be the same length as the number",
" of columns in 'inSCE'")
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
countSub <- counts[sampleInd]
if(!is.null(groupBy)){
groupbySub <- groupBy[sampleInd]
}else{
groupbySub <- NULL
}
p <- .ggViolin(
y = countSub,
groupBy = groupbySub,
violin = violin,
boxplot = boxplot,
dots = dots,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
gridLine = gridLine,
summary = summary,
title = title,
titleSize = titleSize
)
return(p)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
if(!is.null(combinePlot)){
if(combinePlot == "sample"){
plotlist <- c(list(Sample = plotlist))
}
}
} else {
plotlist <- plotlist[[1]]
# plotlist <- unlist(plotlist, recursive=F)
}
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample") &&
length(unique(samples)) > 1){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}else if(combinePlot == "none" && length(plotlist) == 1){
plotlist <- plotlist[[1]]
}
return(plotlist)
}
#' @title Density plot plotting tool.
#' @description Visualizes values stored in the specified slot of a
#' SingleCellExperiment object via a density plot.
#' @param value Numeric value that will be plotted via density plot.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param cutoff Numeric value. The plot will be annotated with a vertical line
#' if set. Default NULL.
#' @return density plot, in .ggplot.
.ggDensity <- function(value,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
defaultTheme = TRUE,
title = NULL,
titleSize = 18,
cutoff = NULL) {
if (is.null(groupBy)) {
groupBy <- rep("Sample", length(value))
}
df <- data.frame(x = groupBy, y = value)
p <- ggplot2::ggplot(df, ggplot2::aes_string(x = value)) +
ggplot2::geom_density() +
ggplot2::facet_grid(. ~ x)
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p) +
ggplot2::theme(strip.background = ggplot2::element_blank())
}
if (all(unique(groupBy) == "Sample")) {
p <- p + ggplot2::theme(strip.text.x = ggplot2::element_blank())
}
if (!is.null(title)) {
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize))
}
p <- p + ggplot2::theme(axis.text = ggplot2::element_text(size = axisSize))
if (!is.null(cutoff)) {
p <- p + ggplot2::geom_vline(xintercept = cutoff, color = "red")
}
return(p)
}
#' @title Density plot of colData.
#' @description Visualizes values stored in the colData slot of a
#' SingleCellExperiment object via a density plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param coldata colData value that will be plotted.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param cutoff Numeric value. The plot will be annotated with a vertical line
#' if set. Default NULL.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the density plot of colData.
#' @examples
#' plotSCEDensityColData(
#' inSCE = mouseBrainSubsetSCE,
#' coldata = "age", groupBy = "sex"
#' )
#' @export
plotSCEDensityColData <- function(inSCE,
sample = NULL,
coldata,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
defaultTheme = TRUE,
title = NULL,
titleSize = 18,
cutoff = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!is.null(coldata)) {
if (!coldata %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(coldata), "' is not found in ColData.")
}
coldata <- SummarizedExperiment::colData(inSCE)[, coldata]
} else {
stop("You must define the desired colData to plot.")
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(coldata)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
coldataSub <- coldata[sampleInd]
if (!is.null(groupBy)) {
groupbySub <- groupBy[sampleInd]
} else {
groupbySub <- NULL
}
if (!is.null(title) && length(samples) > 1) {
title <- paste(title, x, sep = "_")
}
p <- .ggDensity(
value = coldataSub,
groupBy = groupbySub,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize,
cutoff = cutoff
)
return(p)
})
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}
return(plotlist)
}
#' @title Density plot of assay data.
#' @description Visualizes values stored in the assay slot of a
#' SingleCellExperiment object via a density plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param useAssay Indicate which assay to use. Default "counts".
#' @param feature Name of feature stored in assay of SingleCellExperiment
#' object.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param cutoff Numeric value. The plot will be annotated with a vertical line
#' if set. Default NULL.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot of the density plot of assay data.
#' @examples
#' plotSCEDensityAssayData(
#' inSCE = mouseBrainSubsetSCE,
#' feature = "Apoe"
#' )
#' @export
plotSCEDensityAssayData <- function(inSCE,
sample = NULL,
useAssay = "counts",
feature,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
defaultTheme = TRUE,
cutoff = NULL,
title = NULL,
titleSize = 18,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
mat <- getBiomarker(
inSCE = inSCE,
useAssay = useAssay,
gene = feature,
binary = "Continuous"
)
counts <- mat[, 2]
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
countsSub <- counts[sampleInd]
if (!is.null(groupBy)) {
groupbySub <- groupBy[sampleInd]
} else {
groupbySub <- NULL
}
if (!is.null(title) && length(samples) > 1) {
title <- paste(title, x, sep = "_")
}
p <- .ggDensity(
value = countsSub,
groupBy = groupbySub,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize,
cutoff = cutoff
)
return(p)
})
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}
return(plotlist)
}
#' @title Density plot of any data stored in the SingleCellExperiment object.
#' @description Visualizes values stored in any slot of a
#' SingleCellExperiment object via a densityn plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required
#' @param slot Desired slot of SingleCellExperiment used for plotting. Possible
#' options: "assays", "colData", "metadata"
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param annotation Desired vector within the slot used for plotting.
#' @param useAssay Indicate which assay to use. Default "counts".
#' @param feature name of feature stored in assay of SingleCellExperiment
#' object. Will be used only if "assays" slot is chosen. Default NULL.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param cutoff Numeric value. The plot will be annotated with a vertical line
#' if set. Default NULL.
#' @param combinePlot Must be either "all", "sample", or "none". "all" will combine all plots into a single
#' .ggplot object, while "sample" will output a list of plots separated by sample. Default "none".
#' @param plotLabels labels to each plot. If set to "default", will use the name of the samples
#' as the labels. If set to "none", no label will be plotted.
#' @return a ggplot object of the density plot.
#' @examples
#' plotSCEDensity(
#' inSCE = mouseBrainSubsetSCE, slot = "assays",
#' annotation = "counts", feature = "Apoe", groupBy = "sex"
#' )
#' @export
plotSCEDensity <- function(inSCE,
slot,
annotation,
sample = NULL,
useAssay = "counts",
feature = NULL,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
defaultTheme = TRUE,
title = NULL,
titleSize = 18,
cutoff = NULL,
combinePlot = "none",
plotLabels = NULL) {
if(!combinePlot %in% c("all", "sample", "none")){
stop("'combinePlot' must be set to either 'all', 'sample', or 'none'.")
}
if (!slot %in% methods::slotNames(inSCE)) {
stop("'slot' must be a slot within the SingleCellExperiment object.
Please run 'methods::slotNames' if you are unsure the
specified slot exists.")
}
sceSubset <- do.call(slot, args = list(inSCE))
if (!annotation %in% names(sceSubset)) {
stop("'annotation' must be an annotation stored within the specified
slot of the SingleCellExperiment object.")
}
annotation.ix <- match(annotation, names(sceSubset))
if (slot == "assays" && !is.null(feature)) {
counts <- sceSubset[[annotation.ix]]
if (feature %in% rownames(counts)) {
counts <- counts[feature, ]
}
} else if (slot == "colData") {
counts <- sceSubset[, annotation.ix]
} else if (slot == "metadata") {
counts <- sceSubset[[annotation.ix]]
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x) {
sampleInd <- which(sample == x)
countsSub <- counts[sampleInd]
if (!is.null(groupBy)) {
groupbySub <- groupBy[sampleInd]
} else {
groupbySub <- NULL
}
if (!is.null(title) && length(samples) > 1) {
title <- paste(title, x, sep = "_")
}
p <- .ggDensity(
value = countsSub,
groupBy = groupbySub,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize
)
return(p)
})
if(!is.null(feature)){
names(plotlist) <- feature
}
##Needs to be turned off for Shiny User Interface
if(combinePlot %in% c("all", "sample")){
figNcol = NULL
if(!is.null(groupBy)){
if(length(unique(groupBy)) > 1){
figNcol = 1
}
}
plotlist <- .ggSCTKCombinePlots(plotlist,
combinePlot = combinePlot,
ncols = figNcol,
labels = plotLabels)
}
return(plotlist)
}
#' @title Plots for runEmptyDrops outputs.
#' @description A plotting function which visualizes outputs from the
#' runEmptyDrops function stored in the colData slot of the SingleCellExperiment
#' object via scatterplot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results from
#' \link{runEmptyDrops}. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' Default NULL.
#' @param fdrCutoff Numeric. Thresholds barcodes based on the FDR values from
#' runEmptyDrops as "Empty Droplet" or "Putative Cell". Default 0.01.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param dotSize Size of dots. Default 1.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 18.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 12.
#' @param axisLabelSize Size of x/y-axis labels. Default 15.
#' @param legendTitle Title of legend. Default NULL.
#' @param legendTitleSize size of legend title. Default 12.
#' @param legendSize size of legend. Default 10.
#' @param combinePlot Boolean. If multiple plots are generated (multiple
#' samples, etc.), will combined plots using `cowplot::plot_grid`.
#' Default TRUE.
#' @param relHeights Relative heights of plots when combine is set.
#' @param relWidths Relative widths of plots when combine is set.
#' @param samplePerColumn If TRUE, when there are multiple samples and combining by "all",
#' the output .ggplot will have plots from each sample on a single column. Default TRUE.
#' @param sampleRelHeights If there are multiple samples and combining by "all",
#' the relative heights for each plot.
#' @param sampleRelWidths If there are multiple samples and combining by "all",
#' the relative widths for each plot.
#' @return a ggplot object of the scatter plot.
#' @examples
#' data(scExample, package="singleCellTK")
#' sce <- runEmptyDrops(inSCE=sce)
#' plotEmptyDropsScatter(inSCE=sce)
#' @export
plotEmptyDropsScatter <- function(inSCE,
sample = NULL,
fdrCutoff = 0.01,
defaultTheme = TRUE,
dotSize = 1,
title = NULL,
titleSize = 18,
xlab = NULL,
ylab = NULL,
axisSize = 12,
axisLabelSize = 15,
legendTitle = NULL,
legendTitleSize = 12,
legendSize = 10,
combinePlot = "none",
relHeights=1,
relWidths=1,
samplePerColumn = TRUE,
sampleRelHeights = 1,
sampleRelWidths = 1
){
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
plotlist <- lapply(samples, function(x){
sceSampleInd <- which(sample == x)
inSCESub <- inSCE[, sceSampleInd]
inSCESub = inSCESub[,!is.na(inSCESub$dropletUtils_emptyDrops_fdr)]
isCell <- unlist(lapply(inSCESub$dropletUtils_emptyDrops_fdr, function(x){
if(!is.na(x)){
if(x <= fdrCutoff){
return("Putative Cell")
}else{
return("Empty Droplet")
}
}
}))
df <- data.frame(x = inSCESub$dropletUtils_emptyDrops_total,
y = -(inSCESub$dropletUtils_emptyDrops_logprob),
isCell = isCell)
p <- ggplot2::ggplot(df, ggplot2::aes_string("x",
"y", color = "isCell")) +
ggplot2::geom_point(size = dotSize) +
ggplot2::guides(colour = ggplot2::guide_legend(override.aes = list(size=2))) +
ggplot2::scale_color_manual(values = c("gray", "red"))
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p)
}
if (!is.null(title)) {
if(length(samples) > 1){
title = paste(title, x, sep = "_")
}
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize),
axis.text.x = ggplot2::element_text(size = axisSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize),
axis.text.y = ggplot2::element_text(size = axisSize))
}
if (!is.null(legendTitle)) {
p <- p + ggplot2::labs(color = legendTitle) +
ggplot2::theme(legend.title=ggplot2::element_text(size=legendTitleSize),
legend.text=ggplot2::element_text(size=legendSize))
} else {
p <- p + ggplot2::labs(color = "") +
ggplot2::theme(legend.text=ggplot2::element_text(size=legendSize))
}
return(p)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
plotlist <- list(Sample = plotlist)
} else {
plotlist <- plotlist[[1]]
}
##Needs to be turned off for Shiny User Interface
if(!combinePlot == "none"){
if(combinePlot == "all" && length(unique(samples)) > 1){
return(cowplot::plot_grid(plotlist = unlist(plotlist,
recursive = FALSE),
align = "h",
vjust = 0,
rel_heights = sampleRelHeights,
rel_widths = sampleRelWidths))
}else{
return(plotlist)
}
}
return(plotlist)
}
#' @title Plots for runBarcodeRankDrops outputs.
#' @description A plotting function which visualizes outputs from the
#' runBarcodeRankDrops function stored in the colData slot of the SingleCellExperiment
#' object via scatterplot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results from
#' \link{runBarcodeRankDrops}. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' Default NULL.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param dotSize Size of dots. Default 1.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 18.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 12.
#' @param axisLabelSize Size of x/y-axis labels. Default 15.
#' @param legendSize size of legend. Default 10.
#' @param combinePlot Boolean. If multiple plots are generated (multiple
#' samples, etc.), will combined plots using `cowplot::plot_grid`.
#' @param sampleRelHeights If there are multiple samples and combining by "all",
#' the relative heights for each plot.
#' @param sampleRelWidths If there are multiple samples and combining by "all",
#' the relative widths for each plot.
#' Default TRUE.
#' @return a ggplot object of the scatter plot.
#' @examples
#' data(scExample, package="singleCellTK")
#' sce <- runBarcodeRankDrops(inSCE=sce)
#' plotBarcodeRankScatter(inSCE=sce)
#' @export
plotBarcodeRankScatter <- function(inSCE,
sample = NULL,
defaultTheme = TRUE,
dotSize = 1,
title = NULL,
titleSize = 18,
xlab = NULL,
ylab = NULL,
axisSize = 12,
axisLabelSize = 15,
legendSize = 10,
combinePlot = "none",
sampleRelHeights = 1,
sampleRelWidths = 1){
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop(
"'sample' must be the same length as the number",
" of columns in 'inSCE'"
)
}
} else {
sample <- rep(1, ncol(inSCE))
}
samples <- unique(sample)
meta <- S4Vectors::metadata(inSCE)$runBarcodeRanksMetaOutput
plotlist <- lapply(samples, function(x){
sampleMeta <- meta[[x]]
knee <- sampleMeta$dropletUtils_barcodeRank_knee
inflection <- sampleMeta$dropletUtils_barcodeRank_inflection
df <- data.frame(rank = sampleMeta$dropletUtils_barcodeRank_rank,
umi = sampleMeta$dropletUtils_barcodeRank_total)
p <- ggplot2::ggplot(df, ggplot2::aes_string(x="rank", y="umi")) +
ggplot2::geom_point(size=dotSize, shape=20) +
ggplot2::scale_x_log10() +
ggplot2::scale_y_log10()
p <- p + ggplot2::geom_hline(ggplot2::aes(yintercept=knee, linetype = "Knee"), colour = 'red') +
ggplot2::geom_hline(ggplot2::aes(yintercept=inflection, linetype = "Inflection"), colour= 'blue') +
ggplot2::scale_linetype_manual(name = "", values = c(2, 2),
guide = ggplot2::guide_legend(label.theme = ggplot2::element_text(size = legendSize),
override.aes = list(color = c("blue", "red"))))
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p)
}
if (!is.null(title)) {
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize),
axis.text.x = ggplot2::element_text(size = axisSize))
}else{
p <- p + ggplot2::xlab("Rank") +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize),
axis.text.x = ggplot2::element_text(size = axisSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize),
axis.text.y = ggplot2::element_text(size = axisSize))
}else{
p <- p + ggplot2::ylab("Total UMI Counts") +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize),
axis.text.y = ggplot2::element_text(size = axisSize))
}
return(p)
})
if (length(unique(samples)) > 1) {
names(plotlist) <- samples
plotlist <- list(Sample = plotlist)
} else {
plotlist <- plotlist[[1]]
}
##Needs to be turned off for Shiny User Interface
if(!combinePlot == "none"){
if(combinePlot %in% c("all") && length(unique(sample)) > 1){
return(cowplot::plot_grid(plotlist = unlist(plotlist,
recursive = FALSE),
align = "h",
vjust = 0,
rel_heights = sampleRelHeights,
rel_widths = sampleRelWidths))
}else if(combinePlot == "sample"){
return(plotlist)
}
}
return(plotlist)
}
#' @title Bar plot plotting tool.
#' @description Visualizes specified values via a violin plot.
#' @param y Numeric values to be plotted on y-axis.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @return a ggplot of the reduced dimensions.
#' @importFrom dplyr group_by
#' @importFrom dplyr summarize
#' @importFrom dplyr %>%
.ggBar <- function(y,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = 15) {
if (is.null(groupBy)) {
groupBy <- rep("Sample", length(y))
}
df <- data.frame(x = groupBy, y = y)
p <- ggplot2::ggplot(df) +
ggplot2::aes_string(
x = "groupBy",
y = "y"
)
p <- p + ggplot2::geom_bar(stat = "identity")
if (defaultTheme == TRUE) {
p <- .ggSCTKTheme(p)
}
if (!is.null(title)) {
p <- p + ggplot2::ggtitle(label = title) +
ggplot2::theme(plot.title = ggplot2::element_text(
hjust = 0.5,
size = titleSize
))
}
###
p <- p + ggplot2::theme(axis.text.y = ggplot2::element_text(size = axisSize))
###
if(length(unique(df$groupBy)) > 1){
p <- p + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 45,
hjust = 1,
size = axisSize))
}else{
p <- p + ggplot2::theme(axis.text.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
axis.title.x = ggplot2::element_blank())
}
if (gridLine == TRUE){
p <- p + ggplot2::theme(panel.grid.major.y = ggplot2::element_line("grey"))
}
if (!is.null(xlab)) {
p <- p + ggplot2::xlab(xlab) +
ggplot2::theme(axis.title.x = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(ylab)) {
p <- p + ggplot2::ylab(ylab) +
ggplot2::theme(axis.title.y = ggplot2::element_text(size = axisLabelSize))
}
if (!is.null(summary)){
if(summary == "mean"){
summ <- df %>% dplyr::group_by(groupBy) %>% dplyr::summarize(value = base::mean(y))
fun <- base::mean
}else if(summary == "median"){
summ <- df %>% dplyr::group_by(groupBy) %>% dplyr::summarize(value = stats::median(y))
fun <- stats::median
}else{
stop("`summary`` must be either `mean` or `median`.")
}
summ$statY <- max(df$y) + (max(df$y) - min(df$y)) * 0.1
summary <- paste(toupper(substr(summary, 1, 1)),
substr(summary, 2, nchar(summary)), sep="")
summ$label <- paste0(summary,": ", round(summ$value, 5))
p <- p + ggplot2::geom_text(data = summ,
ggplot2::aes_string(x = "groupBy",
y = "statY",
label = "label"),
size = 5)
p <- p + ggplot2::stat_summary(fun = fun, fun.min = fun,
fun.max = fun,
geom = "crossbar",
color = "red",
linetype = "dashed")
}
return(p)
}
#' @title Bar plot of colData.
#' @description Visualizes values stored in the colData slot of a
#' SingleCellExperiment object via a bar plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param coldata colData value that will be plotted.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param dots Boolean. If TRUE, will plot dots for each violin plot.
#' Default TRUE.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Boolean. If multiple plots are generated (multiple
#' samples, etc.), will combined plots using `cowplot::plot_grid`.
#' Default TRUE.
#' @return a ggplot of the barplot of coldata.
#' @examples
#' plotSCEBarColData(
#' inSCE = mouseBrainSubsetSCE,
#' coldata = "age", groupBy = "sex"
#' )
#' @export
plotSCEBarColData <- function(inSCE,
sample = NULL,
coldata,
groupBy = NULL,
dots = TRUE,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = TRUE) {
if (!is.null(coldata)) {
if (!coldata %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(coldata), "' is not found in ColData.")
}
coldata <- SummarizedExperiment::colData(inSCE)[, coldata]
} else {
stop("You must define the desired colData to plot.")
}
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(coldata)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
if (!is.null(sample)) {
if (length(sample) != ncol(inSCE)) {
stop("'sample' must be the same length as the number",
" of columns in 'inSCE'")
}
} else {
sample <- rep(1, ncol(inSCE))
}
p <- .ggBar(
y = coldata,
groupBy = groupBy,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize
)
return(p)
}
#' @title Bar plot of assay data.
#' @description Visualizes values stored in the assay slot of a
#' SingleCellExperiment object via a bar plot.
#' @param inSCE Input \linkS4class{SingleCellExperiment} object with saved
#' dimension reduction components or a variable with saved results. Required.
#' @param sample Character vector. Indicates which sample each cell belongs to.
#' @param useAssay Indicate which assay to use. Default "counts".
#' @param feature Name of feature stored in assay of SingleCellExperiment
#' object.
#' @param groupBy Groupings for each numeric value. A user may input a vector
#' equal length to the number of the samples in the SingleCellExperiment
#' object, or can be retrieved from the colData slot. Default NULL.
#' @param xlab Character vector. Label for x-axis. Default NULL.
#' @param ylab Character vector. Label for y-axis. Default NULL.
#' @param axisSize Size of x/y-axis ticks. Default 10.
#' @param axisLabelSize Size of x/y-axis labels. Default 10.
#' @param dotSize Size of dots. Default 1.
#' @param transparency Transparency of the dots, values will be 0-1. Default 1.
#' @param defaultTheme Removes grid in plot and sets axis title size to 10
#' when TRUE. Default TRUE.
#' @param gridLine Adds a horizontal grid line if TRUE. Will still be
#' drawn even if defaultTheme is TRUE. Default FALSE.
#' @param summary Adds a summary statistic, as well as a crossbar to the
#' violin plot. Options are "mean" or "median". Default NULL.
#' @param title Title of plot. Default NULL.
#' @param titleSize Size of title of plot. Default 15.
#' @param combinePlot Boolean. If multiple plots are generated (multiple
#' samples, etc.), will combined plots using `cowplot::plot_grid`.
#' Default TRUE.
#' @return a ggplot of the barplot of assay data.
#' @examples
#' plotSCEBarAssayData(
#' inSCE = mouseBrainSubsetSCE,
#' feature = "Apoe", groupBy = "sex"
#' )
#' @export
plotSCEBarAssayData <- function(inSCE,
sample = NULL,
useAssay = "counts",
feature,
groupBy = NULL,
xlab = NULL,
ylab = NULL,
axisSize = 10,
axisLabelSize = 10,
dotSize = 1,
transparency = 1,
defaultTheme = TRUE,
gridLine = FALSE,
summary = NULL,
title = NULL,
titleSize = NULL,
combinePlot = TRUE) {
mat <- getBiomarker(
inSCE = inSCE,
useAssay = useAssay,
gene = feature,
binary = "Continuous"
)
counts <- mat[, 2]
if (!is.null(groupBy)) {
if (length(groupBy) > 1) {
if (length(groupBy) != length(counts)) {
stop("The input vector for 'groupBy' needs to be the same
length as the number of samples in your
SingleCellExperiment object.")
}
} else {
if (!groupBy %in% names(SummarizedExperiment::colData(inSCE))) {
stop("'", paste(groupBy), "' is not found in ColData.")
}
groupBy <- as.character(SummarizedExperiment::colData(inSCE)[, groupBy])
}
}
p <- .ggBar(
y = counts,
groupBy = groupBy,
xlab = xlab,
ylab = ylab,
axisSize = axisSize,
axisLabelSize = axisLabelSize,
dotSize = dotSize,
transparency = transparency,
defaultTheme = defaultTheme,
title = title,
titleSize = titleSize
)
return(p)
}
.binSCTK <- function(value, bin, binLabel = NULL) {
if (!is.null(binLabel)) {
if (length(bin) == 1) {
if (bin != length(binLabel)) {
stop("'binLabel' must be equal to the bin length")
}
} else if (length(bin) > 1) {
if (bin != length(binLabel) + 1) {
stop("'binLabel' must be equal to the bin length")
}
}
}
value.bin <- cut(x = value, breaks = bin, labels = binLabel)
return(value.bin)
}
.ggSCTKCombinePlots <- function(plotlist,
ncols = NULL,
nrows = NULL,
combinePlot = "all",
relHeights = 1,
relWidths = 1,
labels = "default",
labelPositionX = NULL,
labelPositionY = NULL,
labelSize = 20,
samplePerColumn = TRUE,
sampleRelHeights = 1,
sampleRelWidths = 1) {
if ("Violin" %in% names(plotlist)) {
plotlistViolin <- plotlist$Violin
} else {
plotlistViolin <- NULL
}
if ("Sample" %in% names(plotlist)) {
plotlistSample <- plotlist$Sample
if (samplePerColumn) {
ncols <- 1
nrowSub <- 1
sampleRelHeights <- 1
}else{
nrowSub = NULL
}
plotlistSample <- lapply(plotlistSample, function(x) {
if(all(class(x) %in% c("gg","ggplot"))){
return(x)
}else if (inherits(x, "list")){
return(cowplot::plot_grid(
plotlist = x,
align = "h",
nrow = nrowSub,
vjust = 0,
rel_heights = sampleRelHeights,
rel_widths = sampleRelWidths
))
}
})
}else{
plotlistSample <- NULL
}
if(!is.null(plotlistViolin) | !is.null(plotlistSample)){
plotlist <- c(plotlistViolin, plotlistSample)
}
# To make the resulting plot close to a square as possible
if (is.null(ncols) && is.null(nrows)) {
ncols <- round(sqrt(length(plotlist)))
}
if (combinePlot == "all") {
if (!is.null(labels) && labels != "none") {
# If default, sample name will be used as labels
if(length(labels) == 1){
if (labels == "default") {
if(!is.null(names(plotlist))){
labels <- names(plotlist)
}
}
}
listNamePlot <- list()
if(is.null(labelPositionX)){
labelPositionX = rep(0, length(plotlist))
}
if(is.null(labelPositionY)){
labelPositionY = rep(1, length(plotlist))
}
for(x in seq_along(plotlist)){
labeled <- plotlist[[x]] + cowplot::draw_plot_label(
labels[x],
x = labelPositionX[x],
y = labelPositionY[x],
size = labelSize)
listNamePlot[[x]] <- labeled
}
plotlist <- listNamePlot
}
plotRes <- cowplot::plot_grid(
plotlist = plotlist,
ncol = ncols,
nrow = nrows,
rel_heights = relHeights,
rel_widths = relWidths
)
return(plotRes)
} else if (combinePlot == "sample") {
#Will happen if "sample" is chosen and multiple samples exist,
#whcih means there will be a plotlistViolin object
if (!is.null(plotlistViolin)) {
return(list(Violin = plotlistViolin, Sample = plotlistSample))
#Will happen when calling the non-QC plot fxns (ie, plotSCEScatter, plotSCEViolin)
#for multiple samples, meaning no merging has occurred across plots
}else if (!is.null(plotlistSample)){
return(plotlistSample)
# #Will happen when?
# }else if(length(plotlist) == 1) {
# return(plotlist[[1]])
#Will happen when sample = NULL, combinePlot = "sample", meaning up to this point
#the "plotlist" should be a list of individual plots for only one sample
} else{
return(cowplot::plot_grid(
plotlist = plotlist,
ncol = ncols,
nrow = nrows,
rel_heights = relHeights,
rel_widths = relWidths
))
}
}
}
.ggSCTKTheme <- function(gg) {
return(gg + ggplot2::theme_bw() +
ggplot2::theme(
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
axis.text = ggplot2::element_text(size = 10),
axis.title = ggplot2::element_text(size = 10)
))
}
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